JP7017179B2 - Inspection system, inspection method, and program - Google Patents

Description

The present invention relates to inspection systems, inspection methods, and programs, and is particularly suitable for use in inspecting the tracks of railway vehicles.

When a railroad vehicle travels on the track, the position of the track changes due to the load from the railroad vehicle. When such a change in track occurs, the railroad vehicle may behave abnormally. Therefore, conventionally, it has been practiced to detect an abnormality in a track by running a railroad vehicle on the track.

In Patent Document 1, it is possible to estimate the amount of deviation by substituting the angular displacement of the wheel set in the yaw direction, the state variable obtained by the Kalman filter, and the anteroposterior force into the equation of motion that describes the yawing of the wheel set. Are listed.

International Publication No. 2017/164133 JP-A-2017-53773

The present inventors have found that in the technique described in Patent Document 1, when a disturbance not considered in the equation of motion occurs, the error of the estimated value of the amount of deviation becomes large.
The present invention has been made in view of the above problems, and an object of the present invention is to enable highly accurate detection of irregularities in the track of a railway vehicle without using a special measuring device.

The inspection system of the present invention is a data acquisition means for acquiring measurement data which is time-series data of measured values measured by traveling a railroad vehicle having a vehicle body, a trolley, and a wheel axis on a track, and a first physical quantity. Based on the first orbital state calculating means for calculating the estimated value of, the estimated value of the first physical quantity calculated by the first orbital state calculating means, and the actual value of the first physical quantity. A correction amount calculating means for calculating a correction amount for the estimated value of the first physical quantity, a second orbital state calculating means for calculating the estimated value of the first physical quantity after the correction amount is calculated, and the above. It has an orbital state correction means for correcting an estimated value of the first physical quantity calculated by the second orbital state calculation means by using the correction amount, and the measurement data is a measured value of a front-back direction force. The front-rear direction force is a front-rear direction force generated in a member arranged between the wheel shaft and the bogie on which the wheel shaft is provided, and the member is a member for supporting the axle box. The front-rear direction is a direction along the traveling direction of the railroad vehicle, the first physical quantity is a physical quantity that reflects the state of the track, and the first track state calculation means and the second physical quantity are present. The orbital state calculating means of the above is the first physical quantity using the relational expression showing the relationship between the first physical quantity and the anteroposterior force at the position of the wheel axis and the measured value of the anteroposterior force. The measured value of the anteroposterior force for calculating the estimated value of and used in the first orbital state calculating means is included in the measurement data acquired by the data acquisition means before the correction amount is calculated. The measured value of the anteroposterior force used in the second orbital state calculation means is included in the measurement data acquired by the data acquisition means after the correction amount is calculated.

The inspection method of the present invention includes a data acquisition step of acquiring measurement data which is time-series data of measured values measured by traveling a railroad vehicle having a vehicle body, a trolley, and a wheel axis on a track, and a first physical quantity. Based on the first orbital state calculation step for calculating the estimated value of, the first estimated physical quantity calculated by the first orbital state calculation step, and the actual value of the first physical quantity. A correction amount calculation step of calculating a correction amount for the estimated value of the first physical quantity, a second orbital state calculation step of calculating the estimated value of the first physical quantity after the correction amount is calculated, and the above. It has an orbital state correction step of correcting the estimated value of the first physical quantity calculated by the second orbital state calculation step by using the correction amount, and the measurement data is a measured value of a front-back direction force. The front-rear direction force is a front-rear direction force generated in a member arranged between the wheel shaft and the bogie on which the wheel shaft is provided, and the member is a member for supporting the axle box. Yes, the front-rear direction is a direction along the traveling direction of the railroad vehicle, the first physical quantity is a physical quantity that reflects the state of the track, and the first track state calculation step and the second physical quantity. In the orbital state calculation step, the first physical quantity is used by using a relational expression showing the relationship between the first physical quantity at the position of the wheel axis and the anteroposterior force, and the measured value of the anteroposterior force. The measured value of the anteroposterior force used in the first orbital state calculation step is included in the measurement data acquired by the data acquisition step before the correction amount is calculated. The measured value of the anteroposterior force used in the second orbital state calculation step is included in the measurement data acquired by the data acquisition step after the correction amount is calculated.

The program of the present invention includes a data acquisition process for acquiring measurement data, which is time-series data of measured values measured by traveling a railroad vehicle having a vehicle body, a trolley, and a wheel axis on a track, and a first physical quantity. The above is based on the first orbital state calculation step for calculating the estimated value, the estimated value of the first physical quantity calculated by the first orbital state calculation step, and the actual value of the first physical quantity. A correction amount calculation step for calculating a correction amount for an estimated value of a first physical quantity, a second orbital state calculation step for calculating an estimated value for the first physical quantity after the correction amount is calculated, and the first A computer is made to execute an orbital state correction step of correcting the estimated value of the first physical quantity calculated by the orbital state calculation step 2 by using the correction amount, and the measurement data is the measurement of the forward / backward force. The front-rear direction force including a value is a front-rear direction force generated in a member arranged between the wheel shaft and the carriage on which the wheel shaft is provided, and the member is a member for supporting the axle box. The front-rear direction is a direction along the traveling direction of the railroad vehicle, and the first physical quantity is a physical quantity that reflects the state of the track, and the first track state calculation step and the first physical quantity. In the track state calculation step 2, the first physical quantity at the position of the wheel axis and the front-rear direction force are used, and the first-first physical quantity is used. The estimated value of the physical quantity is calculated, and the measured value of the anteroposterior force used in the first orbital state calculation step is included in the measurement data acquired by the data acquisition step before the correction amount is calculated. The measured value of the anteroposterior force used in the second orbital state calculation step is characterized by being included in the measurement data acquired by the data acquisition step after the correction amount is calculated.

FIG. 1 is a diagram showing an outline example of a railroad vehicle. FIG. 2 is a diagram conceptually showing the main motion directions of the components of a railroad vehicle. FIG. 3A is a diagram showing an example of the amount of deviation in a straight orbit. FIG. 3B is a diagram showing an example of the amount of deviation in the curved orbit. FIG. 4 is a diagram showing an example of the functional configuration of the inspection device. FIG. 5 is a diagram showing an example of the hardware configuration of the inspection device. FIG. 6 is a flowchart showing an example of the first preprocessing. FIG. 7 is a flowchart showing an example of the second preprocessing. FIG. 8 is a flowchart showing an example of this process. FIG. 9 is a diagram showing an example of the distribution of the eigenvalues of the autocorrelation matrix. FIG. 10 is a diagram showing an example of time-series data (measured value) of the measured value of the front-back direction force and time-series data (calculated value) of the predicted value of the front-back direction force. FIG. 11 is a diagram showing an example of time-series data of high-frequency components of anteroposterior force. FIG. 12A is a diagram showing a first example of the relationship between the estimated value of the amount of deviation, the actual value of the amount of deviation, the traveling speed of the railroad vehicle, and the curvature of the rail, and the distance from the starting point of the railroad vehicle. be. FIG. 12B is a diagram showing a second example of the relationship between the estimated value of the amount of deviation, the actual value of the amount of deviation, the traveling speed of the railroad vehicle, and the curvature of the rail, and the distance from the starting point of the railroad vehicle. be. FIG. 13A is a diagram showing a third example of the relationship between the estimated value of the amount of deviation, the actual value of the amount of deviation, the traveling speed of the railroad vehicle, and the curvature of the rail, and the distance from the starting point of the railroad vehicle. be. FIG. 13B is a diagram showing a fourth example of the relationship between the estimated value of the amount of deviation, the actual value of the amount of deviation, the traveling speed of the railroad vehicle, and the curvature of the rail, and the distance from the starting point of the railroad vehicle. be. FIG. 14A is a diagram showing a fifth example of the relationship between the estimated value of the amount of deviation, the actual value of the amount of deviation, the traveling speed of the railroad vehicle, and the curvature of the rail, and the distance from the starting point of the railroad vehicle. be. FIG. 14B is a diagram showing a sixth example of the relationship between the estimated value of the amount of deviation, the actual value of the amount of deviation, the traveling speed of the railroad vehicle, and the curvature of the rail, and the distance from the starting point of the railroad vehicle. be. FIG. 15 is a diagram illustrating an example of flange contact. FIG. 16A is a diagram showing a first example of the relationship between the second correction amount and the distance from the starting point of the railway vehicle. FIG. 16B is a diagram showing a second example of the relationship between the second correction amount and the distance from the starting point of the railway vehicle. FIG. 16C is a diagram showing a third example of the relationship between the second correction amount and the distance from the starting point of the railway vehicle. FIG. 17A is a diagram showing a first example of the relationship between the corrected estimated value of the amount of deviation and the distance from the starting point of the railroad vehicle. FIG. 17B is a diagram showing a second example of the relationship between the corrected estimated value of the amount of deviation and the distance from the starting point of the railroad vehicle. FIG. 18A is a diagram showing a third example of the relationship between the corrected estimated value of the amount of deviation and the distance from the starting point of the railroad vehicle. FIG. 18B is a diagram showing a fourth example of the relationship between the corrected estimated value of the amount of deviation and the distance from the starting point of the railroad vehicle. FIG. 19A is a diagram showing a fifth example of the relationship between the corrected estimated value of the amount of deviation and the distance from the starting point of the railroad vehicle. FIG. 19B is a diagram showing a sixth example of the relationship between the corrected estimated value of the amount of deviation and the distance from the starting point of the railroad vehicle. FIG. 20 is a diagram showing an example of the configuration of the inspection system.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
(Overview)
First, an outline of the embodiment of the present invention will be described.
FIG. 1 is a diagram showing an outline example of a railroad vehicle. In FIG. 1, the railroad vehicle is assumed to travel in the positive direction of the x-axis (the x-axis is an axis along the traveling direction of the railroad vehicle). Further, it is assumed that the z-axis is in the direction perpendicular to the track 16 (ground) (in the height direction of the railroad vehicle). It is assumed that the y-axis is a horizontal direction perpendicular to the traveling direction of the railway vehicle (a direction perpendicular to both the traveling direction and the height direction of the railway vehicle). In addition, railroad vehicles shall be commercial vehicles. In each figure, those marked with ● in ○ indicate the direction from the back side of the paper to the front side, and those marked with × in ○ indicate the direction from the front side of the paper. Indicates the direction toward the back side.

As shown in FIG. 1, in the present embodiment, the railroad vehicle has a vehicle body 11, bogies 12a and 12b, and wheel sets 13a to 13d. As described above, in the present embodiment, a railroad vehicle in which two bogies 12a and 12b and four sets of wheel sets 13a to 13d are provided in one vehicle body 11 will be described as an example. The wheel sets 13a to 13d have axles 15a to 15d and wheels 14a to 14d provided at both ends thereof. In the present embodiment, the case where the bogies 12a and 12b are bolsterless bogies will be described as an example. Note that, for convenience of notation, only one wheel 14a to 14d of the wheel sets 13a to 13d is shown in FIG. 1, but wheels are also provided on the other of the wheel sets 13a to 13d (in the example shown in FIG. 1, the wheel is provided). There are a total of 8). Further, the railroad vehicle has components other than the components shown in FIG. 1 (components and the like described in the equation of motion described later), but for convenience of notation, the components are not shown in FIG. For example, the bogies 12a and 12b have a bogie frame, a pillow spring, and the like. Further, axle boxes are arranged on both sides of each wheel set 13a to 13d in the direction along the y-axis. Further, the bogie frame and the axle box are connected to each other by the axle box support device. The axle box support device is a device (suspension) arranged between the axle box and the bogie frame. The axle box support device absorbs the vibration transmitted from the track 16 to the railroad vehicle. Further, the axle box support device suppresses the movement of the axle box with respect to the bogie frame in the direction along the x-axis and the direction along the y-axis (preferably so that the movement does not occur). Support the axle box with the position of the axle box restricted with respect to the bogie frame. The axle box support devices are arranged on both sides of each wheel set 13a to 13d in the direction along the y-axis. Since the railway vehicle itself can be realized by a known technique, detailed description thereof will be omitted here.

When a railroad vehicle travels on the track 16, the acting force (creep force) between the wheels 14a to 14d and the track 16 becomes a vibration source, and the vibration propagates sequentially to the wheel sets 13a to 13d, the bogies 12a, 12b, and the vehicle body 11. .. FIG. 2 is a diagram conceptually showing the main motion directions of the components of the railway vehicle (wheel sets 13a to 13d, bogies 12a, 12b, vehicle body 11). The x-axis, y-axis, and z-axis shown in FIG. 2 correspond to the x-axis, y-axis, and z-axis shown in FIG. 1, respectively.

As shown in FIG. 2, in the present embodiment, the wheel sets 13a to 13d, the bogies 12a, 12b, and the vehicle body 11 rotate with the x-axis as the rotation axis and the z-axis as the rotation axis. And the case of performing the motion in the direction along the y-axis will be described as an example. In the following description, the motion of rotating with the x-axis as the rotation axis is referred to as rolling as necessary, and the rotation direction with the x-axis as the rotation axis is referred to as the rolling direction as necessary, and is along the x-axis. The direction is referred to as the front-back direction as necessary. The front-rear direction is the traveling direction of the railway vehicle. In the present embodiment, it is assumed that the direction along the x-axis is the traveling direction of the railway vehicle. Further, the motion of rotating with the z-axis as the rotation axis is referred to as yawing as necessary, and the rotation direction with the z-axis as the rotation axis is referred to as the yawing direction as necessary, and a direction along the z-axis is required. It is called the vertical direction according to the above. The vertical direction is a direction perpendicular to the orbit 16. Further, the movement in the direction along the y-axis is referred to as lateral vibration as necessary, and the direction along the y-axis is referred to as the left-right direction as necessary. The left-right direction is a direction perpendicular to both the front-rear direction (the traveling direction of the railway vehicle) and the up-down direction (the direction perpendicular to the track 16). In addition, the railroad vehicle also performs other exercises, but these exercises are not considered for the sake of simplicity in each embodiment. However, these exercises may be considered.

As described in Patent Document 1, the present inventors are arranged between the wheel sets 13a to 13b (13c to 13d) and the trolley 12a (12b) on which the wheel sets 13a to 13b (13c to 13d) are provided. As an example of the first physical quantity that reflects the orbital irregularity (the appearance defect of the orbit 16), the method of calculating the deviation amount is devised by using the measured value of the force in the front-rear direction generated in the member. In the following description, the front-back force generated in this member will be referred to as a front-back force, if necessary.

The amount of deviation is an equation based on an equation of motion that describes the motion of a railroad vehicle when traveling on a straight track, and is calculated using an equation showing the relationship between the amount of deviation and the forward / backward force. The orbit 16 includes a straight line portion and a curved line portion. In the following description, the straight portion of the orbit 16 is referred to as a straight orbit as necessary, and the curved portion of the orbit 16 is referred to as a curved orbit as necessary.

When filtering by a filter (Kalman filter) that performs data assimilation, which will be described later, if a state equation is constructed using an equation of motion that describes the motion of a railroad vehicle traveling on a curved track, the state variables may diverge. Therefore, the equation of motion for filtering by a filter (Kalman filter) for assimilating data is constructed using an equation of motion that describes the motion of a railroad vehicle traveling on a straight track.
In the equation of motion that describes the motion of a railroad vehicle traveling on a curved track, it is necessary to consider the centrifugal force that the railroad vehicle receives during traveling. Therefore, the equation of motion that describes the motion of a railroad vehicle traveling on a curved track includes a term that includes the radius of curvature of the rail. Therefore, when a railroad vehicle is traveling on a curved track, a state variable is derived using a data assimilation filter (Kalman filter) constructed using an equation of motion that describes the motion of the railroad vehicle traveling on a straight track. , There is a risk that state variables cannot be derived with high accuracy.

The present inventors have focused on the fact that when a railroad vehicle travels on a curved track, the measured value of the forward / backward force has a certain bias with respect to the case where the railroad vehicle travels on a straight track. Therefore, the present inventors have created an equation of motion that describes the motion of a railroad vehicle during traveling on a straight track by reducing the low frequency component (behavior of the bias) from the time-series data of the measured values of the longitudinal force. Even if a filter (Kalman filter) that performs data assimilation, which will be described later, is constructed using the equation based on the equation, it is possible to reduce the low frequency component caused by the railroad vehicle traveling on a curved track from the estimated value of the state variable. Thought. From this, the present inventors use time-series data of the value of the front-rear force with reduced low-frequency components as an equation based on the equation of motion that describes the motion of the railway vehicle when traveling on a straight track. I came up with the idea of calculating the amount of deviation by giving it to the equation showing the relationship between the amount of deviation and the forward / backward force. By calculating the amount of deviation in this way, the amount of deviation in the curved track is calculated even though the equation based on the equation of motion that describes the motion of the railway vehicle when traveling on the straight track is used. be able to. Further, the calculation formula for the amount of deviation is the same regardless of whether it is a curved orbit or a straight orbit.

Furthermore, we have determined that, depending on at least one of the running state of the railroad vehicle and the installation state of the track 16, disturbances that are not considered in the equation of motion that describes the motion of the railroad vehicle affect the measured value of the longitudinal force. Therefore, it was found that the calculation accuracy of the amount of deviation may decrease. The running state of a railroad vehicle that is prone to such disturbances includes, for example, a state in which the railroad vehicle is running at a low speed, a state in which the vehicle is suddenly decelerating, a state in which the vehicle is rapidly accelerating, and a state in which the railway vehicle is in contact with the flange. There is a state of running and a state of running at the seam of the rail. Further, in the installation situation of the track 16 where such disturbance is likely to occur, for example, a state where the rail is a sharp curve (a state where the curvature of the rail is large), and the track 16 is installed in a place where a specific structure is present. There is a state where the track is, a state where the rail has a seam, and a state where the track 16 is a trackless track. Specific structures include, for example, station platforms, bridges, tunnels, turnouts, railroad crossings, and guardrails.

Such a disturbance is represented by the difference between the estimated value and the measured value of the amount of deviation. For the same railroad vehicle, the measured data does not change significantly due to the characteristics unique to the railroad vehicle. Examples of the characteristics peculiar to the railroad vehicle include individual differences of the vehicle body 11, individual differences of the bogies 12a and 12b, individual differences of the wheel sets 13a to 13d, and individual differences of the strain gauge for measuring the front-rear direction force. In addition, the state of these connections is also mentioned as a characteristic peculiar to railway vehicles. Further, if the same railroad vehicle is used, the traveling speed at each position of the track 16 does not change significantly. From this, the present inventors, when the same railroad vehicle is traveling at the same position, the difference between the estimated value and the measured value of the deviation amount as described above does not change significantly depending on the date and time when the railroad vehicle travels. I found. Therefore, at each position of the track 16 on which the railroad vehicle travels, the difference between the estimated value of the deviation amount and the measured value as described above is obtained in advance as a correction amount for the estimated value of the deviation amount. After that, when the railroad vehicle travels on the track 16, the estimated value of the amount of deviation is obtained again at each position of the track 16. The estimated value of the deviation amount thus obtained is corrected by the correction amount at the position of the orbit 16 where the estimated value is obtained. In this way, the amount of deviation is obtained at each position of the orbit 16. In the present embodiment, the corrected street deviation amount is used as the final street deviation amount.

(Equation of motion)
Next, an example of an equation of motion that describes the motion of a railroad vehicle when traveling on a straight track will be described. In this embodiment, the equation of motion described in Patent Document 1 will be taken as an example, and a case where a railroad vehicle has 21 degrees of freedom will be described as an example. That is, it is assumed that the wheel sets 13a to 13d perform a motion in the left-right direction (lateral vibration) and a motion in the yawing direction (yawing) (2 × 4 sets = 8 degrees of freedom). Further, it is assumed that the carriages 12a and 12b perform a motion in the left-right direction (lateral vibration), a motion in the yawing direction (yaw), and a motion in the rolling direction (rolling) (3 × 2 set = 6 degrees of freedom). Further, it is assumed that the vehicle body 11 performs a motion in the left-right direction (lateral vibration), a motion in the yawing direction (yaw), and a motion in the rolling direction (rolling) (3 × 1 set = 3 degrees of freedom). Further, it is assumed that the air springs (pillow springs) provided for the bogies 12a and 12b each perform motion (rolling) in the rolling direction (1 x 2 sets = 2 degrees of freedom). Further, it is assumed that the yaw dampers provided for the bogies 12a and 12b each perform a movement (yaw) in the yawing direction (1 x 2 sets = 2 degrees of freedom).

The degree of freedom is not limited to 21 degrees of freedom. Increasing the degree of freedom improves the calculation accuracy, but increases the calculation load. In addition, the operation of the Kalman filter, which will be described later, may become unstable. The degree of freedom can be appropriately determined in consideration of these points. Further, the following equation of motion describes the operation of each component (vehicle body 11, carriages 12a, 12b, wheel shafts 13a to 13d) in each direction (horizontal direction, yawing direction, rolling direction), for example, Non-Patent Document 1. It can be realized by expressing it based on the description of 2. Therefore, here, the outline of each equation of motion will be described, and detailed description thereof will be omitted. In each of the following equations, there is no term including the radius of curvature (curvature) of the track 16 (rail). That is, each of the following equations is an equation expressing that the railway vehicle travels on a straight track. In the formula expressing that a railroad vehicle travels on a curved track, the radius of curvature of the track 16 (rail) is set to infinity (curvature is 0 (zero)), thereby expressing that the railroad vehicle travels on a straight track. Is obtained.

In each of the following equations, the subscript w represents a wheel set 13a to 13d. Variables with the subscript w (only) indicate that they are common to the wheel sets 13a to 13d. The subscripts w1, w2, w3, and w4 represent wheel sets 13a, 13b, 13c, and 13d, respectively.
The subscripts t and T represent the carts 12a and 12b. Variables with the subscripts t and T (only) indicate that they are common to the carriages 12a and 12b. The subscripts t1 and t2 represent the carts 12a and 12b, respectively.
Subscripts b and B represent the vehicle body 11.

The subscript x represents the front-back direction or the rolling direction, the subscript y represents the left-right direction, and the subscript z represents the vertical direction or the yawing direction.
Further, "・ ・" and "・" attached above the variables represent the second-order time derivative and the first-order time derivative, respectively.
In the explanation of the equation of motion below, the explanation of the variables already mentioned will be omitted if necessary. Further, the equation of motion itself is the same as that described in Patent Document 1.

[Horizontal vibration of wheel set]
The equations of motion that describe the lateral vibrations (movements in the left-right direction) of the wheel sets 13a to 13d are expressed by the following equations (1) to (4).

m _w is the mass of the wheel sets 13a to 13d. y _w1 ... (In the equation, ... is attached above y _w1 (hereinafter, the same applies to other variables)) is the acceleration of the wheel set 13a in the left-right direction. f ₂ is a lateral creep coefficient (note that the lateral creep coefficient f ₂ may be given for each wheel set 13a to 13d). v is the traveling speed of the railway vehicle. y _w1 · (in the equation, · is affixed above y _w1 (hereinafter, the same applies to other variables)) is the velocity of the wheel set 13a in the left-right direction. C _wy is a damping constant in the left-right direction of the axle box support device connecting the axle box and the wheel set. y _t1 · is the speed of the carriage 12a in the left-right direction. a represents 1/2 of the distance in the front-rear direction between the wheel sets 13a / 13b, 13c / 13d provided on the bogies 12a, 12b (wheel sets 13a / 13b, 13c / 13d provided on the bogies 12a, 12b). The distance between them will be 2a). ψ _t1 · is the angular velocity of the bogie 12a in the yawing direction. h ₁ is the vertical distance between the center of the axle and the center of gravity of the bogie 12a. φ _t1 · is the angular velocity of the carriage 12a in the rolling direction. ψ _w1 is the amount of rotation (angular displacement) of the wheel set 13a in the yawing direction. K _wy is a spring constant in the left-right direction of the axle box support device. y _w1 is a displacement of the wheel set 13a in the left-right direction. y _t1 is the displacement of the carriage 12a in the left-right direction. ψ _t1 is the amount of rotation (angular displacement) of the carriage 12a in the yawing direction. φ _t1 is the amount of rotation (angular displacement) of the carriage 12a in the rolling direction. It should be noted that each variable of the equations (2) to (4) is represented by replacing the variable of the equation (1) according to the meaning of the subscripts described above.

[Wheel set yawing]
The equations of motion that describe the yawing of the wheel sets 13a to 13d are expressed by the following equations (5) to (8).

I _wz is the moment of inertia in the yawing direction of the wheel sets 13a to 13d. ψ _w1 ... Is an angular acceleration of the wheel set 13a in the yawing direction. f ₁ is a vertical creep coefficient. b is the distance in the left-right direction between the contact points between the two wheels attached to the wheel sets 13a to 13d and the track 16 (rail). ψ _w1 · is the angular velocity of the wheel set 13a in the yawing direction. C _wx is a damping constant in the front-rear direction of the axle box support device. b ₁ represents a length of 1/2 of the distance between the axle box support devices in the left-right direction (the distance between the two axle box support devices provided on the left and right with respect to one wheel set is 2b ₁ ). Become). γ is the tread slope. r is the radius of the wheels 14a to 14d. y _R1 is an amount of deviation at the position of the wheel set 13a. s _a is an offset amount in the front-rear direction from the center of the axles 15a to 15d to the axle box support spring. y _t1 is the displacement of the carriage 12a in the left-right direction. K _wx is a spring constant in the front-rear direction of the axle box support device. It should be noted that each variable of the equations (6) to (8) is represented by replacing the variable of the equation (5) according to the meaning of the subscripts described above. However, y _R2 , y _R3 , and y _R4 are deviation amounts at the positions of the wheel sets 13b, 13c, and 13d, respectively.

Here, the street deviation is a left-right displacement in the longitudinal direction of the rail as described in the Japanese Industrial Standards (JIS E 1001: 2001). The amount of deviation is the amount of displacement. FIG. 3 shows an example of the amount of deviation y _R1 at the position of the wheel set 13a. In FIG. 3A, a case where the orbit 16 is a straight orbit will be described as an example. In FIG. 3B, a case where the orbit 16 is a curved orbit will be described as an example. In FIGS. 3A and 3B, 16a indicates a rail and 16b indicates a sleeper. In FIG. 3A, it is assumed that the wheel 14a of the wheel set 13a is in contact with the rail 16a at the position 301. In FIG. 3B, it is assumed that the wheel 14a of the wheel set 13a is in contact with the rail 16a at the position 302. The amount of deviation y _R1 at the position of the wheel set 13a is the distance in the left-right direction between the contact position between the wheel 14a of the wheel set 13a and the rail 16a and the position of the rail 16a assuming a normal state. .. The position of the wheel set 13a is the contact position between the wheel 14a of the wheel set 13a and the rail 16a. The amount of deviation y _R2 , y _R3 , and y _R4 at the positions of the wheel sets 13b, 13c, and 13d are also defined in the same manner as the amount of deviation y _R1 at the position of the wheel set 13a.

[Horizontal vibration of the dolly]
The equations of motion that describe the lateral vibrations (movements in the left-right direction) of the carriages 12a and 12b are expressed by the following equations (9) and (10).

m _T is the mass of the carts 12a and 12b. y _t1 ... Is the acceleration of the carriage 12a in the left-right direction. _c'2 is a damping constant of the left-right moving damper. h ₄ is the distance between the center of gravity of the bogie 12a and the left-right moving damper in the vertical direction. y _b · is the speed of the vehicle body 11 in the left-right direction. L represents 1/2 of the distance between the centers of the carriages 12a and 12b in the front-rear direction (the distance between the centers of the carriages 12a and 12b in the front-rear direction is 2L). ψ _b · is the angular velocity of the vehicle body 11 in the yawing direction. h ₅ is the vertical distance between the left-right moving damper and the center of gravity of the vehicle body 11. φ _b · is the angular velocity of the vehicle body 11 in the rolling direction. y _w2 · is the speed of the wheel set 13b in the left-right direction. _k'2 is a spring constant in the left-right direction of the air spring (pillow spring). h ₂ is the distance in the vertical direction between the center of gravity of the bogies 12a and 12b and the center of the air spring (pillow spring). y _b is the displacement of the vehicle body 11 in the left-right direction. ψ _b is the amount of rotation (angular displacement) of the vehicle body 11 in the yawing direction. h ₃ is the vertical distance between the center of the air spring (pillow spring) and the center of gravity of the vehicle body 11. φ _b is the amount of rotation (angular displacement) of the vehicle body 11 in the rolling direction. Each variable in Eq. (10) is represented by replacing the variable in Eq. (9) according to the meaning of the subscripts described above.

[Bogie yawing]
The equations of motion that describe the yawing of the carriages 12a and 12b are expressed by the following equations (11) and (12).

_Itz is the moment of inertia of the bogies 12a and 12b in the yawing direction. ψ _t1 ... Is the angular acceleration of the bogie 12a in the yawing direction. ψ _w2 · is the angular velocity of the wheel set 13b in the yawing direction. ψ _w2 is the amount of rotation (angular displacement) of the wheel set 13b in the yawing direction. y _w2 is a displacement of the wheel set 13b in the left-right direction. _k'0 is the rubber bush rigidity of the yaw damper. _b'0 represents 1/2 of the distance between the two yaw dampers arranged left and right with respect to the trolleys 12a and 12b in the left-right direction (the distance between the two yaw dampers arranged left and right with respect to the trolleys 12a and 12b in the left-right direction). Becomes _2b'0 ). ψ _y1 is the amount of rotation (angular displacement) of the yaw damper arranged on the carriage 12a in the yawing direction. k ″ ₂ is a spring constant in the left-right direction of the air spring (pillow spring). b ₂ represents 1/2 of the distance between the two air springs (pillow springs) arranged on the left and right with respect to the bogies 12a and 12b in the left-right direction (two air springs arranged on the left and right with respect to the bogies 12a and 12b). The distance between the (pillow springs) in the left-right direction is 2b ₂ ). It should be noted that each variable of the equation (12) is represented by reading the variable of the equation (11) according to the meaning of the subscript described above.

[Rolling dolly]
The equations of motion that describe the rolling of the carriages 12a and 12b are expressed by the following equations (13) and (14).

_ITx is the moment of inertia of the carriages 12a and 12b in the rolling direction. φ _t1 ... Is an angular acceleration in the rolling direction of the carriage 12a. c ₁ is a damping constant in the vertical direction of the shaft damper. b'1 represents _1/2 of the distance in the left-right direction of the two shaft dampers arranged on the left and right with respect to the bogies 12a and 12b (the left-right direction of the two shaft dampers arranged on the left and right with respect to the bogies 12a and 12b). The interval in is _2b'1 ). c ₂ is a damping constant in the vertical direction of the air spring (pillow spring). _φa1 · is the angular velocity in the rolling direction of the air spring (pillow spring) arranged on the bogie 12a. k ₁ is a spring constant in the vertical direction of the shaft spring. λ is a value obtained by dividing the volume of the main body of the air spring (pillow spring) by the volume of the auxiliary air chamber. k ₂ is a spring constant in the vertical direction of the air spring (pillow spring). φ _a1 is the amount of rotation (angular displacement) of the air spring (pillow spring) arranged on the bogie 12a in the rolling direction. k ₃ is the equivalent rigidity due to the change in the effective pressure receiving area of the air spring (pillow spring). It should be noted that each variable of the equation (14) is represented by reading the variable of the equation (13) according to the meaning of the subscript described above. However, φ _a2 is the amount of rotation (angular displacement) of the air spring (pillow spring) arranged on the bogie 12b in the rolling direction.

[Horizontal vibration of the car body]
The equation of motion that describes the lateral vibration (movement in the left-right direction) of the vehicle body 11 is expressed by the following equation (15).

m _B is the mass of the carts 12a and 12b. y _b ... is the acceleration of the vehicle body 11 in the left-right direction. y _t2 · is the speed of the carriage 12b in the left-right direction. φ _t2 · is the angular velocity of the carriage 12b in the rolling direction. y _t2 is the displacement of the carriage 12b in the left-right direction. φ _t2 is the amount of rotation (angular displacement) of the carriage 12b in the rolling direction.

[Yawing of the car body]
The equation of motion that describes the yawing of the vehicle body 11 is expressed by the following equation (16).

_IBz is the moment of inertia of the vehicle body 11 in the yawing direction. ψ _b ... is the angular acceleration of the vehicle body 11 in the yawing direction. c ₀ is a damping constant in the anteroposterior direction of the yaw damper. ψ _y1 · is the angular velocity in the yawing direction of the yaw damper arranged on the bogie 12a. ψ _y2 · is the angular velocity in the yawing direction of the yaw damper arranged on the bogie 12b. ψ _t2 is the amount of rotation (angular displacement) of the bogie 12b in the yawing direction.

[Rolling of the car body]
The equation of motion that describes the rolling of the vehicle body 11 is expressed by the following equation (17).

I _Bx is the moment of inertia in the rolling direction of the vehicle body 11. φ _b ... is the angular acceleration of the vehicle body 11 in the rolling direction.

[Yawing of Yodampa]
The equations of motion describing the yawing of the yaw damper arranged on the bogie 12a and the yaw of the yaw damper arranged on the bogie 12b are expressed by the following equations (18) and (19), respectively.

ψ _y2 is the amount of rotation (angular displacement) of the yaw damper arranged on the bogie 12b in the yawing direction.

[Rolling of air spring (pillow spring)]
The equations of motion describing the rolling of the air spring (pillow spring) arranged on the bogie 12a and the air spring (pillow spring) arranged on the bogie 12b are expressed by the following equations (20) and (21), respectively. ..

_φa2 · is the angular velocity in the rolling direction of the air spring (pillow spring) arranged on the bogie 12b.

(Forward and backward force)
Next, the anteroposterior force will be described. The forward / backward force itself is the same as that described in Patent Document 1.
Of the left and right wheels on one wheel set, the components having the same phase of the vertical creep force on one wheel and the vertical creep force on the other wheel are components corresponding to the braking force and the driving force. Therefore, it is preferable to determine the anteroposterior force so as to correspond to the reverse phase component of the longitudinal creep force. The reverse phase component of the vertical creep force is a component in which the vertical creep force on one of the left and right wheels on one wheel set and the vertical creep force on the other wheel are in opposite phases to each other. That is, the reverse phase component of the vertical creep force is a component of the vertical creep force in the direction of twisting the axle. In this case, the front-rear direction force is a component in the front-rear direction that is opposite to each other among the components in the front-rear direction of the force generated in the two members attached to both sides in the left-right direction of one wheel set.

Hereinafter, a specific example of the anteroposterior force when the anteroposterior force is determined so as to correspond to the reverse phase component of the longitudinal creep force will be described.
When the axle box support device is a monolink type axle box support device, the axle box support device includes a link, and the axle box and the bogie frame are connected by a link. Rubber bushes are attached to both ends of this link. In this case, the anteroposterior force is a component in the anteroposterior direction of the load received by each of the two links attached to the left and right ends of one wheel set, which are in opposite phase to each other. Further, depending on the arrangement and configuration of the link, the link receives mainly the load in the front-rear direction among the loads in the front-rear direction, the left-right direction, and the up-down direction. Therefore, for example, one strain gauge may be attached to each link. By deriving the anteroposterior component of the load received by the link using the measured value of this strain gauge, the measured value of the anteroposterior force is obtained. Alternatively, instead of doing so, the displacement of the rubber bush attached to the link in the front-rear direction may be measured with a displacement meter. In this case, the product of the measured displacement and the spring constant of the rubber bush is used as the measured value of the longitudinal force. When the axle box support device is a monolink type axle box support device, the above-mentioned member for supporting the axle box is a link or a rubber bush.

The load measured by the strain gauge attached to the link may include not only a component in the front-rear direction but also a component in the left-right direction and a component in at least one of the components in the up-down direction. However, even in such a case, due to the structure of the axle box support device, the load of the component in the left-right direction and the load of the component in the vertical direction received by the link are sufficiently smaller than the load of the component in the front-rear direction. Therefore, it is possible to obtain a measured value of the anteroposterior force having the accuracy required for practical use only by attaching one strain gauge to each link. As described above, the measured value of the anteroposterior force may include components other than the components in the anteroposterior direction. Therefore, three or more strain gauges may be attached to each link so that the vertical and horizontal strains are cancelled. By doing so, the accuracy of the measured value of the forward / backward force can be improved.

When the axle box support device is an axle beam type axle box support device, the axle box support device includes an axle beam, and the axle box and the bogie frame are connected by the axle beam. The axle beam may be configured integrally with the axle box. A rubber bush is attached to the end of the shaft beam on the bogie frame side. In this case, the anteroposterior force is a component in the anteroposterior direction of the load received by each of the two shaft beams attached to the left and right ends of one wheel set, which are in opposite phase to each other. Further, due to the arrangement configuration of the shaft beam, the shaft beam is likely to receive the load in the left-right direction in addition to the load in the front-rear direction among the loads in the front-rear direction, the left-right direction, and the up-down direction. Therefore, for example, two or more strain gauges are attached to each shaft beam so that the strain in the left-right direction is canceled. By using the measured values of these strain gauges to derive the anteroposterior component of the load applied to the shaft beam, the measured value of the anteroposterior force is obtained. Alternatively, instead of doing so, the displacement of the rubber bush attached to the shaft beam in the front-rear direction may be measured with a displacement meter. In this case, the product of the measured displacement and the spring constant of the rubber bush is used as the measured value of the longitudinal force. When the axle box support device is an axle beam type axle box support device, the above-mentioned member for supporting the axle box is an axle beam or a rubber bush.

The load measured by the strain gauge attached to the shaft beam may include not only the components in the front-rear direction and the left-right direction but also the components in the vertical direction. However, even in such a case, due to the structure of the axle box support device, the load of the component in the vertical direction received by the shaft beam is sufficiently smaller than the load of the component in the front-rear direction and the load of the component in the left-right direction. .. Therefore, it is possible to obtain a measured value of the anteroposterior force having practically required accuracy without attaching a strain gauge so as to cancel the load of the vertical component received by the shaft beam. In this way, the measured anteroposterior force may contain components other than the anteroposterior component, and three or more strain gauges so that the vertical distortion is canceled in addition to the horizontal distortion. May be attached to each shaft beam. By doing so, the accuracy of the measured value of the forward / backward force can be improved.

When the axle box support device is a leaf spring type axle box support device, the axle box support device includes a leaf spring, and the axle box and the bogie frame are connected by the leaf spring. A rubber bush is attached to the end of this leaf spring. In this case, the front-rear direction force is a component of the front-rear direction components of the load received by each of the two leaf springs attached to the left-right end of one wheel set, which are in opposite phase to each other. Further, due to the arrangement configuration of the leaf spring, the leaf spring is likely to receive the load in the left-right direction and the load in the up-down direction in addition to the load in the front-rear direction among the loads in the front-rear direction, the left-right direction, and the up-down direction. Therefore, for example, three or more strain gauges are attached to each leaf spring so as to cancel the strain in the left-right direction and the strain in the vertical direction. By using the measured values of these strain gauges to derive the front-rear component of the load received by the leaf spring, the measured value of the front-rear force is obtained. Alternatively, instead of doing so, the displacement of the rubber bush attached to the leaf spring in the front-rear direction may be measured with a displacement meter. In this case, the product of the measured displacement and the spring constant of the rubber bush is used as the measured value of the longitudinal force. When the axle box support device is a leaf spring type axle box support device, the above-mentioned member for supporting the axle box is a leaf spring or a rubber bush.

As the displacement meter described above, a known laser displacement meter or an eddy current type displacement meter can be used.
Further, here, the longitudinal force has been described by taking as an example the case where the axle box support device is a monolink type, a shaft beam type, and a leaf spring type. However, the method of the axle box support device is not limited to the monolink type, the shaft beam type, and the leaf spring type. As with the monolink type, the shaft beam type, and the leaf spring type, the longitudinal force can be determined according to the method of the axle box support device.
Further, in the following, in order to simplify the explanation, a case where one measured value of the front-rear direction force can be obtained for one wheel set will be described as an example. That is, the railroad vehicle shown in FIG. 1 has four wheel sets 13a to 13d. Therefore, _four measured values of the anteroposterior force T1 to _T4 can be obtained.

(First Embodiment)
Next, the first embodiment of the present invention will be described.

<Inspection device 400>
FIG. 4 is a diagram showing an example of a functional configuration of the inspection device 400. FIG. 5 is a diagram showing an example of the hardware configuration of the inspection device 400. FIG. 6 is a flowchart showing an example of the first preprocessing in the inspection device 400. The first pre-processing is a process for setting the second pre-processing and the equations of state and observations used in this processing. FIG. 7 is a flowchart showing an example of the second preprocessing in the inspection device 400. The second pre-processing is a process of obtaining a correction amount for the estimated value of the deviation amount as described above after the first pre-processing is completed. FIG. 8 is a flowchart showing an example of this process in the inspection device 400. This processing is a processing for obtaining an estimated value of the final amount of deviation after the first preprocessing and the second preprocessing are completed. In the present embodiment, as shown in FIG. 1, a case where the inspection device 400 is mounted on a railroad vehicle is shown as an example. Further, in the following description, it is assumed that the railroad vehicle is the same railroad vehicle on which the inspection device 400 is mounted.

In FIG. 4, the inspection device 400 has, as its functions, a state equation storage unit 401, an observation equation storage unit 402, a data acquisition unit 403, a first frequency adjustment unit 404, a filter calculation unit 405, and a second frequency adjustment unit 406. It has a first orbital state calculation unit 407, an actual value acquisition unit 408, a correction amount calculation unit 409, a correction amount storage unit 410, a second orbital state calculation unit 411, an orbital state correction unit 412, and an output unit 413.

In FIG. 5, the inspection device 400 includes a CPU 501, a main storage device 502, an auxiliary storage device 503, a communication circuit 504, a signal processing circuit 505, an image processing circuit 506, an I / F circuit 507, a user interface 508, a display 509, and a bus. It has 510.

The CPU 501 controls the entire inspection device 400 in an integrated manner. The CPU 501 uses the main storage device 502 as a work area to execute a program stored in the auxiliary storage device 503. The main storage device 502 temporarily stores the data. The auxiliary storage device 503 stores various data in addition to the program executed by the CPU 501. The auxiliary storage device 503 stores the equation of state, the observation equation, and the correction amount (first correction amount, second correction amount) described later. The state equation storage unit 401, the observation equation storage unit 402, and the correction amount storage unit 410 are realized by using, for example, a CPU 501 and an auxiliary storage device 503.

The communication circuit 504 is a circuit for communicating with the outside of the inspection device 400. The communication circuit 504 receives, for example, information on the measured value of the front-rear direction force and the measured value of the acceleration in the left-right direction of the vehicle body 11, the carriages 12a and 12b, and the wheel sets 13a to 13d. The communication circuit 504 may perform wireless communication or wired communication with the outside of the inspection device 400. The communication circuit 504 is connected to an antenna provided in a railroad vehicle when performing wireless communication.

The signal processing circuit 505 performs various signal processing on the signal received by the communication circuit 504 and the signal input according to the control by the CPU 501. The data acquisition unit 403 and the actual value acquisition unit 408 are realized by using, for example, a CPU 501, a communication circuit 504, and a signal processing circuit 505. Further, the first frequency adjustment unit 404, the filter calculation unit 405, the second frequency adjustment unit 406, the first orbital state calculation unit 407, the correction amount calculation unit 409, the second orbital state calculation unit 411, and the orbital state. The correction unit 412 is realized by using, for example, a CPU 501 and a signal processing circuit 505.

The image processing circuit 506 performs various image processing on the signal input according to the control by the CPU 501. The signal subjected to this image processing is output to the display 509.
The user interface 508 is a portion where the operator gives an instruction to the inspection device 400. The user interface 508 includes, for example, buttons, switches, dials, and the like. Further, the user interface 508 may have a graphical user interface using the display 509.

The display 509 displays an image based on the signal output from the image processing circuit 506. The I / F circuit 507 exchanges data with a device connected to the I / F circuit 507. FIG. 5 shows a user interface 508 and a display 509 as devices connected to the I / F circuit 507. However, the device connected to the I / F circuit 507 is not limited to these. For example, a portable storage medium may be connected to the I / F circuit 507. Further, at least a part of the user interface 508 and the display 509 may be outside the inspection device 400.
The output unit 413 is realized by using, for example, at least one of a communication circuit 504 and a signal processing circuit 505, an image processing circuit 506, an I / F circuit 507, and a display 509.

The CPU 501, the main storage device 502, the auxiliary storage device 503, the signal processing circuit 505, the image processing circuit 506, and the I / F circuit 507 are connected to the bus 510. Communication between these components takes place via bus 510. Further, the hardware of the inspection device 400 is not limited to that shown in FIG. 5 as long as the functions of the inspection device 400 described later can be realized.

[Equation of state storage unit 401, S601]
The equation of state storage unit 401 stores the equation of state. In this embodiment, the case where the equation of state described in Patent Document 1 is used will be described as an example. As described above, in the present embodiment, the equation of motion that describes the yawing of the wheel sets 13a to 13d of the equations (5) to (8) is not included in the equation of state, and the equation of state is constructed as follows.
First, the equation of motion that describes the lateral vibration (movement in the left-right direction) of the trolleys 12a and 12b of the equations (9) and (10) and the rolling of the trolleys 12a and 12b of the equations (13) and (14) are described. The equation of motion, the equation of motion that describes the lateral vibration (movement in the left-right direction) of the vehicle body 11 of equation (15), the equation of motion that describes the yawing of the vehicle body 11 of equation (16), and the equation of motion of equation (17). The equation of motion describing the rolling of 11, the equation of motion describing the yawing of the yaw dampers arranged on the bogies 12a of the formulas (18) and (19), and the equations of motion (20), ( As for the equation of motion describing the rolling of the air spring (pillow spring) arranged on the trolley 12a and the air spring (pillow spring) arranged on the trolley 12b of the formula 21), the equation of motion is constructed by using these as they are.

On the other hand, the equation of motion that describes the lateral vibration (movement in the left-right direction) of the wheel shafts 13a to 13d of the formulas (1) to (4) and the yawing of the carriages 12a and 12b of the formulas (11) and (12) are described. The equation of motion to be performed includes the amount of rotation (angular displacement) ψ _w1 to ψ _w4 and the angular velocities ψ _w1 · to ψ _w4 · in the yawing direction of the wheel axes 13a to 13d. The equation of state is constructed by using the equations (1) to (4), (11), and (12) in which these variables are eliminated.

_First , the longitudinal forces T1 to T4 _on the wheel sets 13a to 13d are represented by the following equations (22) to (25). As described above, the front-rear direction forces T ₁ to T ₄ correspond to the difference between the angular displacement ψ _w1 to ψ _w4 in the yawing direction of the wheel set and the angular displacement ψ _t1 to ψ _t 2 in the yawing direction of the carriage on which the wheel set is provided. It is decided.

_The conversion variables e1 to _e4 are defined as in the following equations (26) to (29). As described above, the conversion variables e ₁ to e ₄ are defined by the difference between the angular displacements ψ _t1 to ψ _t2 in the yawing direction of the carriage and the angular displacements ψ _w1 to ψ _w4 in the yawing direction of the wheel set. The conversion variables e ₁ to e ₄ are variables for mutually converting the angular displacements ψ _t1 to ψ _t2 in the yawing direction of the trolley and the angular displacements ψ _w1 to ψ _w4 in the yawing direction of the wheel set.

By transforming the equations (26) to (29), the following equations (30) to (33) can be obtained.

Substituting the equations (30) to (33) into the equations of motion describing the lateral vibrations (movement in the left-right direction) of the wheel sets 13a to 13d of the equations (1) to (4), the following equations (34) to Equation (37) is obtained.

In this way, the equation of motion that describes the lateral vibration (movement in the left-right direction) of the wheel shafts 13a to 13d of the equations ( ₁ ) to ( ₄ ) is expressed by using the conversion variables e1 to e4. The amount of rotation (angular displacement) ψ _w1 to ψ _w4 in the yawing direction of the wheel axes 13a to 13d included in the equation of motion can be eliminated.

By substituting the equations (22) to (25) into the equations of motion describing the yawing of the carriages 12a and 12b of the equations (11) and (12), the following equations (38) and (39) are obtained. ..

In this way, the equation of motion that describes the yawing of the trolleys 12a and 12b of equations (11) and ( ₁₂ ) is included in the equation of motion by expressing it using the longitudinal forces T1 to _T4 . The angular displacements ψ _w1 to ψ _w4 and the angular velocities ψ _w1 · to ψ _w4 · in the yawing direction of the wheel shafts 13a to 13d can be eliminated.

Further, by substituting the equations (26) to (29) into the equations (22) to (25), the following equations (40) to (43) can be obtained.

As described above, in the present embodiment, the equations of motion for describing the lateral vibration (movement in the left-right direction) of the wheel shafts 13a to 13d are expressed as the equations (34) to (37), and the equations (38) and (38) are expressed. 39) The equations of motion that describe the yawing of the carriages 12a and 12b are expressed as in Eq. 39), and the equations of motion are constructed using these equations of motion. Further, equations ( ₄₀ ) to (43) are ordinary differential equations, and the actual values of the conversion variables e1 to _e4 , which are the solutions thereof, are the values of the longitudinal forces T1 to T4 _on the wheel _sets 13a to 13d. Can be obtained by using. Here, the values of the front-rear direction forces T ₁ to T ₄ are caused by the railroad vehicle traveling on the curved portion of the track from the time-series data of the measured values of the front-rear direction forces by the first frequency adjusting unit 404 described later. The signal strength of the low-frequency component generated is reduced.

The actual values of the conversion variables e1 to _e4 obtained in this way are given to the equations ₍ 34) to (37). Further, the values of the longitudinal forces T1 to T4 _on the wheel _sets 13a to 13d are given to the equations (38) and (39). Here, the values of the front-rear direction forces T ₁ to T ₄ are caused by the railroad vehicle traveling on the curved portion of the track from the time-series data of the measured values of the front-rear direction forces by the first frequency adjusting unit 404 described later. The signal strength of the low-frequency component generated is reduced.

In this embodiment, the variables shown in the following equations (44) are set as state variables, and the equations (9), (10), (13) to (21), and (34) to (39) are exercised. Construct the equation of state using the equations.

The state equation storage unit 401, for example, inputs and stores the state equation configured as described above based on the operation of the user interface 508 by the operator.

[Observation equation storage unit 402, S602]
The observation equation storage unit 402 stores the observation equation. In the present embodiment, the acceleration in the left-right direction of the vehicle body 11, the acceleration in the left-right direction of the carriages 12a and 12b, and the acceleration in the left-right direction of the wheel shafts 13a to 13d are used as observation variables. This observed variable is an observed variable for filtering by the Kalman filter described later. In the present embodiment, the observation equations are constructed by using the equations of motion describing the lateral vibrations of the equations (34) to (37), (9), (10), and (15). The observation equation storage unit 402 inputs and stores, for example, the observation equation configured in this way based on the operation of the user interface 508 by the operator.

As described above, after the equation of state and the observation equation are stored in the inspection device 400, the data acquisition unit 403, the first frequency adjustment unit 404, the filter calculation unit 405, the second frequency adjustment unit 406, and the first The orbital state calculation unit 407, the actual value acquisition unit 408, the correction amount calculation unit 409, and the correction amount storage unit 410 are activated. That is, after the first preprocessing according to the flowchart of FIG. 6 is completed, the second preprocessing according to the flowchart of FIG. 7 starts.

[Data acquisition unit 403, S701]
The data acquisition unit 403 acquires measurement data at a predetermined sampling cycle.
In the present embodiment, as measurement data, the data acquisition unit 403 includes time-series data of measured values of acceleration in the left-right direction of the vehicle body 11, time-series data of measured values of acceleration of the carriages 12a and 12b in the left-right direction, and wheel shaft 13a. Acquire time-series data of measured values of acceleration in the left-right direction of ~ 13d. Each acceleration is measured, for example, by using a strain gauge attached to the vehicle body 11, the carriages 12a, 12b, and the wheel sets 13a to 13d, and an arithmetic unit that calculates the acceleration using the measured value of the strain gauge. To. Since the measurement of acceleration can be realized by a known technique, detailed description thereof will be omitted.

Further, the data acquisition unit 403 acquires time-series data of the measured values of the front-rear direction force as the measurement data. The method of measuring the forward / backward force is as described above.
The data acquisition unit 403 can acquire measurement data, for example, by communicating with the above-mentioned arithmetic unit. In step S701, the data acquisition unit 403 shall acquire the measurement data in the entire traveling section of the railway vehicle.

[First frequency adjusting unit 404, S702]
The first frequency adjusting unit 404 reduces the signal strength of the low-frequency component included in the time-series data of the measured values of the anteroposterior force (second physical quantity) among the measurement data acquired by the data acquisition unit 403 (the first frequency adjusting unit 404). (Preferably removed). This low-frequency component signal is not measured when the railroad vehicle is traveling on a straight track, but is a signal measured when the railroad vehicle is traveling on a curved track. That is, the signal measured when the railroad vehicle is traveling on a curved track is a signal obtained by superimposing the signal of this low frequency component on the signal measured when the railroad vehicle is traveling on a straight track. You can see it.

The present inventors have devised a model modified from an autoregressive model (AR (Auto-regressive) model). Then, the present inventors have come up with the idea of using this model to reduce the signal strength of the low-frequency component included in the time-series data of the measured value of the anteroposterior force. In the following description, the model devised by the present inventors will be referred to as a modified autoregressive model. On the other hand, a known autoregressive model is simply referred to as an autoregressive model. An example of the modified autoregressive model will be described below.

Let y _k be the value of the time series data y of the physical quantity at time k (1 ≦ k ≦ M). M is a number indicating to which time the time-series data y of the physical quantity includes the data, and is set in advance. In the following description, time-series data of physical quantities will be abbreviated as data y as necessary. An autoregressive model that approximates the value y _k of the data y is, for example, the following equation (45). As shown in the equation (45), the autoregressive model is a time k-in which the predicted value y ^ _k of the physical quantity at the time k (m + 1 ≦ k ≦ M) in the data y is before the time k in the data y. It is an expression expressed by using the actual value y _kl of the physical quantity of l (1 ≦ l ≦ m). In addition, y ^ _k is expressed by adding ^ on top of y _k in the equation (45).

Α in equation (45) is a coefficient of the autoregressive model. m is the number of data y values used to approximate the data y value y _k at time k in the autoregressive model, and is a continuous time k-1 to km prior to that time k. It is the number of values y _{k -1} to y km of the data y in. m is an integer less than M. For example, 1500 can be used as m.

Subsequently, using the least squares method, a conditional expression is obtained for the predicted value y ^ _k of the physical quantity at time k by the autoregressive model to approximate the value y _k . As a condition for the predicted value y ^ _k of the physical quantity at time k by the autoregressive model to be close to the value y _k , for example, the square error between the predicted value y ^ _k and the value y _k of the physical quantity at time k by the autoregressive model. It is possible to adopt the condition that minimizes. That is, the least squares method is used to approximate the predicted value y ^ _k of the physical quantity at time k by the autoregressive model to the value y _k . The following equation (46) is a conditional equation for minimizing the square error between the predicted value y ^ _k of the physical quantity at the time k by the autoregressive model and the value y _k .

From equation (46), the following equation (47) holds.

Further, by modifying the equation (47) (matrix notation), the following equation (48) can be obtained.

R _jl in the equation (48) is called an autocorrelation of the data y, and is a value defined by the following equation (49). | Jl | at this time is called a time difference.

Based on the equation (48), consider the following equation (50). Equation (50) is derived from the condition that minimizes the error between the predicted value y ^ _k of the physical quantity at time k by the autoregressive model and the value y _k of the physical quantity at time k corresponding to the predicted value y ^ _k . Is the equation to be done. Equation (50) is called the Yule-Walker equation. Further, the equation (50) is a linear equation in which the vector consisting of the coefficients of the autoregressive model is used as the variable vector. The constant vector on the left side in the equation (50) is a vector whose component is the autocorrelation of the data y having a time difference of 1 to m. In the following description, the constant vector on the left side in Eq. (50) will be referred to as an autocorrelation vector, if necessary. Further, the coefficient matrix on the right side in the equation (50) is a matrix whose component is the autocorrelation of the data y having a time difference of 0 to m-1. In the following description, the coefficient matrix on the right side in Eq. (50) will be referred to as an autocorrelation matrix, if necessary.

Further, the autocorrelation matrix (m × m matrix composed of R _jl ) on the right side in the equation (50) is referred to as an autocorrelation matrix R as in the following equation (51).

Generally, when obtaining the coefficient of the autoregressive model, a method of solving Eq. (50) with respect to the coefficient α is used. In equation (50), the coefficient α is derived so that the predicted value y ^ _k of the physical quantity at time k derived by the autoregressive model is as close as possible to the value y _k of the physical quantity at that time k. Therefore, the frequency characteristics of the autoregressive model include a large number of frequency components included in the value y _k of the data y at each time.

Therefore, the present inventors focused on the autocorrelation matrix R multiplied by the coefficient α of the autoregressive model, and studied diligently. As a result, the present inventors have found that the influence of the high frequency component contained in the data y can be reduced by using a part of the eigenvalues of the autocorrelation matrix R. That is, the present inventors have found that the autocorrelation matrix R can be rewritten so that the low frequency component is emphasized.

A specific example of this will be described below.
The autocorrelation matrix R is decomposed into singular values. The elements of the autocorrelation matrix R are symmetric. Therefore, when the autocorrelation matrix R is decomposed into singular values, it becomes the product of the orthogonal matrix U, the diagonal matrix Σ, and the transposed matrix of the orthogonal matrix U as shown in the following equation (52).

The diagonal matrix Σ of the equation (52) is a matrix in which the diagonal component is an eigenvalue of the autocorrelation matrix R, as shown in the following equation (53). Let the diagonal components of the diagonal matrix Σ be σ ₁₁ , σ ₂₂ , ..., Σ _mm . Further, the orthogonal matrix U is a matrix in which each column component vector is an eigenvector of the autocorrelation matrix R. Let the column component vector of the orthogonal matrix U be u ₁ , u ₂ , ..., _Um . There is a correspondence that the eigenvalue of the autocorrelation matrix R with respect to the eigenvector u _j is σ _jj . The eigenvalue of the autocorrelation matrix R is a variable that reflects the intensity of the component of each frequency included in the time waveform of the predicted value y ^ _k of the physical quantity at time k by the autoregressive model.

The values of σ ₁₁ , σ ₂₂ , ..., σ _mm , which are the diagonal components of the diagonal matrix Σ obtained from the result of the singular value decomposition of the autocorrelation matrix R, are in descending order to simplify the notation of the formula. do. Of the eigenvalues of the autocorrelation matrix R shown in equation (53), the matrix R'is defined as in equation (54) below using s eigenvalues from the largest one. s is a number of 1 or more and less than m. In this embodiment, s is predetermined. The matrix R'is a matrix that approximates the autocorrelation matrix R by using s eigenvalues among the eigenvalues of the autocorrelation matrix R.

The matrix Us in the equation (54) is an m × s matrix composed of _s column component vectors (eigenvectors corresponding to the eigenvalues used) from the left of the orthogonal matrix U in the equation (52). That is, the matrix Us is a submatrix formed by cutting out the elements of m × _s on the left from the orthogonal matrix U. Further, _Us ^T in _Eq . (54) is a transposed matrix of Us. Us ^T is an _s × m matrix composed of s row component vectors from the top of the matrix ^UT of Eq. (52). The matrix Σ _s in the equation (54) is an s × s matrix composed of s columns from the left and s rows from the top of the diagonal matrix Σ in the equation (52). That is, the matrix Σ _s is a submatrix formed by cutting out the elements of s × s on the upper left from the diagonal matrix Σ.
If the matrix Σ _s and the matrix _Us are expressed by matrix elements, the following equation (55) is obtained.

By using the matrix R'instead of the autocorrelation matrix R, the relational expression of the equation (50) is rewritten as the following equation (56).

By modifying the equation (56), the following equation (57) can be obtained as an equation for obtaining the coefficient α. The "modified autoregressive model" is a model for calculating the predicted value y ^ _k of the physical quantity at time k by the equation (45) using the coefficient α obtained by the equation (57).

Here, the case where the values of σ ₁₁ , σ ₂₂ , ..., Σ _mm , which are diagonal components of the diagonal matrix Σ, are in descending order has been described as an example. However, in the process of calculating the coefficient α, the diagonal components of the diagonal matrix Σ do not have to be in descending order. In that case, the matrix Us is not a submatrix composed by cutting out the elements of m × _s on the left from the orthogonal matrix U, but is configured by cutting out a column component vector (eigenvector) corresponding to the eigenvalues used. It becomes a submatrix. In addition, the matrix Σ _s is not a submatrix constructed by cutting out the elements of s × s on the upper left from the diagonal matrix Σ, but the eigenvalues used to determine the coefficients of the modified self-return model are used as diagonal components. It becomes a submatrix cut out in.

Equation (57) is an equation used to determine the coefficients of the modified autoregressive model. The matrix Us in Eq. (57) is a _submatrix of the orthogonal matrix U obtained by the singular value decomposition of the autocorrelation matrix R, and is a column of eigenvectors corresponding to the eigenvalues used to determine the coefficients of the modified self-return model. It is a matrix (third matrix) as a component vector. Further, the matrix Σ _s of Eq. (57) is a submatrix of the diagonal matrix obtained by the singular value decomposition of the autocorrelation matrix R, and the eigenvalues used for determining the coefficients of the modified self-return model are diagonal components. It is a matrix (second matrix). The matrix _Us Σ _{s Us} ^T in the equation (57) is a matrix (first matrix) derived from the matrix Σ _s and the matrix _Us .

By calculating the right side of equation (57), the coefficient α of the modified autoregressive model can be obtained. The example of the derivation method of the coefficient α of the modified autoregressive model has been described above. Here, the method for deriving the coefficients of the autoregressive model, which is the basis of the modified autoregressive model, is a method using the least squares method for the predicted value y ^ _k of the physical quantity at time k so that it can be intuitively understood. .. However, in general, a method of defining an autoregressive model using the concept of a stochastic process and deriving its coefficient is known. In that case, the autocorrelation is expressed by the autocorrelation of the stochastic process (population). The autocorrelation of this stochastic process is expressed as a function of time difference. Therefore, the autocorrelation of the data y in the present embodiment may be replaced with a value calculated by another calculation formula as long as it approximates the autocorrelation of the stochastic process. For example, R ₂₂ to R _mm are autocorrelation with a time difference of 0 (zero), but these may be replaced with R ₁₁ .

The number s of the eigenvalues extracted from the autocorrelation matrix R shown in the equation (53) can be determined, for example, from the distribution of the eigenvalues of the autocorrelation matrix R.
Here, the physical quantity in the above-mentioned description of the modified autoregressive model is the anteroposterior force. The value of the front-rear force varies depending on the condition of the railroad vehicle.
Therefore, first, the railroad vehicle is run on the track 16 to obtain data y about the measured value of the front-rear direction force. For each of the obtained data y, the autocorrelation matrix R is obtained using the equations (49) and (51). The eigenvalues of the autocorrelation matrix R are obtained by performing the singular value decomposition expressed by the equation (52) for the autocorrelation matrix R. FIG. 9 is a diagram showing an example of the distribution of the eigenvalues of the autocorrelation matrix R. In FIG. 9, the eigenvalues σ ₁₁ to σ _mm obtained by singular value decomposition of the autocorrelation matrix R for _each of the data y of the measured values of the anteroposterior force T1 on the wheel set 13a are rearranged in ascending order and plotted. ing. The horizontal axis of FIG. 9 is the index of the eigenvalues, and the vertical axis is the value of the eigenvalues.

In the example shown in FIG. 9, there is one eigenvalue with a significantly higher value than the others. In addition, there are two eigenvalues that are not as good as the eigenvalues with remarkably high values, but have relatively large values compared to the others and cannot be regarded as 0 (zero). From this, for example, 2 or 3 can be adopted as the number s of the eigenvalues extracted from the autocorrelation matrix R shown in the equation (53). No matter which one is adopted, there is no significant difference in the results.

The first frequency adjusting unit 404 performs the following processing using the value y _k of the data y of the measured value of the forward / backward force acquired by the data acquisition unit 403 at the time k.
First, the first frequency adjusting unit 404 uses the equations (49) and (51) based on the data y of the measured value of the forward / backward force and the preset numbers M and m. Generate the autocorrelation matrix R.

Next, the first frequency adjusting unit 404 derives the orthogonal matrix U and the diagonal matrix Σ of the equation (52) by singular value decomposition of the autocorrelation matrix R, and the autocorrelation matrix R is derived from the diagonal matrix Σ. The eigenvalues of σ ₁₁ to σ _mm are derived.
Next, the first frequency adjusting unit 404 sets s eigenvalues σ ₁₁ to σ _ss from the largest of the plurality of eigenvalues σ ₁₁ to σ _mm of the autocorrelation matrix R, and the coefficient α of the modified autoregressive model. Is selected as the eigenvalue of the autocorrelation matrix R used to obtain.
Next, the first frequency adjusting unit 404 is based on the data y of the measured value of the anteroposterior force, the eigenvalues σ ₁₁ to σ _ss , and the orthogonal matrix U obtained by the singular value decomposition of the autocorrelation matrix R. Then, the coefficient α of the modified autoregressive model is determined using the equation (57).

Then, the first frequency adjusting unit 404 is based on the coefficient α of the modified autoregressive model and the data y of the measured value of the anteroposterior force, and the data y of the measured value of the anteroposterior force according to the equation (45). The predicted value y ^ _k at the time k of is derived. The time-series data of the predicted value y ^ _k of the front-back direction force is the time-series data obtained by extracting the low frequency component included in the data y of the measured value of the front-back direction force.

FIG. 10 is a diagram showing an example of time-series data (measured value) of the measured value of the front-back direction force and time-series data (calculated value) of the predicted value of the front-back direction force. In this embodiment, _four measured values of the front _- rear direction forces T1 to T4 can be obtained. That is, four data y are obtained for the anteroposterior force. FIG. 10 shows measured and calculated values in each of these four data y. The horizontal axis of FIG. 10 is the elapsed time (seconds) from the reference time when the reference time is 0 ₍ zero), and represents the measurement time / calculation time of the forward _/ backward force T1 to T4. The vertical axis is the front-back direction force T ₁ to T ₄ (Nm).

In FIG. ₁₀ , the calculated value of the anteroposterior force T1 on the wheel set 13a is biased (that is, shows a larger value than other times) in about 15 seconds to 35 seconds. This period corresponds to the period during which the wheel set 13a passes through the curved track. The calculated values of the anteroposterior force T ₂ on the wheel set 13b, the calculated value of the anteroposterior force T ₃ on the wheel set 13c, and the calculated value of the anteroposterior force T ₄ on the wheel set 13d are also the calculated values of the anteroposterior force T ₁ on the wheel set 13a. Similarly, the period during which the wheel sets 13b, 13c, and 13d pass through the curved orbit is biased.

Therefore, in FIG. 10, if the calculated value is removed from the measured values of the front _- rear direction forces T1 to T4 _on the wheel _sets 13a to 13d, the wheel sets 13a to 13d among the signals of the front _- back direction forces T1 to T4 follow the curved trajectory. Low frequency components due to passing can be removed. That is, in FIG. ₁₀ , if the calculated value is removed from the measured values of the front _- rear direction forces T1 to T4 _on the wheel sets 13a to 13d, the front _- back direction forces T1 to T4 when the wheel sets 13a to 13d pass through the curved orbit are used. , It is possible to obtain the same anteroposterior force as when the wheel sets 13a to 13d pass through a straight orbit.

Therefore, the first frequency adjusting unit 404 subtracts the time-series data of the predicted value y ^ _k of the front-back direction force from the time-series data (data y) of the measured value y _k of the front-back direction force. In the following description, the time-series data obtained by subtracting the time-series data of the predicted value y ^ _k of the front-back direction force from the time-series data (data y) of the measured value y _k of the front-back direction force is obtained in the front-back direction as necessary. It is called time series data of high frequency component of force. Further, the value at each sampling time of the time series data of the high frequency component of the anteroposterior force is referred to as the value of the high frequency component of the anteroposterior force, if necessary.

FIG. 11 is a diagram showing an example of time-series data of high-frequency components of anteroposterior force. The vertical axis of FIG. 11 shows the time-series data of the high-frequency components of the anteroposterior force T ₁ , T ₂ , T ₃ , and T ₄ . That is, the high-frequency components of the anteroposterior force T ₁ , T ₂ , T ₃ , and T ₄ shown on the vertical axis of FIG. 11 are the anteroposterior force T ₁ on the wheel shafts 13a, 13b, 13c, and 13d shown in FIG. 10, respectively. , T ₂ , T ₃ , and T ₄ obtained by subtracting the calculated value from the measured value. Further, the horizontal axis of FIG. 11 is the elapsed time (seconds) from the reference time when the reference time is set to _{0 (} zero), as in the case of the horizontal axis of FIG. Represents the measurement time and calculation time of.
As described above, the _first frequency adjusting unit 404 derives the time-series data of the high _- frequency components of the longitudinal forces T1 to T4.

[Filter calculation unit 405, S703]
The filter calculation unit 405 uses the Kalman filter as an observation equation stored by the observation equation storage unit 402 as an observation equation and a state equation stored by the state equation storage unit 401 as the state equation of the state variable shown in equation (44). Determine an estimate. At this time, the filter calculation unit 405 includes the measurement data excluding the front _- rear direction forces T1 to _T4 among the measurement data acquired by the data acquisition unit 403, and the front-back direction force generated by the first frequency adjustment unit 404. Time-series data of high-frequency components of T ₁ to T ₄ are used. As described above, in the present embodiment, the measurement data includes the measured value of the acceleration in the left-right direction of the vehicle body 11, the measured value of the acceleration in the left-right direction of the carriages 12a and 12b, and the measurement of the acceleration in the left-right direction of the wheel shafts 13a to 13d. Contains the value. For the anteroposterior force T1 to T4 _on the wheel shafts 13a to 13d, the anteroposterior force T generated by the _first frequency adjusting unit 404 without using the measurement data (measured value) acquired by the data acquisition unit 403. Time-series data of high _- frequency components ₁ to T4 are used.

The Kalman filter is one of the methods for data assimilation. That is, the Kalman filter is an example of a method for determining the estimated value of an unobserved variable (state variable) so that the difference between the measured value of the observable variable (observed variable) and the estimated value becomes small (minimum). .. The filter calculation unit 405 obtains the Kalman gain in which the difference between the measured value of the observed variable and the estimated value becomes small (minimum), and obtains the estimated value of the unobserved variable (state variable) at that time. In the Kalman filter, the observation equation of the following equation (58) and the equation of state of the following equation (59) are used.
Y = HX + V ... (58)
X ・ ＝ ΦX ＋ W ・ ・ ・ (59)

In equation (58), Y is a vector that stores the measured values of the observed variables. H is an observation model. X is a vector that stores the state variables. V is observation noise. In equation (59), X · indicates the time derivative of X. Φ is a linear model. W is system noise. Since the Kalman filter itself can be realized by a known technique, detailed description thereof will be omitted.
The filter calculation unit 405 generates time-series data of the estimated value of the state variable shown in the equation (44) by determining the estimated value of the state variable shown in the equation (44) in a predetermined sampling cycle.

[Second frequency adjustment unit 406, S704]
If the signal strength of the low frequency component included in the time-series data of the measured value of the anteroposterior force is not sufficiently removed by the first frequency adjusting unit 404, the estimated value of the state variable generated by the filter calculation unit 405. In the time series data of, there is a possibility that a signal of a low frequency component due to the railroad vehicle traveling on a curved track remains. Therefore, the second frequency adjusting unit 406 reduces (preferably removes) the signal strength of the low frequency component included in the time series data of the estimated value of the state variable (second physical quantity) generated by the filter calculation unit 405. do. From the autocorrelation matrix R shown in Eq. (53), the signal strength of the low frequency component included in the time series data of the measured value of the anteroposterior force is sufficiently removed by the first frequency adjusting unit 404. If the number s of the unique values to be extracted can be determined, the processing of the second frequency adjusting unit 406 becomes unnecessary.

In the present embodiment, the second frequency adjusting unit 406, like the first frequency adjusting unit 404, uses the modified autoregressive model to signal the low frequency component included in the time series data of the estimated value of the state variable. Reduce strength.

The second frequency adjusting unit 406 performs the following processing for each state variable in a predetermined sampling cycle.
Here, the physical quantity in the description of the modified autoregressive model described above is a state variable. That is, the data y of the state variable becomes the time series data of the estimated value of the state variable generated by the filter calculation unit 405. The estimated values of the state variables all vary depending on the state of the railroad vehicle.
First, the second frequency adjusting unit 406 self-uses the equations (49) and (51) based on the data y of the estimated value of the state variable and the preset numbers M and m. Generate the correlation matrix R.

Next, the second frequency adjusting unit 406 derives the orthogonal matrix U and the diagonal matrix Σ of the equation (52) by singular value decomposition of the autocorrelation matrix R, and the autocorrelation matrix R is derived from the diagonal matrix Σ. The eigenvalues of σ ₁₁ to σ _mm are derived.
Next, the second frequency adjusting unit 406 sets s eigenvalues σ ₁₁ to σ _ss from the largest of the plurality of eigenvalues σ ₁₁ to σ _mm of the autocorrelation matrix R, and the coefficient α of the modified autoregressive model. Is selected as the eigenvalue of the autocorrelation matrix R used to obtain. s is predetermined for each state variable. For example, a railroad vehicle is run on the track 16 to obtain data y of estimated values of each state variable as described above. Then, the distribution of the eigenvalues of the autocorrelation matrix R is individually created for each state variable. From the distribution of the eigenvalues of the autocorrelation matrix R, the number s of the eigenvalues extracted from the autocorrelation matrix R shown in Eq. (53) is determined for each of the state variables.

Next, the second frequency adjusting unit 406 is based on the data y of the estimated value of the state variable, the eigenvalues σ ₁₁ to σ _ss , and the orthogonal matrix U obtained by the singular value decomposition of the autocorrelation matrix R. , (57) is used to determine the coefficient α of the modified autoregressive model.

Then, the second frequency adjusting unit 406 is based on the coefficient α of the modified autoregressive model and the data y of the estimated value of the state variable, and the time of the data y of the estimated value of the state variable according to the equation (45). The predicted value y ^ _k at k is derived. The time-series data of the predicted value y ^ _k of the state variable is the time-series data obtained by extracting the low frequency component included in the data y of the estimated value of the state variable.

Then, the second frequency adjusting unit 406 subtracts the time series data of the predicted value y ^ _k of the state variable from the data y of the estimated value of the state variable. In the following description, the time-series data obtained by subtracting the time-series data of the predicted value y ^ _k of the state variable from the data y of the estimated value of the state variable is referred to as the time-series data of the high-frequency component of the state variable, if necessary. ..

[First orbital state calculation unit 407, S705]
By substituting the equations (22) to (25) into the equations of motion describing the yawing of the wheel sets 13a to 13d of the equations (5) to (8), the following equations (60) to (63) can be obtained. ..

In the present embodiment, as shown in the equations (60) to (63), the relationship between the longitudinal forces T1 to _{T4 and the amount of deviation y R1 to} y _R4 at the positions of the wheel _sets 13a to 13d is shown. The relational expression is determined.
The first orbital state calculation unit 407 calculates an estimated value of the amount of rotation (angular displacement) ψ _w1 to ψ _w4 of the wheel sets 13a to 13d in the yawing direction from the equations (30) to (33). Then, the first orbital state calculation unit 407 determines the estimated values of the rotation amounts (angular displacements) ψ _w1 to ψ _w4 of the wheel sets 13a to 13d in the yawing direction and the state variables generated by the second frequency adjustment unit 406. By giving the value of the high frequency component and the value of the high frequency component of the longitudinal forces T1 to _T4 generated by the _first frequency adjusting unit 404 to the equations (60) to (63), the wheel sets 13a to The amount of deviation y _R1 to y _R4 at the position of 13d is calculated. The state variables used here are the lateral displacements of the trolleys 12a to 12b y _t1 to y _t2 , the lateral speeds of the trolleys 12a to 12b y _t1 · to y _t2 ·, and the lateral displacements of the wheel shafts 13a ~ 13d. The speeds y _w1 to y _w4 and the speeds y _w1 and y _w4 in the left-right direction of the wheel shafts 13a to 13d. The first orbital state calculation unit 407 obtains time-series data of the deviation amount y _R1 to y _R4 by performing the calculation of the deviation amount y _R1 to y _R4 as described above in a predetermined sampling cycle.

Then, the first orbital state calculation unit 407 calculates the deviation amount y _R from the deviation amount y _R1 to y _R4 . For example, the first orbital state calculation unit 407 adjusts the phase of the time-series data of the deviation amount y _R2 to y _R4 to the phase of the time-series data of the deviation amount y _R1 . That is, the first track state calculation unit 407 determines the position with respect to the time when the wheel set 13a passes a certain position from the distance between the wheel set 13a and the wheel sets 13b to 13d in the front-rear direction and the speed of the railroad vehicle. The delay time of the time when 13b to 13d pass is calculated. The first orbital state calculation unit 407 shifts the phase by this delay time with respect to the time-series data of the amount of deviation y _R2 to y _R4 .

The first orbital state calculation unit 407 calculates the arithmetic mean value of the sum of the values of the phase-matched deviation quantities y _R1 to y _R4 at the same sampling time as the deviation amount y _R at the sampling time. The first orbital state calculation unit 407 obtains time-series data of the amount of deviation y _R by performing such a calculation at each sampling time. Since the phase of the deviation amount y _R2 to y _R4 is matched with the phase of the deviation amount y _R1 , the disturbance factors commonly existing in the time series data of the deviation amount y _R1 to y _R4 can be offset.

The first orbital state calculation unit 407 takes a moving average for each of the phase-matched deviation amounts y _R1 to y _R4 (that is, passes through a low-pass filter), and the deviation amount y as the moving average is taken. From _R1 to y _R4 , the amount of deviation y _R may be calculated.
Further, the first orbital state calculation unit 407 deviates through the arithmetic mean value of two values excluding the maximum value and the minimum value among the values at the same sampling time of the phase deviation amount y _R1 to y _R4 . It may be calculated as a quantity y _R.

The inspection device 400 uses the measurement data at each sampling time acquired by the data acquisition unit 403 while the railway vehicle is traveling in the entire traveling section of the railway vehicle, and uses the measurement data of the first frequency adjustment unit 404 and the filter. The processing of the calculation unit 405, the second frequency adjustment unit 406, and the first orbital state calculation unit 407 is executed.

In this way, the first track state calculation unit 407 can obtain the deviation amount _yR at each sampling time while the railway vehicle is traveling in the entire traveling section. The first track state calculation unit 407 calculates the traveling position of the railway vehicle at each sampling time based on, for example, the traveling speed of the railway vehicle and the elapsed time from the start of traveling of the railway vehicle. In the present embodiment, a case where the traveling position of the railway vehicle is set to the position of the wheel set 13a will be described as an example. The first track state calculation unit 407 calculates the amount of deviation y _R at each traveling position of the railway vehicle based on the amount of deviation y _R at each sampling time and the traveling position of the railway vehicle at each sampling time. do. In the following description, the value calculated in this way is referred to as an estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle, or an estimated value of the amount of deviation, if necessary.

The first track state calculation unit 407 does not necessarily have to calculate the traveling position of the railway vehicle at each sampling time as described above. For example, the first track state calculation unit 407 may obtain the traveling position of the railway vehicle at each sampling time by using GPS (Global Positioning System).

[Actual value acquisition unit 408, S706]
The actual value acquisition unit 408 acquires the measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle. It is assumed that the measured value of the amount of deviation at each position of the entire traveling section of the railroad vehicle is measured before the second preprocessing is started. The timing for acquiring the measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle is not limited to between step S705 and step S707. The timing for acquiring the measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle may be any timing as long as it is a timing before step S707. For example, the actual value acquisition unit 408 may acquire an actually measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle before the flowchart of FIG. 7 is started. In the following description, the measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle is referred to as the measured value or the measured value of the amount of deviation, if necessary.

The measured value of the amount of deviation is a value obtained by directly measuring the amount of deviation. The measured value of the amount of deviation can be obtained, for example, as follows. Drive a test vehicle equipped with a sensor that directly measures the amount of deviation. By repeatedly directly measuring the amount of deviation with the sensor while the test vehicle is traveling at a predetermined cycle, the amount of deviation in the entire traveling section of the railway vehicle is obtained. In addition, for example, the measuring device described in Patent Document 2 can be used to obtain an actually measured value of a deviation amount. As described above, the measured value of the amount of deviation can be obtained by a known technique. Therefore, the detailed description thereof will be omitted here.

12A to 14B show the estimated value of the amount of deviation (y _R ), the actual value of the amount of deviation (y _R ), the traveling speed of the railroad vehicle (v), and the curvature of the track 16 (rail) (1). It is a figure which shows the 1st to 6th examples of the relationship between / R) and the distance from the starting point of a railroad vehicle. The estimated value of the amount of deviation is calculated by the first orbital state calculation unit 407. The actual value of the amount of deviation is acquired by the actual value acquisition unit 408. Further, in FIGS. 12A to 14B, for convenience of notation, the illustration of the data of the portion where the distance from the starting point of the railway vehicle is small is omitted.

In FIGS. 12A to 14B, graphs 1211, 1221, 1311, 1321, 1411, 1421 show estimated values of the amount of deviation as calculated by the first orbital state calculation unit 407. Graphs 1212, 1222, 1312, 1322, 1412, and 1422 show the actual value of the deviation amount as acquired by the actual value acquisition unit 408. Graphs 1213, 1223, 1313, 1323, 1413, 1423 show the traveling speeds of railway vehicles. Graphs 1214, 1224, 1314, 1324, 1414, 1424 show the curvature 1 / R of the track 16 (rail).

In FIGS. 12A to 14B, a curvature 1 / R of 0 (zero) indicates a linear orbit, and a value other than curvature 1 / R of 0 (zero) indicates a curved orbit. show.
12A and 12B show that graphs 1214 and 1224 are the same and have the same traveling section. 12A and 12B show that the traveling speeds of the railroad vehicles are different, as shown in graphs 1213 and 1223. As described in Graphs 1211, 1221, the estimated value of the amount of deviation is different due to the difference in the traveling speed of the railroad vehicle in the same traveling section, but it can be seen that the difference is not so large.

Further, the graphs 1212 and 1222 (actual values of the amount of deviation) are the same. As shown in graphs 1211, 1212, there is a difference between the estimated value of the amount of deviation calculated by the first orbital state calculation unit 407 and the actual value of the amount of deviation acquired by the actual value acquisition unit 408. It turns out that there is. This is the same in graphs 1221 and 1222.
As described above, it can be seen that the accuracy of estimating the amount of deviation decreases depending on the traveling state of the railroad vehicle and the installation state of the track 16.

As shown in Graphs 1214 and 1224, the traveling section shown in FIGS. 12A and 12B has a sharp curve with a radius of curvature R of 171 m. Therefore, the railroad vehicle is in contact with the flange.
Here, the flange contact will be described. FIG. 15 is a diagram illustrating an example of flange contact. FIG. 15 shows a cross section when the left and right rails of the track 16 and one wheelset 13 are cut perpendicular to the traveling direction (x-axis direction) of the railway vehicle. Further, FIG. 15 shows a state of the wheel set 13 when the track 16 (rail) is bent in the right direction (negative direction of the y-axis) and the railroad vehicle is traveling while turning in the right direction. In FIG. 15, the lateral creep force F _{y Li and the normal load N Li on the left wheel 14L and the lateral creep force F y} ^R _{i and} ^the _normal load ^{N R i} _on the right wheel _14R are shown together. ..

As shown in FIG. 15, when the railroad vehicle travels on a track that is bent to the right, the railroad vehicle receives an action force in the left direction (positive direction of the y-axis), and the wheel shaft 13 moves to the left. By doing so, the reaction force in the left-right direction from the contact position between the wheels 14L and 14R and the rail becomes large, and the balance point of the force is reached. When this acting force becomes larger, the wheel set 13 moves further to the left, and when the contact angle α ^L becomes the same as the flange angle a ^L of the left wheel 14L, as shown in FIG. 15, the left wheel 14L has a rail. Will come into contact with the flange. Such contact is called flange contact. On the other hand, in this state, the right wheel 14R comes into contact with the rail on the tread.

13A and 13B show that graphs 1314 and 1324 are the same and have the same traveling section. As shown in graphs 1314 and 1324, since the curvature 1 / R is 0 (zero), it can be seen that the traveling section shown in FIGS. 13A and 13B is a straight track. 13A and 13B show that the traveling speeds of the railcars are different, as shown in graphs 1313 and 1323. As described in Graphs 1311, 1321, the estimated value of the amount of deviation is different due to the difference in the traveling speed of the railroad vehicle in the same traveling section, but it can be seen that the difference is not so large. Further, in FIGS. 13A and 13B, since the traveling speed of the railway vehicle is reduced to 30 km / h or less, the S / N ratio of the measured value of the front-rear direction force is reduced. Therefore, as shown in Graphs 1311, 1321, high-frequency noise is mixed in the estimated value of the amount of deviation. However, in graphs 1311 and 1321, it can be seen that the feature amount of the amount of deviation (how the graph changes, etc.) is captured.

Further, the graphs 1312 and 1322 (actual values of the amount of deviation) are the same. As shown in graphs 1311, 1312, the estimated value of the estimated value of the deviation amount calculated by the first orbital state calculation unit 407 and the actual value of the deviation amount acquired by the actual value acquisition unit 408. It turns out that there is a difference. This also applies to graphs 1321 and 1322.
As described above, it can be seen that the accuracy of estimating the amount of deviation decreases depending on the traveling state of the railroad vehicle.

14A and 14B show that graphs 1414 and 1424 are the same and have the same traveling section. 14A and 14B show that the traveling speeds of the railroad vehicles are different, as shown in graphs 1413 and 1423. As described in the graphs 1411, 1421, the estimated values of the amount of deviation are different due to the difference in the traveling speed of the railroad vehicle in the same traveling section, but it can be seen that the difference is not so large. Further, the graphs 1412 and 1422 (actual values of the amount of deviation) are the same. As shown in graphs 1411, 1412, there is a difference between the estimated value of the deviation amount calculated by the first orbital state calculation unit 407 and the actual value of the deviation amount acquired by the actual value acquisition unit 408. It turns out that there is. This also applies to graphs 1421 and 1422.

As shown in Graphs 1414 and 1424, the traveling section shown in FIGS. 14A and 14B has a gentle curve with a radius of curvature R of 993 m, and the railroad vehicle is not in contact with the flange.
As described above, it can be seen that the accuracy of estimating the amount of deviation decreases depending on the installation state of the track 16.

[Correction amount calculation unit 409, correction amount storage unit 410, S707 to S711]
When the correction amount calculation unit 409 calculates the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle by the first track state calculation unit 407, the correction amount calculation unit 409 corrects at each position of the entire traveling section of the railway vehicle. Calculate the amount. The correction amount at each position of the entire traveling section of the railway vehicle is a correction amount for the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle, which is calculated by the second track state calculation unit 411 described later. ..

The correction amount calculation unit 409 is the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle calculated by the first track state calculation unit 407, and the railway vehicle acquired by the actual value acquisition unit 408. The correction amount at each position of the entire traveling section of the railway vehicle is calculated based on the measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle.
In the present embodiment, the correction amount calculation unit 409 calculates the correction amount at each position of the entire traveling section of the railway vehicle as follows.

The correction amount calculation unit 409 is a pair of the estimated value of the deviation amount calculated by the first orbital state calculation unit 407 and the measured value of the deviation amount acquired by the actual value acquisition unit 408. , Extract a pair of values at the same position. The correction amount calculation unit 409 calculates a value obtained by subtracting the measured value of the deviation amount from the extracted estimated value of the deviation amount as the correction amount at the position. The correction amount calculation unit 409 calculates such a correction amount using the estimated value of the deviation amount and the measured value of the deviation amount at each position of the entire traveling section of the railway vehicle. In this way, the correction amount at each position of the entire traveling section of the railway vehicle is calculated.

In the present embodiment, when the railway vehicle travels once in the entire traveling section, the first track state calculation unit 409 calculates one set of correction amounts at all positions of the entire traveling section of the railway vehicle (step S707). ..
The correction amount calculation unit 409 can calculate the correction amount at all positions of the entire traveling section of the railway vehicle by performing interpolation processing on the correction amount at each position of the entire traveling section of the railway vehicle. ..

In the following description, the correction amount at each position of the entire traveling section of the railway vehicle, which is obtained by traveling the railway vehicle once in the entire traveling section in this way, is used as necessary for the entire traveling section of the railway vehicle. It is referred to as a first correction amount or a first correction amount at each position.
The first correction amount at each position of the entire traveling section of the railway vehicle may be used as the correction amount for the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle. However, in the present embodiment, the correction amount calculation unit 409 uses a plurality of first correction amounts as the first correction amount at a certain position in the entire traveling section of the railway vehicle, and the amount of deviation at the position is the same. Calculate the correction amount for the estimated value. This is because the accuracy of the correction amount with respect to the estimated value of the deviation amount can be improved.

In the present embodiment, as an example thereof, the arithmetic mean value of the plurality of first correction amounts is used as the correction amount for the estimated value of the deviation amount at each position of the entire traveling section of the railway vehicle. In the following description, the correction amount for the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle, which is obtained by using the plurality of first correction amounts in this way, is determined as necessary for the railway vehicle. It is referred to as a second correction amount or a second correction amount at each position of the entire traveling section of the above.

When the correction amount calculation unit 409 obtains the first correction amount at each position of the entire traveling section of the railway vehicle, the correction amount calculation unit 409 temporarily stores the first correction amount at each position of the entire traveling section of the railway vehicle (the correction amount calculation unit 409). Step S708).
Then, the correction amount calculation unit 409 determines whether or not a predetermined number of first correction amounts required for calculating the arithmetic mean value have been obtained (step S709). The predetermined number may be any number as long as it is 2 or more. As a result of this determination, when the predetermined number of first correction amounts required for calculating the arithmetic mean value is not obtained (NO in step S709), the inspection device 400 is used again for the railway vehicle in the entire traveling section. The above-mentioned steps S701 to S708 are performed while the vehicle is traveling, and a new first correction amount is stored.

As described above, when the predetermined number of first correction amounts required for calculating the added mean value is obtained (YES in step S709), the correction amount calculation unit 409 is in charge of the predetermined number of first correction amounts. The added average value of the correction amount is calculated as the second correction amount (step S710). The correction amount storage unit 410 stores the second correction amount (step S711). As described above, the second correction amount is a correction amount for the estimated value of the deviation amount, and is used by the orbital state correction unit 412 described later.

After the second correction amount is stored in the correction amount storage unit 410 as described above, the data acquisition unit 403, the first frequency adjustment unit 404, the filter calculation unit 405, the second frequency adjustment unit 406, and the second The orbital state calculation unit 411, the orbital state correction unit 412, and the output unit 413 are activated. That is, after the second preprocessing according to the flowchart of FIG. 7 is completed, the main processing according to the flowchart of FIG. 8 starts. At the time of this processing, the first orbital state calculation unit 407, the actual value acquisition unit 408, and the correction amount calculation unit 409 are not activated. Further, it is assumed that the flowchart of FIG. 8 is repeatedly executed every time the sampling time arrives.

16A to 16C are diagrams showing first to third examples of the relationship between the second correction amount M and the distance from the starting point of the railway vehicle, respectively. FIG. 16A shows the second complement M obtained from the results shown in FIGS. 12A and 12B. FIG. 16B shows a second complement M obtained from the results shown in FIGS. 13A and 13B. 16C shows a second complement M obtained from the results shown in FIGS. 14A and 14B.

[Data acquisition unit 403, S801]
The data acquisition unit 403 acquires measurement data at a predetermined sampling cycle. In step S801, the data acquisition unit 403 shall acquire one set of measurement data at the sampling time. Since the measurement data acquired by the data acquisition unit 403 has the same measurement target as the measurement data acquired in step S701, detailed description thereof will be omitted here.
[First frequency adjusting unit 404, S802]
The first frequency adjusting unit 404 reduces (preferably removes) the signal strength of the low frequency component included in the time-series data of the measured value of the front-back direction force in the measurement data acquired by the data acquisition unit 403. Since the process of step S802 is the same as the process of step S702, detailed description thereof will be omitted here.

However, in step S702, the first frequency adjusting unit 404 is a time series in which the low frequency component included in the data y of the measured value of the front-rear direction force is extracted after the measurement data in the entire traveling section of the railway vehicle is obtained. Derive the data. On the other hand, in step S802, in the first frequency adjusting unit 404, every time the data acquisition unit 403 acquires the value y _k at the time k of the data y of the measured value of the anteroposterior force in a predetermined sampling cycle. Time-series data obtained by extracting low-frequency components included in the data y of the measured value of the front-back direction force is derived.

[Filter calculation unit 405, S803]
The filter calculation unit 405 uses the Kalman filter as an observation equation stored by the observation equation storage unit 402 as an observation equation and a state equation stored by the state equation storage unit 401 as the state equation of the state variable shown in equation (44). Determine an estimate. Since the process of step S803 is the same as the process of step S703, detailed description thereof will be omitted here.

[Second frequency adjustment unit 406, S804]
The second frequency adjusting unit 406 reduces (preferably removes) the signal strength of the low frequency component included in the time series data of the estimated value of the state variable generated by the filter calculation unit 405. Since the process of step S804 is the same as the process of step S704, detailed description thereof will be omitted here.

[Second orbital state calculation unit 411, S805]
The second orbital state calculation unit 411 calculates the deviation amount y _R1 to y _R4 , and calculates the deviation amount y _R as the estimated value of the deviation amount from the deviation amount y _R1 to y _R4 . Since the process of step S805 is the same as the process of step S705, detailed description thereof will be omitted here. However, in step S705, the first track state calculation unit 411 calculates an estimated amount of deviation amount at each position of the entire traveling section of the railway vehicle. On the other hand, in step S805, the second track state calculation unit 411 calculates an estimated amount of deviation amount at the traveling position of the railway vehicle corresponding to the current sampling time.

[Orbital state correction unit 412, S806]
The track state correction unit 412 reads out a second correction amount at the traveling position of the railway vehicle corresponding to the current sampling time from the correction amount storage unit 410. The track state correction unit 412 was calculated by the second track state calculation unit 411 using the second correction amount at the traveling position of the railway vehicle corresponding to the current sampling time read from the correction amount storage unit 410. , Correct the estimated value of the amount of deviation in the running position of the railroad vehicle corresponding to the current sampling time.

In the present embodiment, the track state correction unit 412 is a correction amount storage unit from the estimated value of the deviation amount at the traveling position of the railway vehicle corresponding to the current sampling time, which is calculated by the second track state calculation unit 411. The railway corresponding to the current sampling time calculated by the second track state calculation unit 411 by subtracting the second correction amount at the traveling position of the railway vehicle read from 410 and corresponding to the current sampling time. Correct the estimated value of the amount of deviation in the running position of the vehicle. In the following description, the estimated value of the amount of deviation at the traveling position of the railway vehicle corresponding to the current sampling time, which is corrected in this way, is referred to as an estimated value of the amount of deviation after correction, if necessary. .. The estimated value of the corrected street deviation amount becomes the final estimated value of the street deviation amount.

When the second correction amount in the correction amount calculation unit 409 is a value obtained by subtracting the estimated value of the deviation amount from the measured value of the deviation amount, the track state correction unit 412 is as follows. Then, the estimated value of the amount of deviation at the traveling position of the railroad vehicle corresponding to the current sampling time calculated by the second track state calculation unit 411 is corrected. That is, the track state correction unit 412 reads from the correction amount storage unit 410 and the estimated value of the amount of deviation at the traveling position of the railway vehicle corresponding to the current sampling time, which is calculated by the second track state calculation unit 411. In addition, the railway vehicle corresponding to the current sampling time calculated by the second track state calculation unit 411 by adding the second correction amount at the traveling position of the railway vehicle corresponding to the current sampling time. Correct the estimated value of the amount of deviation at the running position.

17A to 19B are diagrams showing first to sixth examples of the relationship between the corrected estimated value of the deviation amount and the distance from the starting point of the railway vehicle, respectively. Here, for the sake of simplicity, the estimated value of the deviation amount calculated by the second orbital state calculation unit 411 is the same as the estimated value of the deviation amount calculated by the first orbital state calculation unit 411. It is supposed to be.

That is, in the graphs 1711 and 1721 of FIGS. 17A and 17B, as shown in FIGS. 12A and 12B, the estimated values of the deviation amount (graphs 1211, 1221) are corrected by the correction amount M shown in FIG. 16A, respectively. The estimated value of the amount of deviation is shown. Further, the graphs 1212, 1222, 1712, and 1722 (actual values of the amount of deviation) are the same.
In the graphs 1811 and 1821 of FIGS. 18A and 18B, the estimated values of the deviation amount (graphs 1311, 1321) shown in FIGS. 13A and 13B are corrected by the correction amount M shown in FIG. 16B, respectively. Shows an estimate of the quantity. Further, the graphs 1312, 1322, 1812, and 1822 (actual values of the amount of deviation) are the same.

Graphs 1911 and 1921 of FIGS. 19A and 19B show deviations after correction of estimated values (graphs 1411, 1421) of the amount of deviation as shown in FIGS. 14A and 14B, respectively, corrected by the correction amount M shown in FIG. 16C. Shows an estimate of the quantity. Further, the graphs 1412, 1422, 1912, and 1922 (actual values of the amount of deviation) are the same.
As shown in FIGS. 17A to 19B, in any case, it can be seen that the estimated value of the deviation amount after the correction agrees with the measured value with high accuracy.

[Output unit 413, S807]
The output unit 413 outputs the information of the estimated value of the deviation amount as corrected as calculated by the track state correction unit 412. At this time, the output unit 413 may output information indicating that the orbit 16 is abnormal when the estimated value of the deviation amount after the correction is larger than the preset value. As the form of output, for example, at least one of display on a computer display, transmission to an external device, and storage in an internal or external storage medium can be adopted.

<Summary>
As described above, in the present embodiment, the inspection device 400 drives the railroad vehicle and acquires the measured values of the front-rear directional forces T ₁ to T ₄ . _The inspection device ₄₀₀ uses the measured values of the longitudinal forces T1 to _{T4 and the relational expression between the longitudinal forces T1 to T4 and the amount of deviation y R1 to y R4 at the} positions of the wheel sets 13a to 13d. Then, the estimated value of the amount of deviation at each position of the entire traveling section of the railroad vehicle is obtained. The inspection device 400 uses the estimated value and the measured value of the amount of deviation at each position of the entire traveling section of the railway vehicle as a correction amount for the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle. Calculate the correction amount of 2. After that, the inspection device 400 runs the railroad vehicle and obtains an estimated value of the amount of deviation in the running position of the railroad vehicle as described above. The inspection device 400 corrects the estimated value of the amount of deviation in the traveling position of the railway vehicle thus obtained by the second correction amount in the traveling position. Therefore, the irregularity of the track 16 of the railway vehicle can be detected with high accuracy without using a special measuring device.

Further, in the present embodiment, the inspection device ₄₀₀ reduces the signal strength of the low frequency component included in the time _- series data of the measured values of the anteroposterior force T1 to _T4 , and the high frequency of the anteroposterior force T1 to _T4 . Generate time series data of components. The inspection device 400 transmits the time-series data of the high _- frequency components of the front _- rear direction forces T1 to _{T4 to the relationship between the front-rear direction forces T1 to T4 and the amount of deviation y R1 to y R4 at the} positions of the wheel sets 13a to 13d. By giving to the equation, the amount of deviation y _R1 to y _R4 at the positions of the wheel sets 13a to 13d is calculated. This relational expression is an equation based on an equation of motion (that is, an equation that does not include the radius of curvature R of the track 16 (rail)) that describes the motion of a railroad vehicle when traveling on a straight track. Therefore, irregularities in the curved orbit can be detected with high accuracy without using a special measuring device.

Further, in the present embodiment, the inspection device 400 generates an autocorrelation matrix R from the data y of the measured value of the anteroposterior force, and is the largest of the eigenvalues obtained by decomposing the autocorrelation matrix R into singular values. Using s eigenvalues from the thing, the coefficient α of the modified autocorrelation model that approximates the data y of the measured value of the anteroposterior force is determined. Therefore, the coefficient α can be determined so that the signal of the low frequency component included in the data y of the measured value of the anteroposterior force remains and the high frequency component does not remain. The inspection device 400 applies the predicted value y ^ _k of the anteroposterior force at the time k to the modified autoregressive model in which the coefficient α is determined in this way, at a time kl (1 ≦ l ≦) before that time. It is calculated by giving the data y of the measured value of the anteroposterior force in m). Therefore, it is possible to reduce the signal of the low frequency component caused by the traveling of the curved track of the railway vehicle from the data y of the measured value of the front-rear direction force without assuming the cutoff frequency in advance.

Further, in the present embodiment, the inspection device ₄₀₀ is generated by the measurement data obtained by the data acquisition unit 403, excluding the longitudinal forces T1 to T4, and the _first frequency adjustment unit 404. The time-series data of the high _- frequency components of the longitudinal forces T1 to T4 and the time _- series data are given to the Kalman filter, and the state variables (y _w1 · to y _w4 ·, y _w1 ~ y _w4 , y _t1 · ~ y _t2 ·, y _t1 ～ y _t2 , ψ _t1・ ～ ψ _t2・, ψ _t1 ～ ψ _t2 , φ _t1・ ～ φ _t2・, φ _t1 ～ φ _t2 , y _b・, y _b , ψ _b・, ψ _b , φ _b・, φ _b , ψ _y1 , ψ _y2 , φ _a1 , φ _a2 ) are derived. Next, the inspection device 400 calculates the value of the high frequency component of the state variable by reducing (preferably removing) the signal strength of the low frequency component included in the time series data of the estimated value of the state variable. Next, the inspection device ₄₀₀ uses the values of the high-frequency components of the rotation amounts (angular displacements) ψ _t1 to ψ _t2 in the yawing direction of the trolleys 12a and 12b and the actual values of the conversion variables e1 to _e4 . The amount of rotation (angular displacement) ψ _w1 to ψ _w4 of the wheel sets 13a to 13d in the yawing direction is derived. Next, the inspection device 400 uses the equation of motion for describing the yawing of the wheel sets 13a to 13d, the amount of rotation (angular displacement) ψ _w1 to ψ _w4 in the yawing direction of the wheel sets 13a to 13d, and the value of the high frequency component of the state variable. By substituting the values of the high frequency components of the longitudinal forces T1 to _{T4, the amount of displacement y R1 to} y _R4 at the positions of the wheel _sets 13a to 13d is calculated. Then, the inspection device 400 calculates the deviation amount y _R from the deviation amount y _R1 to y _R4 at the positions of the wheel sets 13a to 13d. Therefore, it is not necessary to construct the equation of motion using the equation of motion including the amount of deviation y _R1 to y _R4 at the positions of the wheel shafts 13a to 13d as a variable as the equation of motion for describing the yawing of the wheel shafts 13a to 13d. This eliminates the need to create a model of the orbit 16 and reduces the number of state variables. In this embodiment, the degree of freedom of the model can be reduced from 21 degrees of freedom to 17 degrees of freedom, and the number of state variables can be reduced from 38 to 30. In addition, the measured value used in the Kalman filter increases by the amount of the front-rear direction force T ₁ to T ₄ .

On the other hand, if the equation of motion that describes the yawing of the wheel sets 13a to 13d of equations (5) to ( ₈ ) is included in the state equation without using the longitudinal forces T1 to _T4 , the calculation becomes unstable and is estimated. Results may not be obtained. That is, if the state variable is not selected, the calculation becomes unstable and the estimation result may not be obtained. Further, even if an estimation result is obtained, the method of the present embodiment has higher accuracy of detecting irregularities of the orbit 16 than the method of not selecting a state variable. This is because the present embodiment does not include the equation of motion that describes the yawing of the wheel sets 13a to 13d in the state equation, and uses the measured value of the anteroposterior force.

Further, in the present embodiment, since the strain gauge can be used as the sensor, no special sensor is required. Therefore, the abnormality (orbital irregularity) of the orbit 16 can be accurately detected without incurring a large cost. In addition, since it is not necessary to use a special sensor, by attaching a strain gauge to the commercial vehicle and mounting the inspection device 400 on the commercial vehicle, it is possible to detect irregularities in the track 16 in real time while the commercial vehicle is running. can. Therefore, the irregularity of the track 16 can be detected without running the inspection vehicle. However, a strain gauge may be attached to the inspection vehicle, and the inspection device 400 may be mounted on the inspection vehicle.

<Modification example>
In the present embodiment, the case where the arithmetic mean value of the plurality of first correction amounts is used as the correction amount for the estimated value of the deviation amount at each position of the entire traveling section of the railway vehicle has been described as an example. However, it is not always necessary to obtain the correction amount for the estimated value of the amount of deviation at each position of the entire traveling section of the railway vehicle in this way.

For example, the inspection device 400 calculates a plurality of first correction amounts as the first correction amount at the same position in a state where the traveling speeds of the railway vehicles are different from each other. The inspection device 400 performs regression analysis using these plurality of first correction quantities, and calculates the coefficient of the regression equation. The objective variable of the regression equation is the second complement. The explanatory variables of the regression equation include the traveling speed of the railroad vehicle. The inspection device 400 obtains such a regression equation at each position of the entire traveling section of the railway vehicle. After that, the inspection device 400 (track state correction unit 412) reads out the regression equation corresponding to the traveling position of the railway vehicle corresponding to the current sampling time from the correction amount storage unit 410. Then, the inspection device 400 (track state correction unit 412) substitutes the traveling speed of the railway vehicle corresponding to the current sampling time into the regression equation to calculate the second correction amount.

Further, it is not necessary to calculate the correction amount for the estimated value of the amount of deviation at a certain position in the entire traveling section of the railway vehicle by using the plurality of first correction amounts. In this case, the correction amount for the estimated value of the amount of deviation at a certain position in the entire traveling section of the railway vehicle is determined by one first correction amount at the position. In this way, the accuracy of the correction amount with respect to the estimated value of the deviation amount may decrease. However, in the second pretreatment, it is not necessary to run the railroad vehicle a plurality of times. For example, it is possible to determine which method is to be adopted in consideration of the accuracy of the correction amount with respect to the estimated value of the deviation amount and the time and effort of the second preprocessing.

Further, in step S701 of the flowchart of FIG. 7, the case where the data acquisition unit 403 acquires the measurement data in the entire traveling section of the railway vehicle has been described as an example. However, it is not always necessary to do this. For example, as in the flowchart of FIG. 8, in step S701, the data acquisition unit 403 may acquire one set of measurement data at the sampling time. In this case, the processes of steps S701 to S708 are repeatedly performed for each traveling position of the railway vehicle corresponding to the sampling time. This process is repeated until a correction amount (first correction amount) at each position of the entire traveling section of the railway vehicle is obtained.

Further, in the present embodiment, the measured values of the longitudinal force used by the first track state calculation unit 407 and the second track state calculation unit 411 are measured values in the same railway vehicle as an example. explained. In this case, the inspection device 400 for calculating the estimated value of the deviation amount and the inspection device 400 for calculating the second correction amount are the inspection devices 400 mounted on the same railway vehicle. This is preferable because it is possible to suppress the error due to the characteristics peculiar to the railway vehicle from being included in the second correction amount. However, it is not always necessary to do this. For example, the same second correction amount may be used for a plurality of railroad vehicles of the same model and traveling in the same traveling section. Further, the same second correction amount may be used for a plurality of railway vehicles having the same line name.

Further, in the present embodiment, a case where a modified autoregressive model is used has been described as an example. However, it is not always necessary to reduce the signal of the low frequency component caused by the traveling of the curved track of the railroad vehicle from the data y of the measured value in the front-rear direction by using the modified autoregressive model. For example, when it is possible to identify the frequency band caused by the traveling of the curved track of the railway vehicle, the high-pass filter is used and the data y of the measured value of the front-rear direction force is used to cause the traveling of the curved track of the railway vehicle. The signal of the low frequency component may be reduced.

Further, it is not always necessary to reduce the signal of the low frequency component caused by the traveling of the curved track of the railway vehicle from the data y of the measured value in the front-rear direction. For example, it is not necessary to do this when calculating the amount of deviation according to a straight line orbit. In this case, the first frequency adjusting unit 404 and the second frequency adjusting unit 406 become unnecessary.

Further, in the present embodiment, the case where the wheel set as a reference for adjusting the phase is the wheel set 13a has been described as an example. However, the reference wheel set may be a wheel set 13b, 13c, or 13d other than the wheel set 13a.

In this embodiment, a case where a Kalman filter is used has been described as an example. However, if a filter that derives the estimated value of the state variable (that is, a filter that performs data assimilation) is used so that the error between the measured value and the estimated value of the observed variable is minimized or the expected value of the error is minimized. , It is not always necessary to use the Kalman filter. For example, a particle filter may be used. As an error between the measured value of the observed variable and the estimated value, for example, a square error between the measured value of the observed variable and the estimated value can be mentioned.

Further, in the present embodiment, the case of deriving the amount of deviation is described as an example. However, if the physical quantity that reflects the orbital irregularity (the appearance defect of the orbital 16) is derived as the physical quantity that reflects the state of the orbital 16 (first physical quantity), it is not always necessary to derive the deviation amount. .. For example, by performing the following equations (64) to (67) in addition to or in place of the amount of deviation, the lateral pressure (wheel and rail) generated when the railway vehicle is traveling on a straight track. The stress in the left-right direction between them) may be derived. However, Q ₁ , Q ₂ , Q ₃ , and Q ₄ are lateral pressures on the wheels 14a, 14b, 14c, and 14d, respectively. f ₃ represents the spin creep coefficient.

Further, in the present embodiment, a case where a state variable representing the state of the vehicle body 11 is included has been described as an example. However, the vehicle body 11 is a portion where the propagation of vibration due to the acting force (creep force) between the wheels 14a to 14d and the track 16 is finally transmitted. Therefore, for example, when it is determined that the influence of the propagation is small in the vehicle body 11, it is not necessary to include the state variable representing the state of the vehicle body 11. In this case, among the equations of motion of equations (1) to (21), the equations of motion describing the lateral vibration, yawing, and rolling of the vehicle body 11 of equations (15) to (17) and (18). The equation of motion for describing the yawing of the yaw of the equation, the yaw damper arranged on the bogie 12a of the equation (19), and the yaw of the yaw damper arranged on the bogie 12b becomes unnecessary. Further, in the equations of motion of equations (1) to (21), the state quantity related to the vehicle body (state quantity including the subscript b) and the state quantity relating to the vehicle body (state quantity including the subscript b) are included in {}. Set the value (for example, {φ _a2 -φ _b } in the third term on the left side of the equation (21)) to 0 (zero).

Further, in the present embodiment, the case where the bogies 12a and 12b are bolsterless bogies has been described as an example. However, the bogies 12a and 12b are not limited to bolsterless bogies. In addition, the equation of motion is appropriately rewritten according to the components of the railroad vehicle, the force received by the railroad vehicle, the direction of motion of the railroad vehicle, and the like. That is, the equation of motion is not limited to that exemplified in this embodiment.

(Second embodiment)
Next, the second embodiment will be described.
In the first embodiment, the case where the inspection device 400 mounted on the railroad vehicle calculates and corrects the estimated value of the amount of deviation has been described as an example. On the other hand, in the present embodiment, a data processing device equipped with some functions of the inspection device 400 is arranged at the command center. This data processing device receives measurement data transmitted from a railroad vehicle, calculates an estimated value of a deviation amount using the received measurement data, and corrects it. As described above, in the present embodiment, the functions of the inspection device 400 of the first embodiment are shared and executed by the railway vehicle and the command center. The configuration and processing according to this are mainly different between the present embodiment and the first embodiment. Therefore, in the description of the present embodiment, the same parts as those of the first embodiment are designated by the same reference numerals as those given in FIGS. 1 to 19B, and detailed description thereof will be omitted.

FIG. 20 is a diagram showing an example of the configuration of the inspection system. In FIG. 20, the inspection system includes data acquisition devices 2010a and 2010b and a data processing device 2020. FIG. 20 also shows an example of the functional configuration of the data acquisition devices 2010a and 2010b and the data processing device 2020. The hardware of the data acquisition devices 2010a and 2010b and the data processing device 2020 can be realized by, for example, those shown in FIG. Therefore, detailed description of the hardware configuration of the data acquisition devices 2010a and 2010b and the data processing device 2020 will be omitted.

Each of the railroad vehicles is equipped with one data acquisition device 2010a and one 2010b. The data processing device 2020 is arranged at the command center. The command center, for example, centrally manages the operation of a plurality of rolling stock.

<Data collection devices 2010a, 2010b>
The data acquisition devices 2010a and 2010b can be realized by the same device. The data acquisition devices 2010a and 2010b include data acquisition units 2011a and 2011b and data transmission units 2012a and 2012b.

[Data acquisition units 2011a, 2011b]
The data acquisition units 2011a and 2011b have the same functions as the data acquisition unit 403. That is, the data acquisition units 2011a and 2011b acquire the same measurement data as the measurement data acquired by the data acquisition unit 403. Specifically, the data acquisition units 2011a and 2011b measure the measurement data of the acceleration in the left-right direction of the vehicle body 11, the measurement value of the acceleration in the left-right direction of the carriages 12a and 12b, and the measurement of the acceleration in the left-right direction of the wheel shafts 13a to 13d. Obtain the value and the measured value of the forward / backward force. The strain gauge and arithmetic unit for obtaining these measured values are the same as those described in the first embodiment.

[Data transmission units 2012a, 2012b]
The data transmission units 2012a and 2012b transmit the measurement data acquired by the data acquisition units 2011a and 2011b to the data processing device 2020. In the present embodiment, the data transmission units 2012a and 2012b transmit the measurement data acquired by the data acquisition units 2011a and 2011b to the data processing device 2020 by wireless communication. At this time, the data transmission units 2012a and 2012b add the identification numbers of the railway vehicles on which the data collection devices 2010a and 2010b are mounted to the measurement data acquired by the data acquisition units 2011a and 2011b. In this way, the data transmission units 2012a and 2012b transmit the measurement data to which the identification number of the railroad vehicle is added.

<Data processing device 2020>
[Data receiving unit 2021]
The data receiving unit 2021 receives the measurement data transmitted by the data transmitting units 2012a and 2012b. An identification number of the railway vehicle that is the source of the measurement data is added to the measurement data.

[Data storage unit 2022]
The data storage unit 2022 stores the measurement data received by the data reception unit 2021. The data storage unit 2022 stores measurement data for each identification number of the railway vehicle. The data storage unit 2022 identifies the traveling position of the railway vehicle at the reception time of the measurement data based on the current operation status of the railway vehicle and the reception time of the measurement data, and the information of the specified traveling position and the measurement thereof. Store data in association with each other. The data collection devices 2010a and 2010b may collect information on the current traveling position of the railway vehicle and include the collected information in the measurement data.

[Data reading unit 2023]
The data reading unit 2023 reads out the measurement data stored by the data storage unit 2022. The data reading unit 2023 can read the measurement data specified by the operator from the measurement data stored by the data storage unit 2022. Further, the data reading unit 2023 can also read measurement data that meets the predetermined conditions at a predetermined timing. In the present embodiment, the measurement data read by the data reading unit 2023 is determined based on, for example, at least one of the identification number of the railway vehicle and the traveling position.

State equation storage unit 401, observation equation storage unit 402, first frequency adjustment unit 404, filter calculation unit 405, second frequency adjustment unit 406, first orbital state calculation unit 407, actual value acquisition unit 408, correction amount. The calculation unit 409, the correction amount storage unit 410, the second orbital state calculation unit 411, the orbital state correction unit 412, and the output unit 413 are the same as those described in the first embodiment. Therefore, these detailed explanations will be omitted here. The filter calculation unit 405 determines the estimated value of the state variable shown in the equation (44) by using the measurement data read by the data reading unit 2023 instead of the measurement data acquired by the data acquisition unit 403. ..

<Summary>
As described above, in the present embodiment, the data collecting devices 2010a and 2010b mounted on the railroad vehicle collect the measurement data and transmit it to the data processing device 2020. The data processing device 2020 arranged at the command center stores the measurement data received from the data collection devices 2010a and 2010b, and uses the stored measurement data to calculate and correct an estimated value of the amount of deviation. Therefore, in addition to the effects described in the first embodiment, for example, the following effects are exhibited. That is, the data processing device 2020 can calculate the final deviation amount _yR at an arbitrary timing by reading the measurement data at an arbitrary timing. In addition, the data processing device 2020 can output a time-series change in the estimated value of the final deviation amount at the same position. Further, the data processing device 2020 can output an estimated value of the amount of deviation in a plurality of lines for each line.

<Modification example>
In the present embodiment, the case where the measurement data is directly transmitted from the data collection devices 2010a and 2010b to the data processing device 2020 has been described as an example. However, it is not always necessary to do this. For example, an inspection system may be constructed using cloud computing.
In addition, in this embodiment as well, various modifications described in the first embodiment can be adopted.

Further, in the first embodiment, the state equation storage unit 401, the observation equation storage unit 402, the data acquisition unit 403, the first frequency adjustment unit 404, the filter calculation unit 405, the second frequency adjustment unit 406, and the first The track state calculation unit 407, the actual value acquisition unit 408, the correction amount calculation unit 409, the correction amount storage unit 410, the second track state calculation unit 411, the track state correction unit 412, and the output unit 413 are included in one device. The case was explained as an example. However, it is not always necessary to do this. State equation storage unit 401, observation equation storage unit 402, data acquisition unit 403, first frequency adjustment unit 404, filter calculation unit 405, second frequency adjustment unit 406, first orbital state calculation unit 407, actual value acquisition The functions of the unit 408, the correction amount calculation unit 409, the correction amount storage unit 410, the second orbital state calculation unit 411, the orbital state correction unit 412, and the output unit 413 may be realized by a plurality of devices. In this case, the inspection system is configured by using these plurality of devices.

(Other embodiments)
The embodiment of the present invention described above can be realized by executing a program by a computer. Further, a computer-readable recording medium on which the program is recorded and a computer program product such as the program can also be applied as an embodiment of the present invention. As the recording medium, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a magnetic tape, a non-volatile memory card, a ROM, or the like can be used.

In addition, the embodiments of the present invention described above are merely examples of embodiment of the present invention, and the technical scope of the present invention should not be construed in a limited manner by these. It is a thing. That is, the present invention can be implemented in various forms without departing from the technical idea or its main features.

The entire contents of the specification and drawings of Patent Document 1 can be incorporated herein by reference.

The present invention can be used to inspect the track of a railroad vehicle.

Claims (20)

A data acquisition means for acquiring measurement data, which is time-series data of measured values measured by traveling a railroad vehicle having a vehicle body, a trolley, and a wheel set on an orbit.
The first orbital state calculation means for calculating the estimated value of the first physical quantity, and
Correction to calculate the correction amount for the estimated value of the first physical quantity based on the estimated value of the first physical quantity calculated by the first orbital state calculating means and the actual value of the first physical quantity. Quantity calculation means and
After the correction amount is calculated, the second orbital state calculation means for calculating the estimated value of the first physical quantity, and
It has an orbital state correction means for correcting an estimated value of the first physical quantity calculated by the second orbital state calculating means by using the correction amount.
The measurement data includes the measured value of the anteroposterior force.
The front-rear direction force is a force in the front-rear direction generated in a member arranged between the wheel set and the bogie on which the wheel set is provided.
The member is a member for supporting the axle box, and is a member.
The front-rear direction is a direction along the traveling direction of the railway vehicle.
The first physical quantity is a physical quantity that reflects the state of the orbit.
The first orbital state calculating means and the second orbital state calculating means include a relational expression showing the relationship between the first physical quantity and the anteroposterior direction force at the position of the wheel set, and the anteroposterior direction force. Using the measured value, the estimated value of the first physical quantity is calculated.
The measured value of the anteroposterior force used in the first orbital state calculation means is included in the measurement data acquired by the data acquisition means before the correction amount is calculated.
An inspection system characterized in that the measured value of the anteroposterior force used in the second orbital state calculation means is included in the measurement data acquired by the data acquisition means after the correction amount is calculated. The correction amount calculating means is a plurality of the first ones calculated by the first track state calculating means using the measured values of the front-rear direction force when the railroad vehicle is traveling at the same position. The first aspect of claim 1, wherein the correction amount at the position is calculated as the correction amount for the estimated value of the first physical quantity based on the estimated value of the physical quantity and the actual value of the first physical quantity. Inspection system. The correction amount calculating means is a plurality of the first ones calculated by the first track state calculating means using the measured values of the front-rear directional force when the railroad vehicle is traveling at the same position. A correction amount for the estimated value of the first physical quantity is calculated based on the estimated value of the physical quantity, the traveling speed when the railroad vehicle is traveling at the position, and the actual value of the first physical quantity. death,
The inspection system according to claim 1 or 2, wherein the correction amount for the estimated value of the first physical quantity is a correction amount according to the position and traveling speed of the railway vehicle. Claims 1 to 3 are characterized in that the measured values of the anteroposterior force used in the first track state calculating means and the second track state calculating means are the measured values in the same railroad vehicle. The inspection system according to any one of the above items. From the time series data of the second physical quantity, it further has a frequency adjusting means for reducing the signal strength of the low frequency component generated by the railroad vehicle traveling on the curved portion of the track.
The second physical quantity is a physical quantity whose value fluctuates according to the state of the railway vehicle.
The frequency adjusting means is a low-frequency component generated by the railroad vehicle traveling on a curved portion of the track from time-series data of a measured value of the front-rear direction force, which is one of the second physical quantities. It has a first frequency adjusting means for reducing the signal strength of the
The first orbital state calculating means and the second orbital state calculating means include the relational expression and the value of the anteroposterior force in which the signal strength of the low frequency component is reduced by the first frequency adjusting means. , To calculate the estimated value of the first physical quantity.
The inspection system according to any one of claims 1 to 4, wherein the relational expression is an expression that does not include the radius of curvature of the rail. The frequency adjusting means determines a coefficient in the modified autoregressive model using the time-series data of the second physical quantity, and the modified autoregressive model in which the coefficient is determined, and the time-series data of the second physical quantity. From the time series data of the second physical quantity, the signal strength of the low frequency component generated by the railroad vehicle traveling on the curved portion of the track is reduced by using.
The modified autoregressive model is an expression expressing a predicted value of the second physical quantity by using the value of the second physical quantity and the coefficient with respect to the value.
The frequency adjusting means determines the coefficient by using an equation in which the first matrix is a coefficient matrix and the autocorrelation vector is a constant vector.
The autocorrelation vector is a vector whose component is the autocorrelation of the time series data of the second physical quantity whose time difference is from 1 to m, which is the number of measured values used in the modified autoregressive model.
The first matrix includes a second matrix Σ _s derived from the s eigenvalues of the autocorrelation matrix and the diagonal matrix Σ for s, which is a set number of 1 or more and less than m. It is a third matrix Us derived from the _s eigenvalues and the orthogonal matrix U, and a matrix _Us Σ _{s Us} ^T derived from the eigenvalues.
The autocorrelation matrix is a matrix whose component is the autocorrelation of the time series data of the second physical quantity having a time difference of 0 to m-1.
The diagonal matrix is a matrix having an eigenvalue of the autocorrelation matrix derived by singular value decomposition of the autocorrelation matrix as a diagonal component.
The orthogonal matrix is a matrix in which the eigenvector of the autocorrelation matrix is a column component vector.
The second matrix is a submatrix of the diagonal matrix, and is a matrix having the s eigenvalues as diagonal components.
The inspection system according to claim 5, wherein the third matrix is a submatrix of the orthogonal matrix, and the eigenvectors corresponding to the s eigenvalues are used as column component vectors. The inspection system according to claim 6, wherein the s eigenvalues include the maximum eigenvalue among the eigenvalues of the autocorrelation matrix. Using the measurement data, the state equation, and the observation equation, the estimated value of the state variable, which is a variable for which the estimated value should be determined by the state equation, is obtained by performing an operation using a filter that performs data assimilation. It also has a filter calculation means to determine
The measurement data further includes measured values of lateral acceleration of the bogie and the wheel set.
The left-right direction is a direction perpendicular to both the front-back direction and the up-down direction which is a direction perpendicular to the orbit.
The front-rear direction force is a force determined according to the difference between the angular displacement of the wheel set in the yawing direction and the angular displacement of the wheel set provided with the yaw direction.
The yawing direction is a rotation direction with the vertical direction as a rotation axis.
The equation of state is an equation described by using the state variable, the anteroposterior force, and the transformation variable.
The state variables are the lateral displacement and velocity of the trolley, the angular displacement and angular velocity of the trolley in the yawing direction, the angular displacement and angular velocity of the trolley in the rolling direction, and the lateral displacement and velocity of the wheel axis. , Includes the rolling angular displacement of the air spring attached to the railroad vehicle, and does not include the yawing angular displacement and angular velocity of the wheel axis.
The rolling direction is a rotation direction with the front-rear direction as a rotation axis.
The conversion variable is a variable that mutually converts the angular displacement of the wheel set in the yawing direction and the angular displacement of the trolley in the yawing direction.
The observation equation is an equation described by using the observation variable and the transformation variable.
The observed variables include lateral accelerations of the bogie and the wheel sets.
The filter calculation means includes the state equation in which the measured value of the observed variable, the measured value of the anteroposterior force, and the actual value of the converted variable are substituted, and the observed equation in which the actual value of the converted variable is substituted. To determine the error between the measured and estimated values of the observed variable or the estimated value of the state variable when the expected value of the error is minimized.
The first track state calculation means and the second track state calculation means include an estimated value of the angular displacement of the trolley in the yawing direction, which is one of the state variables determined by the filter calculation means, and the said. Using the actual value of the conversion variable, the estimated value of the angular displacement of the wheel axis in the yawing direction is calculated, the estimated value of the angular displacement of the wheel axis in the yawing direction, the value of the anteroposterior force, and the relational expression. And, the estimated value of the first physical quantity is calculated using
The relational expression is an equation expressing the equation of motion describing the motion of the wheel set in the yawing direction by using the anteroposterior force.
The inspection system according to any one of claims 1 to 7, wherein the actual value of the conversion variable is derived by using the measured value of the anteroposterior force. The state equations include a motion equation describing the lateral motion of the wheel axis, a motion equation describing the lateral motion of the trolley, a motion equation describing the motion of the trolley in the yawing direction, and the trolley. It is composed of a motion equation that describes the motion in the rolling direction and a motion equation that describes the motion in the rolling direction of the air spring.
The equation of motion describing the left-right motion of the wheel axis is an equation of motion described using the conversion variable instead of the angular displacement of the wheel axis in the yawing direction.
The equation of motion describing the movement of the trolley in the yawing direction is an equation of motion described by using the anteroposterior force instead of the angular displacement and the angular velocity of the wheel axis in the yawing direction.
The inspection system according to claim 8, wherein the transformation variable is represented by a difference between the angular displacement of the bogie in the yawing direction and the angular displacement of the wheel set in the yawing direction. The data acquisition means further acquires the measured value of the acceleration in the left-right direction of the vehicle body, and further acquires the measured value.
The observed variable further includes the left-right acceleration of the vehicle body.
The state variables are the lateral displacement and velocity of the vehicle body, the angular displacement and angular velocity of the vehicle body in the yawing direction, the angular displacement and angular velocity of the vehicle body in the rolling direction, and the yawing direction of the yaw damper attached to the railway vehicle. With more angular displacement,
8. The inspection system according to 9. The equations of motion are an equation of motion that describes the lateral motion of the vehicle body, an equation of motion that describes the motion of the vehicle body in the yawing direction, an equation of motion that describes the motion of the vehicle body in the rolling direction, and the yaw damper. The inspection system according to claim 10, further comprising an equation of motion describing motion in the yawing direction. The observation equation is further composed of an equation of motion that describes the lateral motion of the wheel axis and an equation of motion that describes the lateral motion of the trolley.
The equation of motion describing the lateral motion of the wheel axis is a motion equation described by using the conversion variable instead of the angular displacement of the wheel axis in the yawing direction, according to claims 8 to 11. The inspection system according to any one item. The inspection system according to claim 12, wherein the observation equation is further configured by using an equation of motion that describes the lateral motion of the vehicle body. The first track state calculation means and the second track state calculation means are determined by the filter calculation means and the displacement and speed of the trolley in the left-right direction, which are the state variables determined by the filter calculation means. The left-right displacement and velocity of the wheel axis, which are the state variables, the estimated value of the angular displacement of the wheel axis in the yawing direction, the measured value of the anteroposterior force, and the motion of the wheel axis in the yawing direction are described. Based on the equation of motion, the displacement amount according to the trajectory is derived as the estimated value of the first physical quantity.
The inspection system according to any one of claims 8 to 13, wherein the equation of motion describing the movement of the wheel set in the yawing direction includes the anteroposterior force and the amount of deviation according to the trajectory as variables. From the time series data of the second physical quantity, it further has a frequency adjusting means for reducing the signal strength of the low frequency component generated by the railroad vehicle traveling on the curved portion of the track.
The second physical quantity is a physical quantity whose value fluctuates according to the state of the railway vehicle.
The frequency adjusting means is a low-frequency component generated by the railroad vehicle traveling on the curved portion of the track from the time-series data of the estimated value of the state variable, which is one of the second physical quantities. The inspection system according to any one of claims 8 to 14, further comprising a second frequency adjusting means for reducing signal strength. The inspection system according to any one of claims 8 to 15, wherein the filter is a Kalman filter. The first physical quantity is an amount of deviation according to the track, or a lateral pressure which is a stress in the left-right direction between the wheel provided on the wheel set and the track.
The inspection system according to any one of claims 1 to 16, wherein the left-right direction is a direction perpendicular to both the front-rear direction and the up-down direction which is a direction perpendicular to the orbit. .. The front-rear direction force is a component of the front-rear direction components of the force generated in each of the two members attached to both sides of the wheel axle in the left-right direction, which are in opposite phase to each other.
The inspection system according to any one of claims 1 to 17, wherein the left-right direction is a direction perpendicular to both the front-rear direction and the up-down direction which is a direction perpendicular to the orbit. .. A data acquisition process for acquiring measurement data, which is time-series data of measured values measured by running a railroad vehicle having a vehicle body, a carriage, and a wheel set on a track, and
The first orbital state calculation step for calculating the estimated value of the first physical quantity, and
Correction to calculate the correction amount for the estimated value of the first physical quantity based on the estimated value of the first physical quantity calculated by the first orbital state calculation step and the actual value of the first physical quantity. Quantity calculation process and
After the correction amount is calculated, a second orbital state calculation step of calculating an estimated value of the first physical quantity, and
It has an orbital state correction step of correcting an estimated value of the first physical quantity calculated by the second orbital state calculation step by using the correction amount.
The measurement data includes the measured value of the anteroposterior force.
The front-rear direction force is a force in the front-rear direction generated in a member arranged between the wheel set and the bogie on which the wheel set is provided.
The member is a member for supporting the axle box, and is a member.
The front-rear direction is a direction along the traveling direction of the railway vehicle.
The first physical quantity is a physical quantity that reflects the state of the orbit.
The first orbital state calculation step and the second orbital state calculation step include a relational expression showing the relationship between the first physical quantity and the anteroposterior direction force at the position of the wheel set, and the anteroposterior direction force. Using the measured value, the estimated value of the first physical quantity is calculated.
The measured value of the anteroposterior force used in the first orbital state calculation step is included in the measurement data acquired by the data acquisition step before the correction amount is calculated.
An inspection method characterized in that the measured value of the anteroposterior force used in the second orbital state calculation step is included in the measurement data acquired by the data acquisition step after the correction amount is calculated. A data acquisition process for acquiring measurement data, which is time-series data of measured values measured by running a railroad vehicle having a vehicle body, a carriage, and a wheel set on a track, and
The first orbital state calculation step for calculating the estimated value of the first physical quantity, and
Correction to calculate the correction amount for the estimated value of the first physical quantity based on the estimated value of the first physical quantity calculated by the first orbital state calculation step and the actual value of the first physical quantity. Quantity calculation process and
After the correction amount is calculated, a second orbital state calculation step of calculating an estimated value of the first physical quantity, and
A computer is made to execute an orbital state correction step of correcting the estimated value of the first physical quantity calculated by the second orbital state calculation step by using the correction amount.
The measurement data includes the measured value of the anteroposterior force.
The front-rear direction force is a force in the front-rear direction generated in a member arranged between the wheel set and the bogie on which the wheel set is provided.
The member is a member for supporting the axle box, and is a member.
The front-rear direction is a direction along the traveling direction of the railway vehicle.
The first physical quantity is a physical quantity that reflects the state of the orbit.
The first orbital state calculation step and the second orbital state calculation step include a relational expression showing the relationship between the first physical quantity and the anteroposterior direction force at the position of the wheel set, and the anteroposterior direction force. Using the measured value, the estimated value of the first physical quantity is calculated.
The measured value of the anteroposterior force used in the first orbital state calculation step is included in the measurement data acquired by the data acquisition step before the correction amount is calculated.
The program characterized in that the measured value of the anteroposterior force used in the second orbital state calculation step is included in the measurement data acquired by the data acquisition step after the correction amount is calculated.

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