WO2021014854A1 - Inspection system, inspection method, and program - Google Patents

Abstract

According to the present invention, an inspection device (300) detects the states of axle springs (18L, 18R) of a railway vehicle by using a measured value of a physical quantity measured by causing the railway vehicle to travel on a track (30).

Description

Inspection system, inspection method, and program

The present invention relates to inspection systems, inspection methods, and programs, and is particularly suitable for use in inspecting shaft springs in railroad vehicles. The present application claims priority based on Japanese Patent Application No. 2019-137036 filed in Japan on July 25, 2019, and the entire contents of Japanese Patent Application No. 2019-137036 are incorporated herein by reference.

High safety is required for railroad vehicles. Therefore, it is necessary to inspect whether the railroad vehicle is normal or not.
Patent Document 1 describes a railway vehicle condition monitoring system including one acceleration sensor arranged on each bogie of a railway vehicle and an acceleration sensor arranged on a specific axle box to detect a defect of the railway vehicle. ing. Further, Patent Document 1 describes a method for monitoring the state of a railroad vehicle that detects an abnormality of an air spring based on an amplitude ratio based on the vertical acceleration of the bogie frame of the own bogie or another bogie when the railcar is sound. There is.
In the railcar condition monitoring system, when the frequency response of the vertical acceleration of the bogie frame based on the vertical acceleration of the axle box is shown, there is a difference between when the air spring is healthy and when it is abnormal in the frequency band of 3 Hz to 8 Hz. The occurrence is used to detect an abnormality in the air spring.
The method for monitoring the state of a railroad vehicle utilizes the fact that the amplitude ratio of the acceleration waveform of the bogie frame when there is a defect in the air spring deviates from 1 in a wide frequency band around 1 Hz to 10 Hz, resulting in an abnormality in the air spring. Is detected. The amplitude ratio of the acceleration waveform of the bogie frame when there is a defect in the air spring is an amplitude ratio based on the acceleration of the bogie frame when there is no abnormality in the air spring.
Further, Patent Document 1 describes that the air spring is a shaft spring.

Japanese Unexamined Patent Publication No. 2012-58208 International Publication No. 2017/164133 International Publication No. 2019/0433859

However, the technique described in Patent Document 1 measures the acceleration of the bogie and the axle box. Therefore, the physical quantity indicating the state of the shaft spring is not directly evaluated. In addition, it is not easy to extract data that contributes to detecting the state of the shaft spring from only the measurement data of the acceleration of the bogie and the axle box. Therefore, there is a problem that it is not easy to accurately detect the state of the shaft spring of the railway vehicle.

The present invention has been made in view of the above problems, and an object of the present invention is to enable accurate detection of the state of a shaft spring of a railway vehicle.

The inspection system of the present invention is an inspection system for inspecting the state of a shaft spring of a railroad vehicle having a vehicle body, a carriage, a wheel shaft, an axle box, and a shaft spring, and is measured by running the railroad vehicle on a track. There are a data acquisition means for acquiring the measured value of the physical quantity, and a shaft spring state detecting means for detecting the state of the shaft spring of the railroad vehicle by using the measured value of the physical quantity acquired by the data acquisition means. The physical quantity for which the measured value is acquired by the data acquisition means includes a front-rear direction force, and the front-rear direction force is generated in a member arranged between the wheel shaft and a carriage on which the wheel shaft is provided. It is a directional force, the member is a member for supporting the axle box, and the front-rear direction is a direction along the traveling direction of the railcar.

The inspection method of the present invention is an inspection method for inspecting the state of a shaft spring of a railroad vehicle having a vehicle body, a carriage, a wheel shaft, an axle box, and a shaft spring, and is measured by running the railroad vehicle on a track. It has a data acquisition step of acquiring the measured value of the physical quantity and a shaft spring state detecting step of detecting the state of the shaft spring of the railroad vehicle by using the measured value of the physical quantity acquired by the data acquisition step. The physical quantity whose measured value is acquired by the data acquisition process includes a front-rear direction force, and the front-rear direction force is generated in a member arranged between the wheel shaft and a carriage on which the wheel shaft is provided. It is a directional force, the member is a member for supporting the axle box, and the front-rear direction is a direction along the traveling direction of the railcar.

The program of the present invention is a program for causing a computer to execute a process for inspecting the state of a shaft spring of a railroad vehicle having a vehicle body, a carriage, a wheel set, an axle box, and a shaft spring, and tracks the railroad vehicle. A shaft that detects the state of the shaft spring of the railroad vehicle by using the data acquisition step of acquiring the measured value of the physical quantity measured by running on the above and the measured value of the physical quantity acquired by the data acquisition step. The physical quantity obtained by causing a computer to execute the spring state detection step and the measured value is acquired by the data acquisition step includes the front-rear direction force, and the front-rear direction force includes the wheel axle and the carriage provided with the wheel axle. It is a force in the front-rear direction generated in the member arranged between the members, the member is a member for supporting the axle box, and the front-rear direction is a direction along the traveling direction of the railroad vehicle. It is a feature.

FIG. 1A is a diagram showing a schematic example of a railway vehicle. FIG. 1B is a diagram showing an example of the configuration of the lower portion of the vehicle body of the railway vehicle. FIG. 2 is a diagram conceptually showing the directions of the main movements of the components of the railway vehicle. FIG. 3 is a diagram showing a first example of the functional configuration of the inspection device. FIG. 4 is a diagram showing an example of the hardware configuration of the inspection device. FIG. 5 is a diagram showing an example of the distribution of eigenvalues of the autocorrelation matrix. FIG. 6 is a flowchart illustrating a first example of processing in the inspection device. FIG. 7 is a diagram showing the curvature of the rail, the amount of deviation, and the amount of high and low deviation. FIG. 8 is a diagram showing a first example of time-series data of forward / backward force. FIG. 9 is a diagram showing a second example of time-series data of forward / backward force. FIG. 10 is a diagram showing a third example of time-series data of forward / backward force. FIG. 11 is a diagram showing an example of time-series data of the modified front shaft spring rigidity. FIG. 12 is a diagram showing a first example of time-series data of the modified shaft spring rigidity. FIG. 13 is a diagram showing a second example of time-series data of the corrected shaft spring rigidity. FIG. 14 is a diagram showing a third example of time-series data of the modified shaft spring rigidity. FIG. 15 is a diagram showing an example of the configuration of the inspection system. FIG. 16 is a diagram showing a first example of the functional configuration of the inspection device. FIG. 17 is a flowchart illustrating a second example of processing in the inspection device. FIG. 18 is a diagram showing a first example of the relationship between the restoring force and the displacement. FIG. 19 is a diagram showing a second example of the relationship between the restoring force and the displacement. FIG. 20 is a diagram showing a second example of the relationship between the restoring force and the displacement.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
(First Embodiment)
First, the first embodiment will be described.
<Outline of railway vehicle>
First, the railway vehicle illustrated in this embodiment will be described. FIG. 1A is a diagram showing a schematic example of a railway vehicle. FIG. 1B is a diagram showing an example of the configuration of the lower portion of the vehicle body of the railway vehicle. In addition, in FIGS. 1A and 1B, it is assumed that the railroad vehicle travels 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 30 (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 with a cross in ◯ indicate the direction from the front side to the back side of the paper.

As shown in FIG. 1A, 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 bogies with bolsters will be described as an example. In FIG. 1A, for convenience of notation, only one wheel 14a to 14d of the wheel sets 13a to 13d is shown, but as shown in FIG. 1B, a wheel is also provided on the other side of the wheel sets 13a to 13d (FIG. 1). In the example shown in, there are a total of 8 wheels). Further, the railroad vehicle has components other than the components shown in FIGS. 1A and 1B (components described in the equation of motion described later, etc.), but for convenience of notation, the components are shown in FIGS. 1A and 1B. Is omitted. Further, in FIG. 1B, only the bogie frame 16 in the bogie 12b is shown, but the bogie frame in the bogie 12a is also realized by the same one as shown in FIG. 1B. Further, FIG. 1B shows only the components ( axle boxes 17L, 17R, shaft springs 18L, 18R, shaft dampers 19L, 19R, etc.) of the bogie 12b with respect to the wheel sets 13d, but other components with respect to the wheel sets are also shown in FIG. 1B. It is realized by the same thing as shown.

Shaft boxes 17L and 17R are arranged on both sides of each wheel axle 13a to 13d in the direction along the y-axis. The bogie frame 16 and the axle boxes 17L and 17R are connected to each other by the axle box support device. In the example shown in FIG. 1B, the axle box support device has axle springs 18L, 18R and axle dampers 19L, 19R. The axle box support device is a device (suspension) arranged between the axle boxes 17L, 17R and the bogie frame 16. The axle box support device absorbs the vibration transmitted from the track 30 to the railway vehicle. Further, the axle box support device with respect to the bogie frame 16 of the axle boxes 17L and 17R so as to prevent the axle boxes 17L and 17R from moving in the direction along the x-axis and the direction along the y-axis with respect to the bogie frame 16. The axle boxes 17L and 17R are supported in a restricted position. The axle box support devices are arranged on both sides of each wheel axle 13a to 13d in the direction along the y-axis.

A pillow beam 21 is arranged above the bogie frame 16. Pillow springs 22L and 22R and a left-right moving damper 23 are arranged between the pillow beam 21 and the vehicle body 11. In this embodiment, it is assumed that the pillow spring is a commonly used air spring. In the following, the pillow springs 22L and 22R will be referred to as air springs 22L and 22R, but the pillow springs do not have to be air springs.
Here, in the present embodiment, the right side and the left side mean the right side and the left side in the traveling direction of the railway vehicle (positive direction of the x-axis), respectively. The axle box 17L, axle spring 18L, axle damper 19L, and air spring 22L are arranged on the left side of the railcar, and the axle box 17R, axle spring 18R, axle damper 19R, and air spring 22R are arranged on the right side of the rolling stock. ..
Since the railway vehicle itself can be realized by a known technique, detailed description thereof will be omitted here. Further, the trolley may be a bolsterless trolley.

When a railroad vehicle travels on the track 30, the acting force (creep force) between the wheels 14a to 14d and the track 30 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.

In the following explanation, the movement of the railroad vehicle in the vertical direction is referred to as vertical movement as necessary (see the double-headed arrow line along the z-axis in FIG. 2). The vertical direction is a direction perpendicular to the orbit 30. In the examples shown in FIGS. 1A and 1B, the vertical direction is a direction along the z-axis. Further, in the following description, the traveling direction of the railway vehicle is referred to as a front-rear direction as necessary, and the direction along the z-axis is referred to as a vertical direction as necessary. Further, a direction perpendicular to both the front-rear direction (traveling direction of the railroad vehicle) and the vertical direction (direction perpendicular to the track 30) is referred to as a left-right direction, if necessary.

Further, the motion of the railroad vehicle rotating around the x-axis is referred to as rolling as necessary (see the double-headed arrow line around the x-axis in FIG. 2), and the rotation with the x-axis as the rotation axis. The direction is referred to as the rolling direction as necessary. Further, the motion of the railroad vehicle rotating around the y-axis (the motion of the leading portion of the railroad vehicle swinging up and down) is called pitching as necessary (double arrow around the y-axis in FIG. 2). (See line), the rotation direction with the y-axis as the rotation axis is referred to as the pitching direction, if necessary. Further, the motion of the railroad vehicle rotating around the z-axis is referred to as yawing as necessary (see the double-headed arrow line around the z-axis in FIG. 2), and the rotation with the z-axis as the rotation axis. The direction is referred to as the yawing direction as necessary.

<Equation of motion of vertical movement and pitching of bogies 12a and 12b>
Next, the equations of motion for vertical movement and pitching of the carriages 12a and 12b will be described.
In each equation, the subscript i is a symbol for identifying the wheel sets 13a, 13b, 13c, 13d (i = 1, 2, 3, 4 correspond to the wheel sets 13a, 13b, 13c, 13d, respectively). ). Further, the subscript j is a symbol for identifying the carriages 12a and 12b (j = 1 and 2 correspond to the carriages 12a and 12b, respectively). Further, in each equation, it is assumed that the information of the railway vehicle (mass, dimensions, etc.) and the information of the rail (curvature, etc.) are given in advance as constants.

<< Equation of motion representing the vertical movement of trolleys 12a and 12b >>
The equation of motion representing the vertical movement of the carriages 12a and 12b is expressed by the equation (1).

Here, _{m t} is carriage 12a, the mass of 12b. z _{t, j} ... Is the vertical acceleration of the carriages 12a, 12b (in the equation, ... is attached above z _{t, j} (hereinafter, the same applies to other variables)). _FASzj ^L is the load received by the left air spring 22L. _FASzj ^R is the load received by the air spring 22R on the right side. k _{1 and i} are average values of the rigidity (spring constant) of the shaft springs 18L and 18R attached to the axle boxes 17L and 17R of the wheel sets 13a and 13c. i is 1 or 3. As described above, i = 1 represents the wheel set 13a, and i = 3 represents the wheel set 13c (hereinafter, the same applies to other variables).

Further, z _{t and j} are displacements of the carriages 12a and 12b in the vertical direction. j is 1 or 2. As described above, j = 1 represents the carriage 12a, and j = 2 represents the carriage 12b (hereinafter, the same applies to other variables). a represents 1/2 of the distance in the front-rear direction between the wheel sets 13a to 13b and 13c to 13d provided on the carriages 12a and 12b, respectively (the wheel sets 13a to 13b and 13c provided on the carriages 12a and 12b). The distance between ~ 13d is 2a). θ _{t and j} are the amount of rotation (angular displacement) of the carriages 12a and 12b in the pitching direction. z _{w and i} are vertical displacements of the wheel sets 13a and 13c. k _{1 and i + 1} are average values of the rigidity (spring constant) of the shaft springs 18L and 18R attached to the axle boxes 17L and 17R of the wheel sets 13b and 13d. As described above, i + 1 = 2 represents a wheel set 13b, and i + 1 = 4 represents a wheel set 13d (hereinafter, the same applies to other variables). z _{w and i + 1} are vertical displacements of the wheel sets 13b and 13d. z _{w, i} , z _{w, i + 1} can be obtained, for example, by time-integrating the acceleration detected by the acceleration sensor attached to the axle box.

Further, c ₁ is an average value of the damping constants of the shaft dampers 19L and 19R in the vertical direction. z _{t, j} · is the vertical velocity of the carriages 12a, 12b (in the equation, · is attached above z _{t, j} (hereinafter, the same applies to other variables)). z _{w, i} · are the velocities in the vertical direction of the wheel sets 13a, 13c. z _{w, i + 1} · are the velocities in the vertical direction of the wheel sets 13b and 13d. v is the traveling speed of the railway vehicle. _Ri is the radius of curvature of the rail at the positions of the wheel sets 13a and 13c. R _{i + 1} is the radius of curvature of the rail at the positions of the wheel sets 13b and 13d. φ _{rail and i} are cant angles of the rails at the positions of the wheel sets 13a and 13c. φ _{rail and i + 1} are cant angles of rails at positions of wheel sets 13b and 13d. g is the gravitational acceleration. z _{w, i} ·, z _{w, i + 1} · can be obtained, for example, by time-integrating the acceleration detected by the acceleration sensor attached to the axle box. z _{t, j} ... Are measured by, for example, an acceleration sensor attached to the carriages 12a and 12b. z _{t, j} ·, z _{t, j} can be obtained, for example, by time-integrating the acceleration detected by the acceleration sensors attached to the carriages 12a and 12b. c ₁ is given in advance as a constant. It is assumed that φ _{rail, i} , φ _{rail, and i + 1} have been measured in advance.

The left side of the equation (1) represents the inertial force in the vertical direction of the carriages 12a and 12b. The first and second terms on the right side of the equation (1) represent the loads received by the air springs 22L and 22R, respectively. The third and fourth terms on the right side of the equation (1) represent the average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction. The fifth term on the right side of the equation (1) represents the average value of the forces received by the left shaft dampers 19L and the right shaft dampers 19R arranged at intervals in the left-right direction. The sixth term on the right side of the equation (1) represents the centrifugal force received by the carriages 12a and 12b. The seventh term on the right side of the equation (1) is the gravity received by the carriages 12a and 12b.

<< Equation of motion representing pitching of trolleys 12a and 12b >>
The equation of motion representing the pitching of the carriages 12a and 12b is expressed by the following equation (2).

It _{and y} are moments of inertia of the carriages 12a and 12b in the pitching direction. It _{and y} shall be given in advance. θ _{t, j} ... Are angular accelerations of the carriages 12a and 12b in the pitching direction. a ₁ is trolley 12a, (carriage 12a represents a half of the distance in the longitudinal direction between the two axes dampers 19L arranged at a distance in the front-rear direction (19R) in each of 12b, back and forth in each of 12b distance in longitudinal direction between the two axes dampers 19L arranged at a distance in the direction (19R) is 2a _1). θ _{t, j} · are the angular velocities of the carriages 12a and 12b in the pitching direction. h ₁ is the distance between the center of the axle and the center of gravity of the carriages 12a and 12b in the vertical direction. F _Wx, ^{i L} is the longitudinal direction forces in the left wheel set 13a, 13c. F _{Wx and i} ^R are the front-rear directional forces on the right side of the wheel sets 13a and 13c. F _{Wx, i + 1} ^L are front-rear directional forces on the left side of the wheel sets 13b and 13d. F _{Wx, i + 1} ^R is a front-back force on the right side of the wheel sets 13b and 13d. F _{Wx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R are measured by a sensor attached to a member for supporting the axle box as described later.

The left side of equation (2) is the sum of the moments of force received by the bogies 12a and 12b during pitching. The first and second terms on the right side of the equation (2) are moments of force received from the shaft springs 18L and 18R in pitching. The third term on the right side of the equation (2) is the moment of force received from the shaft dampers 19L and 19R in pitching. The fourth term on the right side of the equation (2) is the moment of force (total value) received by the carriages 12a and 12b based on the front-rear direction force.

<Forward and backward force>
Here, the front-rear direction force will be described.
The in-phase component of the vertical creep force of one of the left and right wheels on one wheel set and the vertical creep force of the other wheel is a component corresponding to the braking force and the driving force. Therefore, it is preferable to determine the anteroposterior force so as to correspond to the opposite phase component of the longitudinal creep force. The anti-phase component of the vertical creep force is a component in which the vertical creep force of one of the left and right wheels on one wheel set and the vertical creep force of 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.

A specific example of the anteroposterior force when the anteroposterior force is determined so as to correspond to the opposite phase component of the longitudinal creep force will be described below.
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 the link. Rubber bushes are attached to both ends of this link. In this case, the front-rear force is a component in the front-rear direction of the load received by each of the two links attached to the left-right ends of one wheel set, which are opposite 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 front-rear 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.

Note that the load measured by the strain gauge attached to the link may include not only the components in the front-rear direction but also at least one of the components in the left-right direction and 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, by attaching one strain gauge to each link, it is possible to obtain a measured value of the anteroposterior force having practically required accuracy. 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. In this way, the accuracy of the measured value of the front-rear force can be improved.

When the axle box support device is an axle beam type axle box support device, the axle box support device is provided with 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 axle beam on the bogie frame side. In this case, the front-rear force is a component of the front-rear direction of the load received by each of the two shaft beams attached to the left-right ends of one wheel set, which are opposite 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 distortion in the left-right direction is canceled. By using the measured values of these strain gauges to derive the anteroposterior component of the load received by 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 front-rear 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.

Note that 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 longitudinal force having practically required accuracy without attaching a strain gauge so as to cancel the load of the component in the vertical direction received by the shaft beam. In this way, the measured anteroposterior force may include components other than the anteroposterior component, and three or more strain gauges so as to cancel the vertical distortion in addition to the horizontal distortion. May be attached to each shaft beam. In this way, the accuracy of the measured value of the front-rear 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 in the front-rear direction of the load received by each of the two leaf springs attached to the left-right ends of one wheel set, which are in opposite phases to each other. Further, depending on 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 distortion in the horizontal 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 front-rear 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 front-rear direction force has been described by taking as an example the case where the type of 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 axle beam type, and the leaf spring type. As with the monolink type, the shaft beam type, and the leaf spring type, the front-rear direction force can be determined according to the type of the axle box support device.

<Calculation formula for deriving the rigidity (spring constant) k ₁ of the shaft springs 18L and 18R>
Next, a calculation formula for deriving the rigidity (spring constant) k ₁ of the shaft springs 18L and 18R will be described. The calculation formula for deriving the rigidity (spring constant) k ₁ of the shaft springs 18L and 18R is derived using the formulas (1) and (2). Equations (1) and (2) are equations of motion for vertical movement of the carriages 12a and 12b and equations of motion for pitching the carriages 12a and 12b.

First, the left side and the right side of the formula (2) divided by a (1/2 of the distance between the wheel sets 13a to 13b and 13c to 13d provided on the bogies 12a and 12b in the front-rear direction) are obtained. , Subtract from the left and right sides of equation (1) (formula (1)-formula (2) ÷ a). The left side of the equation thus obtained is transferred to the right side. In the equation thus obtained, "-k _{1, i} (z _{t, j-} aθ _{t, j-} z _{w, i} )" on the right side of equation (1) and "-k _{1, i} (z _{t, j-} aθ _{t, j-} z _{w, i} )" on the right side of equation (2) The value obtained by dividing "ak _{1, i} (z _{t, j-} aθ _{t, j-} z _{w, i} )" by -a ("-{ak _{1, i} (z _{t, j-} aθ _{t, j-} z _{w, i} )" _i )} ÷ a ") and the sum is transferred to the left side. Then, the following equation (3) is obtained.

In equation (3), the average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the front wheels ( wheel sets 13a, 13c) provided on the bogies 12a and 12b is calculated. It is an equation to represent. The fifth term on the right side of the equation (3) is a centrifugal force received by the bogies 12a and 12b, and is therefore unnecessary unless the railroad vehicle travels on a curved track.

Next, the left and right sides of the equation (2) divided by a (1/2 of the distance between the wheel sets 13a to 13b and 13c to 13d provided on the carriages 12a and 12b in the front-rear direction) are divided into the left and right sides. Add to the left and right sides of equation (1), respectively (formula (1) + equation (2) ÷ a). The left side of the equation thus obtained is transferred to the right side. In the equation thus obtained, "-k _{1, i + 1} (z _{t, j} + aθ _{t, j-} z _{w, i + 1} )" on the right side of equation ( ₁ ) and the right side of equation (2) The value obtained by dividing "-ak _{1, i + 1} (z _{t, j} + aθ _{t, j-} z _{w, i + 1} )" by a ("-{ak _{1, i + 1} (z _{t, j} + aθ _{t, j-} z _{w, i + 1)"} )} ÷ a ") and the sum is transferred to the left side. Then, the following equation (4) is obtained.

In equation (4), the average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the rear wheels (wheel sets 13b, 13d) provided on the carriages 12a and 12b. Is an equation that represents. The fifth term on the right side of the equation (4) is a term that is unnecessary unless the railroad vehicle travels on a curved track because it is the centrifugal force received by the bogies 12a and 12b.

Here, the load F _ASzj ^L received by the left air spring 22L provided on the carriages 12a and 12b and the load F _ASzj ^R received by the right air spring 22R provided on the carriages 12a and 12b are as follows. It is expressed by the equations (5) and (6).

Here, _Aj ^L is the pressure receiving area of the left air spring 22L provided on the carriages 12a and 12b. _Pj ^L is the internal pressure of the left air spring 22L provided on the carriages 12a and 12b. Pat is atmospheric pressure. b ₂ represents 1/2 of the distance between the air springs 22L and 22R arranged in the left-right direction in the left-right direction (the distance between the air springs 22L and 22R arranged in the left-right direction in the left-right direction). 2b ₂ ). y _b is the displacement of the vehicle body 11 in the left-right direction. dy _b is the amount of eccentricity in the left-right direction of the center of gravity of the vehicle body 11. 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). dx _b is the amount of eccentricity in the front-rear direction of the center of gravity of the vehicle body 11. _mb is the mass of the vehicle body 11. A _j ^R is the pressure receiving area of the right air spring 22R provided on the carriages 12a and 12b. _Pj ^R is the internal pressure of the right air spring 22R provided on the carriages 12a and 12b. Further, in the equations (5) and (6), the symbol with-under the + indicates that + is adopted for the equation for the carriage 12a and-is adopted for the equation for the carriage 12b. .. _Pj ^L and _Pj ^R are measured by a sensor that detects the internal pressure of the air springs 22L and 22R.

Receiving area _A ^j L · _A ^{j R} of the carriage 12a, the left and right are provided on 12b air springs 22L · 22R, respectively, the following equation (7) is expressed by equation (8).

Here, z _ASj ^L is a displacement of the left air spring 22L provided on the carriages 12a and 12b in the vertical direction. dA / dz is the rate of change (change amount per unit length) of the effective pressure receiving area of the air springs 22L and 22R in the vertical direction. A ₀ is the effective pressure receiving area of the air springs 22L and 22R. z _ASj ^R is the vertical displacement of the right air spring 22R provided on the carriages 12a and 12b. dA / dz is given in advance as a constant. A ₀ is given in advance as an initial value. Further, z _ASj ^R and z _ASj ^L are measured by a sensor that detects the displacement of the air springs 22L and 22R.

As described above, in the equations (3) and (4), the variables other than θ _{t, j} , θ _{t, j} ·, θ _{t, j} ··· are values given in advance or measured values. Therefore, if θ _{t, j} , θ _{t, j} ·, θ _{t, j} · · are derived, the rigidity (spring constant) of the shaft springs 18L and 18R is k ₁ (k) according to the equations (3) and (4). _{1, i} , k _{1, i + 1} ) can be derived. In the following description, the average values k _{1, i} of the rigidity (spring constant) of the shaft springs 18L and 18R attached to the axle boxes 17L and 17R of the axles 13a and 13c, and the axle boxes 17L and 17R of the axles 13b and 13d. The average value k _{1, i + 1} of the rigidity (spring constant) of the attached shaft springs 18L and 18R is referred to as the shaft spring rigidity, if necessary.

<< Derivation of θ _{t, j} , θ _{t, j} ·, θ _{t, j} · · >>
F _{Wx, i} ^L (front-rear direction force on the left side of the front wheels ( wheel sets 13a, 13c) of the bogies 12a, 12b) and F _{Wx, i} ^R (front-rear direction on the right side of the front wheels ( wheel sets 13a, 13c) of the bogies 12a, 12b) The sum (= F _{Wx, i} ^L + F _{Wx, i} ^R ) with the force) is expressed by the following equation (9). Further, the F _{Wx, i + 1} ^L (front-rear direction force on the left side of the rear wheels (wheel sets 13b, 13d) of the bogies 12a, 12b) and the F _{Wx, i + 1} ^R (rear wheels (wheel sets 13b, 13d) of the bogies 12a, 12b). The sum (= F _{Wx, i + 1} ^L + F _{Wx, i + 1} ^R ) with the front-back force on the right side is expressed by the following equation (10). Therefore, the following equation (11) can be obtained from the equations (9) and (10).

Here, K _Wx is a spring constant in the front-rear direction of the axle box support device. x _{t and j} are displacements of the carriages 12a and 12b in the front-rear direction. C _Wx is a damping constant in the left-right direction of the axle box support device. x _{t, j} · are the speeds of the carriages 12a and 12b in the front-rear direction. θ _{t, j} · are the angular velocities of the carriages 12a and 12b in the pitching direction. K _Wx and C _Wx are given in advance as constants.
By solving Eq. (11), θ _{t and j} can be obtained as solutions to ordinary differential equations. In _addition, θ _{t, j} · and θ _{t, j} ·· is derived by differentiating the θ _{t, j} time.

<< How to derive z _ASj ^R and z _ASj ^L by calculation >>
The z _ASj ^L and z _ASj ^R shown in the equations (7) and (8) can also be calculated by the following equations (12) and (13), respectively.

Here, z _b is the displacement of the vehicle body 11 in the vertical direction. φ _b is the amount of rotation (angular displacement) of the vehicle body 11 in the rolling direction. θ _b is the amount of rotation (angular displacement) of the vehicle body 11 in the pitching direction. φ _tj is the amount of rotation (angular displacement) of the carriages 12a and 12b in the rolling direction. Further, in the equations (12) and (13), the symbol with + under-indicates that-is adopted for the equation for the carriage 12a and + is adopted for the equation for the carriage 12b. .. z _b is obtained by time-integrating the acceleration detected by the acceleration sensor attached to the vehicle body 11.

θ _b (the amount of rotation (angular displacement) of the vehicle body 11 in the pitching direction) is derived as follows, for example. First, as described in Patent Document 2, φ _b (the amount of rotation (angular displacement) of the vehicle body 11 in the rolling direction), ψ _b · (angular velocity of the vehicle body 11 in the yawing direction), and ψ _b (vehicle body 11). The amount of rotation (angular displacement) in the yawing direction of The contents described in Patent Document 2 are incorporated herein by reference. Then, θ _b (the amount of rotation (angular displacement) of the vehicle body 11 in the pitching direction) is derived based on the equation of motion representing the pitching of the vehicle body 11 shown in the following equation (14).

Here, I _{b and y} are moments of inertia of the vehicle body 11 in the pitching direction. θ _b ... Is the angular acceleration of the vehicle body 11 in the pitching direction. h ₁₄ is the distance between the position of the center of gravity of the vehicle body 11 and the position of the center of gravity of the yaw damper. c ₀ is a damping constant in the front-rear direction of the yaw damper. θ _b · is the angular velocity of the vehicle body 11 in the pitching direction. k ″ ₂ is the spring constant of the air springs 22L and 22R in the front-rear direction. c ₀ is a damping constant in the front-rear direction of the yaw damper. c ₀ and k ″ ₂ are given in advance as constants.

<Modified autoregressive model>
It is assumed that the time-series data of the physical quantity is not stable, and the time-series data of the physical quantity contains noise components other than the essential components. It is possible to remove the noise component of the time series data of the physical quantity by using a low-pass filter or a band-pass filter, but it is not easy to set the cutoff frequency.

Therefore, the present inventors devised a model modified from the autoregressive model (AR (Auto-regressive) model) as a model for extracting the essential signal component of the physical quantity. Then, the present inventors have come up with the idea of extracting the essential signal component from the signal of the physical quantity by using this model. 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. The modified autoregressive model itself is described in Patent Document 3. The contents described in Patent Document 3 are incorporated herein by reference.

Let y _k be the value of the time series data y of the physical quantity at the time k (1 ≦ k ≦ M). In the present embodiment, the physical quantities are the shaft spring rigidity k _{1, i} and k _{1, i + 1} .

M is a number indicating up to what time the time-series data y of the physical quantity includes the data, and is preset. 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 (15). As shown in the equation (15), 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 set 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) and the coefficient α _l with respect to the actual value. In addition, y ^ _k is expressed by adding ^ on top of y _{k in} the equation (15).

Α in Eq. (16) 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.

Conditions for the square error of the prediction value y ^ _k of the physical quantity and the value y _k at time k by autoregressive model minimizes equation is given by the following equation (16).

From equation (16), the relationship of equation (17) below holds.

Further, by modifying the equation (18) (matrix notation), the following equation (18) can be obtained.

R _{jl in the} equation (18) is called the autocorrelation of the data y, and is a value defined by the following equation (19). | Jl | at this time is called a time difference.

The predicted value y ^ _k of the physical quantity at the time k by autoregressive model, from the condition of minimizing the value y _k of the physical quantity, of the error at time k corresponding to the predicted value y ^ _k, the following equation (20) The Yule-Walker equation is obtained. The constant vector on the left side in the equation (20) 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. (20) will be referred to as an autocorrelation vector, if necessary. The coefficient matrix on the right side in Eq. (20) 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. (20) 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 (20) is referred to as an autocorrelation matrix R as in the following equation (21).

Generally, when obtaining the coefficient of the autoregressive model, the method of solving Eq. (20) with respect to the coefficient α is used. On the other hand, when obtaining the coefficients of the modified autoregressive model, a part of the eigenvalues of the autocorrelation matrix R is used to reduce the influence of noise contained in the data y and emphasize the essential signal components. The autocorrelation matrix R is rewritten so as to (increase the SN ratio).

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 Eq. (22) below.

The diagonal matrix Σ of the equation (22) is a matrix in which the diagonal component is an eigenvalue of the autocorrelation matrix R, as shown in the following equation (23). 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 vectors of the orthogonal matrix U be u ₁ , u ₂ , ..., U _m . There is a correspondence that the eigenvalue of the autocorrelation matrix R with respect to the eigenvector u _j is σ _JJ . The eigenvalues of the autocorrelation matrix R are variables that reflect the intensity of the components 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 mathematical formula. To do. Of the eigenvalues of the autocorrelation matrix R shown in equation (23), s eigenvalues are used to define the matrix R'as in equation (24) below. s is a number greater than or equal to 1 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.

(24) The matrix U _s in formula is a m × s matrix constituted by (22) s number of columns of the vector from the left of the orthogonal matrix U of (eigenvectors corresponding to eigenvalues used). Further, the _U ^{s T} in (24), a transposed matrix of _{U s.} U _s ^T is a s × m matrix composed of s rows component vectors from the top of the matrix ^{U T} of equation (22). The matrix Σ _s in the equation (24) 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 (22).
If the matrix Σ _s and the matrix _Us are expressed by the matrix components, the following equation (25) is obtained.

By using the matrix R'instead of the autocorrelation matrix R, the relational expression of the equation (20) is rewritten as the following equation (26).

By modifying the equation (26), the following equation (27) can be obtained as an equation for obtaining the coefficient α. The "modified autoregressive model" is a model that calculates the predicted value y ^ _k of the physical quantity at time k by the equation (15) using the coefficient α obtained by the equation (27).

Here, the case where the values of σ ₁₁ , σ ₂₂ , ..., Σ _mm , which are the 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.

Equation (27) is an equation used to determine the coefficients of the modified autoregressive model. (27) of the matrix U _s is a partial matrix of the orthogonal matrix U obtained by singular value decomposition of the autocorrelation matrix R, column eigenvector corresponding to the eigenvalue which is used to determine the coefficients of the correction autoregressive model It is a matrix (third matrix) as a component vector. Further, the matrix Σ _s of Eq. (27) 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 autocorrelation model are diagonal components. It is a matrix (second matrix). (27) is a matrix _{U s Σ s U s} ^T of the equation is a matrix derived from a matrix sigma _s and the matrix _{U s} (first matrix).

By calculating the right side of equation (27), the coefficient α of the modified autoregressive model can be obtained. The example of the method of deriving the coefficient α of the modified autoregressive model has been described above.
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 eigenvalues extracted from the autocorrelation matrix R shown in equation (23) can be determined, for example, from the distribution of the eigenvalues of the autocorrelation matrix R.
In the present embodiment, the physical quantities in the description of the modified autoregressive model described above are the shaft spring rigidity k _{1, i} and k _{1, i + 1} . The values of the shaft spring rigidity k _{1, i} and k _{1, i + 1} vary depending on the state of the railway vehicle. Therefore, first, the railroad vehicle is run on the track 30 to obtain data y for the shaft spring rigidity k _{1, i} and k _{1, i + 1} . For each of the obtained data y, the autocorrelation matrix R is obtained using the equations (19) and (21). The eigenvalues of the autocorrelation matrix R are obtained by performing the singular value decomposition represented by Eq. (22) on the autocorrelation matrix R.

FIG. 5 is a diagram showing an example of the distribution of the eigenvalues of the autocorrelation matrix R. In FIG. 5, 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 shaft spring stiffness k _{1 and 1} are rearranged in ascending order and plotted. The horizontal axis of FIG. 5 is an index of eigenvalues, and the vertical axis represents the value of eigenvalues in common logarithm. Here, m of equation (15) was set to 1500. The sampling period was set to 0.002 s.

In the example shown in FIG. 5, there is one eigenvalue with a significantly higher value than the others. Although not shown, the eigenvalues of all the shaft spring stiffnesses k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ have significantly higher values than the others, as in FIG. There was one. From this, for example, 1 can be adopted as the number s of the eigenvalues extracted from the autocorrelation matrix R shown in the equation (23). In addition, for example, an eigenvalue exceeding the threshold value can be extracted.

The coefficient α of the modified autoregressive model is determined as follows.
Based on the data y of the shaft spring rigidity k _{1, i} , k _{1, i + 1} , and the preset numbers M, m, the autocorrelation matrix R is calculated using the equations (19) and (21). Generate.

Next, the orthogonal matrix U and the diagonal matrix Σ of Eq. (22) are derived by singular value decomposition of the autocorrelation matrix R, and the eigenvalues σ ₁₁ to σ _mm of the autocorrelation matrix R are derived from the diagonal matrix Σ. To do.
Next, of the plurality of eigenvalues σ ₁₁ to σ _mm of the autocorrelation matrix R, s predetermined eigenvalues σ ₁₁ to σ _ss are used to obtain the coefficient α of the modified autoregressive model. Select as the eigenvalue of R.
Next, based on the data y of the axial spring stiffness k _{1, i} , k _{1, i + 1} , the eigenvalues σ ₁₁ to σ _ss, and the orthogonal matrix U obtained by the singular value decomposition of the autocorrelation matrix R, ( The coefficient α of the modified autoregressive model is determined using the equation 27).

<Configuration of inspection device 300>
FIG. 3 is a diagram showing an example of a functional configuration of the inspection device 300. FIG. 4 is a diagram showing an example of the hardware configuration of the inspection device 300.

In FIG. 3, the inspection device 300 has a data acquisition unit 301, a shaft spring state detection unit 302, a determination unit 303, and an output unit 304 as its functions.
In FIG. 4, the inspection device 300 includes a CPU 401, a main storage device 402, an auxiliary storage device 403, a communication circuit 404, a signal processing circuit 405, an image processing circuit 406, an I / F circuit 407, a user interface 408, a display 409, and a bus. It has 410.

The CPU 401 controls the entire inspection device 300 in an integrated manner. The CPU 401 uses the main storage device 402 as a work area to execute a program stored in the auxiliary storage device 403. The main storage device 402 temporarily stores data. The auxiliary storage device 403 stores various data in addition to the program executed by the CPU 401.

The communication circuit 404 is a circuit for communicating with the outside of the inspection device 300. The communication circuit 404 receives, for example, information on the measured value of the front-rear force, which will be described later. The communication circuit 404 may perform wireless communication or wired communication with the outside of the inspection device 300. The communication circuit 404 is connected to an antenna provided on a railroad vehicle when performing wireless communication.

The signal processing circuit 405 performs various signal processing on the signal received by the communication circuit 404 and the signal input according to the control by the CPU 401. The data acquisition unit 301 is realized by using, for example, a CPU 401, a communication circuit 404, and a signal processing circuit 405. Further, the shaft spring state detection unit 302 and the determination unit 303 are realized by using, for example, a CPU 401 and a signal processing circuit 405.

The image processing circuit 406 performs various image processing on the signal input under the control of the CPU 401. The signal after this image processing is performed is output to the display 409.
The user interface 408 is a part in which the operator gives an instruction to the inspection device 300. The user interface 408 includes, for example, buttons, switches, dials, and the like. Further, the user interface 408 may have a graphical user interface using the display 409.

The display 409 displays an image based on the signal output from the image processing circuit 406. The I / F circuit 407 exchanges data with a device connected to the I / F circuit 407. FIG. 4 shows a user interface 408 and a display 409 as devices connected to the I / F circuit 407. However, the device connected to the I / F circuit 407 is not limited to these. For example, a portable storage medium may be connected to the I / F circuit 407. Further, at least a part of the user interface 408 and the display 409 may be outside the inspection device 300.
The output unit 303 is realized, for example, by using at least one of the communication circuit 404 and the signal processing circuit 405, the image processing circuit 406, the I / F circuit 407, and the display 409.

The CPU 401, the main storage device 402, the auxiliary storage device 403, the signal processing circuit 405, the image processing circuit 406, and the I / F circuit 407 are connected to the bus 410. Communication between these components takes place via bus 410. Further, the hardware of the inspection device 300 is not limited to that shown in FIG. 4 as long as the functions of the inspection device 300 described later can be realized.

<< Data acquisition unit 301 >>
The data acquisition unit 301 acquires the measured values for the railway vehicle to be inspected and is necessary for the calculation of the equations (3) and (4) at a predetermined sampling cycle. As a result, time series data of each measured value can be obtained. In the present embodiment, for example, the longitudinal forces F _{Wx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R , air springs 22 ^L , 22 ^R internal pressures P _j ^L , P _j ^R , trolley. Displacements of the left and right air springs 22L and 22R provided on 12a and 12b in the vertical direction z _ASj ^L , z _ASj ^R , vertical acceleration z _b of the vehicle body 11 and vertical directions of the carriages 12a and 12b. The acceleration z _{t, j} ..., the vertical acceleration z _{w, i} ..., z _{w, i + 1} ... of the wheel shafts 13a to 13b, 13c to 13d, and the traveling speed v of the railroad vehicle are obtained as measured values.

The data acquisition unit 301 derives the displacement z _b of the vehicle body 11 in the vertical direction by time-integrating the measured values of the acceleration z _b ... In the vertical direction of the vehicle body 11. Data acquisition unit 301, carriage 12a, vertical acceleration _{z t} of _12b, by integrating the measured values of _j · · time, vertical speed _{z t} of the truck _{12A12b, j} ·, displacement _{z t,} the _j Derived. The data acquisition unit 301 time-integrates the measured values of the vertical accelerations zw _{, i} ..., zw _{, i + 1} ... Of the wheel sets 13a to 13b and 13c to 13d, so that the wheel sets 13a to 13b and 13c to 13d The vertical velocities z _{w, i} ·, z _{w, i + 1} ·, displacement z _{w, i} , z _{w, i + 1} are derived.
In the following description, various variables ( _{FWx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R , P _j ^L , P _j ^R) acquired and derived by the data acquisition unit 301. , Z _ASj ^L , z _ASj ^R , z _b , z _{t, j} ..., z _{t, j} ·, z _{t, j} , z _{w, i} ·, z _{w, i + 1} ·, z _{w, i} , z _{w, i + 1} , v) will be referred to as measurement data, if necessary.

<< Shaft spring state detector 302 >>
The shaft spring state detection unit 302 derives the rigidity (spring constant) k ₁ (k _{1, i} , k _{1, i + 1} ) of the shaft springs 18L and 18R using the measurement data obtained by the data acquisition unit 301. To do. In the present embodiment, the shaft spring state detection unit 302 has a shaft spring rigidity lead-out unit 302a and a frequency component adjusting unit 302b.
<<< Shaft spring rigidity lead-out unit 302a >>>
The shaft spring rigidity deriving unit 302a uses the measurement data obtained by the data acquisition unit 301 to perform the calculations of equations (3) and (4), whereby the shaft spring rigidity k _{1, i} , k _{1, i + 1} Is derived at a predetermined sampling period.

Here, when calculating k _{1, i} and k _{1, i + 1} using the equations (3) and (4), both sides of the equations (3) and (4) are changed to the equation (3), respectively. It is necessary to divide by 2 (z _{t, j-} aθ _{t, j-} z _{w, i} ) on the left side of, and 2 (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) on the left side of equation (4). That is, in the equations for obtaining k _{1, i} and k _{1, i + 1} derived in this way, (z _{t, j −} aθ _{t, j −} z _{w, i} ) and ( _i ) on the left side of equation (3), respectively. The denominator is (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) on the left side of equation 4). In the following description, it is located in the denominator of the equation for obtaining k _{1, i} , k _{1, i + 1} in this way (z _{t, j} −aθ _{t, j −} z _{w, i} ), (z _{t, j} + aθ _{t). , J-} z _{w, i + 1} ) is called the denominator of the formula for obtaining k _{1, i} , k _{1, i + 1} as needed.

In this case, the values of the denominators in Eqs. (3) and (4) are not stable, and the value of the denominator straddles "0" and has both a positive value and a negative value (that is, vibration). To do) is assumed. In this case, when the denominator values of Eqs. (3) and (4) are "0", the so-called zero division calculation is performed, so that the values of the shaft spring rigidity k _{1, i} and k _{1, i + 1} are extremely large. Or become smaller. When calculating the shaft spring stiffness k _{1, i} , k _{1, i + 1} as continuous values (when not discretizing (numerical analysis)), the values of the shaft spring stiffness k _{1, i} , k _{1, i + 1} diverge. To do. The shaft spring rigidity k _{1, i} and k _{1, i + 1} are proportional constants obtained by dividing the load when a load is applied to the shaft springs 18L and 18R by the elongation, so that the elongation originally approaches "0". Even if it does, it has the property of converging to a constant value. However, the data used in the calculation includes errors (measurement error and numerical error). Therefore, the present inventors considered that when the elongation is close to "0", the S / N ratio of the data used in the calculation decreases, and such a phenomenon occurs. It is considered that the original information is largely lost in the values of the shaft spring rigidity k _{1, i} and k _{1, i + 1} which are extremely large or small. From this, the present inventors have invalidated the values of the shaft spring stiffnesses k _{1, i} and k _{1, i + 1} derived as described above to a certain extent, and then used them as time-series data. It was thought that the accuracy of the shaft spring rigidity could be improved by reducing the component (noise). Therefore, in the present embodiment, when the values of the shaft spring rigidity k _{1, i} and k _{1, i + 1} derived as described above exceed the upper limit value, the shaft spring rigidity deriving unit 302a has the shaft spring rigidity. The values of k _{1, i} and k _{1, i + 1} are set as the upper limit value, and when the value is lower than the lower limit value, the values of the shaft spring rigidity k _{1, i} and k _{1, i + 1} are set as the lower limit value. By doing so, the range of the shaft spring rigidity k _{1, i} and k _{1, i + 1} is limited. In the present embodiment, the coefficients q ₁ and q ₂ are real numbers of 0 or more, and the range of the shaft spring rigidity k _{1, i} , k _{1, i + 1} is limited to the sections shown in the following equations (28a) and (28b). The upper limit value (= q ₂ × k _{1, i} −) and the lower limit value (= q ₁ × k _{1, i} −) are set so as to be performed.

k _{1, i} -is the average value of the spring constants of the normal shaft springs 18L and 18R, and for example, a design value can be used (in the formula,-is added above k (hereinafter, other). The same applies to variables)). In the following description, the average value of the spring constants of the normal shaft springs 18L and 18R will be referred to as a reference value of the shaft spring rigidity, if necessary. Further, for example, "0.5" and "1.5" can be preset as the coefficients q ₁ and q ₂ , respectively (q ₁ = 0.5, q ₂ = 1.5). In the following description, the shaft spring rigidity derived by the shaft spring rigidity lead-out unit 302a by limiting the range to the section shown in the equation (28a) and (28b) is referred to as a modified front shaft spring rigidity, if necessary. ..

<<< Frequency component adjustment unit 302b >>>
The frequency component adjusting unit 302b performs the following processing using the value y _k of the modified front shaft spring rigidity data y at the time k.
First, the frequency component adjusting unit 302b uses the equations (19) and (21) to form an autocorrelation matrix based on the data y of the modified front shaft spring rigidity and the preset numbers M and m. Generate R.

Next, the frequency component adjusting unit 302b derives the orthogonal matrix U and the diagonal matrix Σ of the equation (22) by decomposing the autocorrelation matrix R into singular values, and the eigenvalues of the autocorrelation matrix R are derived from the diagonal matrix Σ. Derivation of σ ₁₁ to σ _mm .
Next, the frequency component adjusting unit 302b has s eigenvalues σ ₁₁ to σ _ss out of a plurality of eigenvalues σ ₁₁ to σ _mm of the autocorrelation matrix R (one eigenvalue σ _{11 in} the example shown in FIG. 5). Is selected as the eigenvalue of the autocorrelation matrix R used to obtain the coefficient α of the modified autoregressive model.
Next, the frequency component adjusting unit 302b is based on the modified front shaft spring rigidity data y, the eigenvalues σ ₁₁ to σ _ss, and the orthogonal matrix U obtained by the singular value decomposition of the autocorrelation matrix R. The coefficient α of the modified autoregressive model is determined using the equation 27).

Then, the frequency component adjusting unit 302b is based on the coefficient α of the modified autoregressive model and the modified front shaft spring rigidity data y, according to the equation (15), at the time k of the modified front shaft spring rigidity data y. The predicted value y ^ _k is derived. In this way, the high frequency component of the modified front shaft spring rigidity data y is reduced (the low frequency component is extracted), and the modified front shaft spring rigidity data y is corrected. In the present embodiment, the frequency component adjusting unit 302b derives the predicted value y ^ _k of the modified front shaft spring rigidity data y derived in this way at time _k at a predetermined sampling cycle. In the following description, the predicted value y ^ _k of the modified front shaft spring rigidity data y at time k is referred to as the modified rear shaft spring rigidity, if necessary.

<< Judgment unit 303 >>
The determination unit 303 determines the rigidity (spring constant) of the shaft springs 18L and 18R based on the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected shaft spring rigidity) derived by the shaft spring state detection unit 302. ) Is determined to be present. For example, the determination unit 303 has the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected shaft spring rigidity) derived by the shaft spring state detection unit 302, and the normal shaft spring rigidity k _{1, i} −. , K _{1, i + 1} −, and the presence or absence of abnormality in the rigidity (spring constant) of the shaft springs 18L and 18R is determined. For example, the determination unit 303 has the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected shaft spring rigidity) derived by the shaft spring state detection unit 302, and the normal shaft spring rigidity k _{1, i} −. , K _{1, i + 1-If} the absolute value of the difference exceeds the threshold value, it is determined that the rigidity (spring constant) of the shaft springs 18L and 18R is abnormal, and if not, the shaft spring 18L, It is determined that the rigidity (spring constant) of 18R is not abnormal.

The determination unit 303 can make the above determination regardless of the traveling position of the railway vehicle. However, the determination unit 303 may make the above determination by limiting the traveling position of the railway vehicle.
For example, the determination unit 303 may make the above determination only when the railway vehicle is traveling on a straight track, or may perform the above determination only when the railway vehicle is traveling on a curved track. You may. Further, the determination unit 303 determines whether or not there is an abnormality in the left shaft spring 18L when the railroad vehicle is traveling on a clockwise curved track in the traveling direction, and whether or not there is an abnormality in the right shaft spring 18R. Does not have to be determined. Further, the determination unit 303 determines whether or not there is an abnormality in the right shaft spring 18R when the railroad vehicle is traveling on a counterclockwise curved track in the traveling direction, and whether or not there is an abnormality in the left shaft spring 18L. Does not have to be determined.

For example, before operating the inspection device 300 of the present embodiment, the shaft spring rigidity k ₁ derived by the shaft spring state detection unit 302 by running a railroad vehicle of the shaft springs 18L and 18R in various states on a trial basis. _{, I} , k _{1, i + 1} (corrected shaft spring rigidity) is acquired. Then, the axial spring rigidity _{k 1} obtained, i, _{k 1, i + 1} from the magnitude of the value of (corrected axial spring stiffness), the axial spring stiffness _{k 1,} i, _{k 1, i + 1} (after correction shaft A section in which the value of spring rigidity) changes remarkably when the shaft springs 18L and 18R are abnormal is specified. The section specified in this way can be determined in advance as a section for determining the presence or absence of abnormality in the rigidity (spring constant) of the shaft springs 18L and 18R. The traveling position of the rolling stock at the time when the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected shaft spring rigidity) is derived is determined by using, for example, GPS (Global Positioning System). It is obtained by detecting the position of. Further, the traveling position of the railway vehicle at the relevant time may be obtained from the integrated value of the speeds of the railway vehicle at each time.

<< Output section 304 >>
The output unit 304 outputs information based on the result determined by the determination unit 303. Specifically, when the determination unit 303 determines that at least one of the rigidity (spring constant) of the shaft springs 18L and 18R is abnormal, the output unit 304 outputs information indicating that fact. At this time, the output unit 304 also outputs information for identifying the shaft spring whose rigidity (spring constant) is determined to be abnormal. The output unit 304 may also output information indicating the traveling position of the railway vehicle at the timing when the rigidity (spring constant) of the shaft spring is determined to be abnormal. Further, when the determination unit 303 determines that all of the shaft springs 18L and 18R are not abnormal, the output unit 304 may output information indicating that fact. 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 of the inspection device 300 can be adopted.

<Operation flowchart>
Next, an example of processing in the inspection device 300 of the present embodiment will be described with reference to the flowchart of FIG.
First, in step S601, the inspection device 300 waits until the railroad vehicle to be inspected enters the inspection section. When the railroad vehicle to be inspected enters the inspection section, the process proceeds to step S602. When the process proceeds to step S602, the inspection device 300 waits until the predetermined sampling cycle (start time) arrives. When the predetermined sampling cycle (start time) arrives, the process proceeds to step S603. When the process proceeds to step S603, the data acquisition unit 301 determines the measurement data ( _{FWx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R , P _j ^L , P _j ^R , z _ASj ^L , z _ASj ^R , z _b , z _{t, j} ..., z _{t, j} ·, z _{t, j} , z _{w, i} ·, z _{w, i + 1} ·, z _{w, i} , z _{w, i + 1} , v) is acquired.

Next, in step S604, the shaft spring rigidity deriving unit 302a uses the measurement data acquired in step S603 to perform calculations using Eqs. (3) and (4), whereby the shaft spring rigidity k _{1 , I} , k _{1, i + 1} (corrected front axle spring rigidity) is derived. At this time, when the shaft spring rigidity k _{1, i} , k _{1, i + 1} exceeds the upper limit value (= q ₂ × k _{1, i} −), the measurement data derivation unit 302a has the shaft spring rigidity k _{1, i} , k. _{1, i + 1} is changed to the upper limit value. Further, when the shaft spring rigidity k _{1, i} , k _{1, i + 1} is lower than the lower limit value (= q ₁ × k _{1, i} −), the measurement data derivation unit 302a has the shaft spring rigidity k _{1, i} , k _{1 , I + 1} is changed to the lower limit value.

Next, in step S605, the frequency component adjusting unit 302b generates an autocorrelation matrix R based on the modified front shaft spring rigidity data y and the preset numbers M and m. The frequency component adjusting unit 302b derives the eigenvalues σ ₁₁ to σ _ss of the autocorrelation matrix R based on the result of singular value decomposition of the autocorrelation matrix R. The frequency component adjusting unit 302b is a modified autoregressive model based on the modified front shaft spring rigidity data y, the eigenvalues σ ₁₁ to σ _ss, and the orthogonal matrix U obtained by singular value decomposition of the autocorrelation matrix R. Determine the coefficient α. Then, the frequency component adjusting unit 302b calculates the predicted value y ^ _k at the time k of the modified front shaft spring rigidity data y based on the coefficient α of the modified autoregressive model and the modified front shaft spring rigidity data y. , Derived as the modified shaft spring rigidity. The process of step S605 is executed when the value of each time of the modified front shaft spring rigidity data is m (for example, 1500) or more. If the value of each time of the modified front shaft spring rigidity data is not m or more, the process of step S605 is not executed until the value of each time of the modified front shaft spring rigidity data becomes m or more. The processes of steps S602 to S604 are repeated.

Next, in step S606, the determination unit 303 determines the rigidity of the shaft springs 18L and 18R based on the shaft spring rigidity k _{1, i} and k _{1, i + 1} (corrected shaft spring rigidity) derived in step S605. Judge whether or not (spring constant) is abnormal. As a result of the determination in step S606, if the rigidity (spring constant) of at least one of the shaft springs 18L and 18R is not normal, the process proceeds to step S607. On the other hand, when the rigidity (spring constant) of all the shaft springs 18L and 18R is normal, the process skips step S607 and proceeds to step S608 described later.

When the process proceeds to step S607, the output unit 304 outputs abnormal information including that the rigidity (spring constant) of the shaft springs 18L and 18R is abnormal.
Next, in step S608, the inspection device 300 determines whether or not the railroad vehicle to be inspected has left the inspection section. As a result of this determination, if the railroad vehicle to be inspected does not leave the inspection section, the process returns to step S602, and the processes of steps S602 to S608 are repeatedly executed until the railroad vehicle to be inspected leaves the inspection section. .. Then, in step S608, when it is determined that the railway vehicle to be inspected has left the inspection section, the process according to the flowchart of FIG. 6 ends.
In step S606, when the rigidity (spring constant) of all the shaft springs 18L and 18R is normal, the output unit 304 includes that the rigidity (spring constant) of all the shaft springs 18L and 18R is normal. Normal information may be output.

<Calculation example>
Next, a calculation example will be described. Here, assuming that the motion state of the railroad vehicle has 86 degrees of freedom, data corresponding to the measurement data in the present embodiment was acquired from the result of simulating (numerical analysis) the running of the railroad vehicle traveling at 270 km / hr. .. Using the data acquired in this way, the shaft spring rigidity is derived by the method described in this embodiment, and the value set in the simulation is compared with the value obtained by the method described in this embodiment. did.
FIG. 7 is a diagram showing the curvature 1 / R of the rail used in this calculation example, the amount of deviation y _R, and the amount of deviation y _H. The time on the horizontal axis shown in FIG. 7 corresponds to the time on the horizontal axis shown in FIGS. 8 to 14.

Passage is a left-right displacement of the rail in the longitudinal direction, as described in the Japanese Industrial Standards (JIS E 1001: 2001). The amount of deviation is the amount of displacement. High-low deviation is a vertical displacement of the rail in the longitudinal direction as described in the Japanese Industrial Standards (JIS E 1001: 2001). The amount of high-low deviation is the amount of displacement.
In FIG. 7, a positive curvature 1 / R indicates that the railroad vehicle turns clockwise in the direction of travel.

FIG. 8 is a diagram showing a first example of time-series data of the front-back directional forces F _{Wx, 1} , F _{Wx, 2} , F _{Wx, 3} , and F _{Wx, 4} used in this calculation example. FIG. 8 shows the sum of the anteroposterior force F _{Wx, i} ^L on the left side of the same wheel set 13a to 13d and the anteroposterior force F _{Wx, i} ^R on the right side. FIG. 8 shows an example of time-series data of the longitudinal forces _{FWx, 1} , _{FWx, 2} , _{FWx, 3} , _{FWx, 4} when all the shaft springs 18L and 18R are normal.

FIG. 9 is a diagram showing a second example of time-series data of the front-back directional forces F _{Wx, 1} , F _{Wx, 2} , F _{Wx, 3} , and F _{Wx, 4} used in this calculation example. In FIG. 9, similarly to FIG. 8, the sum of the front-rear direction forces F _{Wx, i} ^L on the left side of the same wheel set 13a to 13d and the front-rear direction force F _{Wx, i} ^R on the right side is shown. FIG. 9 shows the front-rear direction forces F _{Wx, 1} , F _{Wx, 2} when the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheel axle 13a) of the front bogie 12a is halved from the normal state. , _{FWx, 3} , _{FWx, 4} shows an example of time-series data. In FIG. 9, normal indicates time series data of the front-rear direction forces F _{Wx, 1} , F _{Wx, 2} , F _{Wx, 3} , and F _{Wx, 4} when all the shaft springs 18L and 18R are normal. fail is the front-rear direction force F _{Wx, 1} , F _{Wx, 2} , when the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheel set 13a) of the front bogie 12a is halved from the normal state. The time series data of F _{Wx, 3} and F _{Wx, 4} are shown. Note that normal corresponds to a graph having a low density and is the same as the graph shown in FIG. fail corresponds to a dense graph.

FIG. 10 is a diagram showing a third example of time-series data of the front-back directional forces F _{Wx, 1} , F _{Wx, 2} , F _{Wx, 3} , and F _{Wx, 4} used in this calculation example. Also in FIG. 10, similarly to FIGS. 8 and 9, the sum of the front-rear direction forces F _{Wx, i} ^L on the left side of the same wheel sets 13a to 13d and the front-rear direction forces F _{Wx, i} ^R on the right side is shown. FIG. 10 shows the front-rear direction forces F _{Wx, 1} , F _{Wx, 2} when the rigidity (spring constant) of the right shaft spring 18R of the front wheel (wheel set 13a) of the front bogie 12a is halved from the normal state. , _{FWx, 3} , _{FWx, 4} shows an example of time-series data. In FIG. 10, normal indicates time-series data of the longitudinal forces F _{Wx, 1} , F _{Wx, 2} , F _{Wx, 3} , and F _{Wx, 4} when all the shaft springs 18L and 18R are normal. fail is the front-rear direction force F _{Wx, 1} , F _{Wx, 2} , when the rigidity (spring constant) of the right shaft spring 18R of the front wheel (wheel set 13a) of the front bogie 12a is halved from the normal state. The time series data of F _{Wx, 3} and F _{Wx, 4} are shown. Note that normal corresponds to a graph having a low density and is the same as the graph shown in FIG. fail corresponds to a dense graph.

FIG. 11 is a diagram showing an example of time-series data of the modified front shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ . Here, the coefficients q ₁ and q ₂ of the equations (28a) and (28b) are set to "0.5" and "1.5", respectively (q ₁ = 0.5, q ₂ = 1.5). ).
11, reference is normal axis spring 18L, the average value _k of the spring constant of 18R 1, 1 _- indicates a _{-, k 1,2 -, k 1,3} -, k 1,4. The estimated values show the modified front shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ obtained by the method of the present embodiment. The standard corresponds to a graph having a low density. Estimates correspond to denser graphs. As in the example shown in FIG. 11, the modified front shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ may be unstable. Note that FIG. 11 shows an example of time-series data of the modified front shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , k ₁ , ₄ when all the shaft springs 18L and 18R are normal. Shown.

FIG. 12 is a diagram showing a first example of time-series data of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ . FIG. 12 shows an example of time-series data of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ when all the shaft springs 18L and 18R are normal. That is, FIG. 12 shows the modified front shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , k ₁ , ₄ shown in FIG. 11 after modification obtained by the method of the present embodiment. The time series data of the shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ are shown. 12, reference is normal axis spring 18L, the average value _k of the spring constant of 18R 1, 1 _- indicates a _{-, k 1,2 -, k 1,3} -, k 1,4. The estimated values show the modified shaft spring stiffness k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ obtained by the method of the present embodiment. The standard corresponds to a graph having a low density. Estimates correspond to denser graphs.

In FIG. 12, the average values of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ (estimated values) obtained by the method of the present embodiment are normal, respectively. axial springs 18L, the average value of the spring constant of _{18R k 1,1 -, k 1,2 -} , k 1,3 -, k 1,4 - 1.02 times the average value (reference value), 1.08 It was double, 1.02 times, and 1.08 times. In the linear orbit with the time shown in FIG. 7 from 0 seconds to about 15 seconds, the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , k ₁ obtained by the method of the present embodiment is used. _{, 4} (estimated values) are the average values of the spring constants of the normal shaft springs 18L and 18R, k ₁ , _1- , k ₁ , _2, -, k ₁ , _3- , k ₁ , _4- (, respectively. It was 1.02 times, 1.09 times, 1.03 times, and 1.07 times the average value of the reference value).
As described above, when all the shaft springs 18L and 18R are normal, in the method of the present embodiment, when simulating the running of the railroad vehicle (numerical analysis) assuming that the motion state of the railroad vehicle has 86 degrees of freedom. It can be seen that the same result as the value set in is obtained.

FIG. 13 is a diagram showing a second example of time-series data of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ . FIG. 13 shows the modified rear shaft spring rigidity k ₁ , ₁ , k ₁ when the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheel axle 13a) of the front carriage 12a is halved from the normal state. An example of time-series data of _{, 2} , k ₁ , ₃ , and k ₁ , ₄ is shown. 13, reference is normal axis spring 18L, the average value _k of the spring constant of 18R 1, 1 _- indicates a _{-, k 1,2 -, k 1,3} -, k 1,4. The estimated values show the modified shaft spring stiffness k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ obtained by the method of the present embodiment. The standard corresponds to a graph having a low density. Estimates correspond to denser graphs.

In FIG. 13, the average values of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ (estimated values) obtained by the method of the present embodiment are normal, respectively. axial springs 18L, the average value of the spring constant of _{18R k 1,1 -, k 1,2 -} , k 1,3 -, k 1,4 - 0.61 times the average value (reference value), 1.08 It was double, 1.04 times, and 1.09 times. In the linear orbit with the time shown in FIG. 7 from 0 seconds to about 15 seconds, the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , k ₁ obtained by the method of the present embodiment is used. _{, 4} (estimated values) are the average values of the spring constants of the normal shaft springs 18L and 18R, k ₁ , _1- , k ₁ , _2, -, k ₁ , _3- , k ₁ , _4- (, respectively. It was 0.77 times, 1.08 times, 1.04 times, and 1.08 times the average value of the reference value).
As described above, even when the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheelset 13a) of the front bogie 12a is halved of the normal state, the method of the present embodiment is that of the railcar. It can be seen that a result equivalent to the value set when simulating (numerical analysis) the running of a railroad vehicle is obtained assuming that the motion state has 86 degrees of freedom.

The shaft spring rigidity k _{1, i} and k _{1, i + 1} are average values of the rigidity (spring constant) of the shaft springs 18L and 18R attached to the shaft boxes 17L and 17R arranged at intervals in the left-right direction. Therefore, assuming that the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheel axle 13a) of the front bogie 12a is 1/2 times the normal value, theoretically, the average value of the shaft spring rigidity is the normal value. It becomes 0.75 times (= (1.0 + 0.5) ÷ 2). In the result shown in FIG. 13, the rigidity (spring constant) of the shaft spring of the front wheel (wheel axle 13a) of the front bogie 12a is 0.77 times that in the normal state, which is close to 0.75 times.

FIG. 14 is a diagram showing a second example of time-series data of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ . FIG. 14 shows the modified rear shaft spring rigidity k ₁ , ₁ , k ₁ when the rigidity (spring constant) of the right shaft spring 18R of the front wheel (wheel axle 13a) of the front carriage 12a is halved from the normal state. An example of time-series data of _{, 2} , k ₁ , ₃ , and k ₁ , ₄ is shown. 14, reference is normal axis spring 18L, the average value _k of the spring constant of 18R 1, 1 _- indicates a _{-, k 1,2 -, k 1,3} -, k 1,4. The estimated values show the modified shaft spring stiffness k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ obtained by the method of the present embodiment. The standard corresponds to a graph having a low density. Estimates correspond to denser graphs.

In FIG. 14, the average values of the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , and k ₁ , ₄ (estimated values) obtained by the method of the present embodiment are normal, respectively. 0.74 times, 1.07 times the average value of the average values of the spring constants of the shaft springs 18L and 18R, k _1,1- , k ₁ , _2, -, k _1,3- , k _1,4- (reference value) It was double, 1.03 times, and 1.09 times. In the linear orbit with the time shown in FIG. 7 from 0 seconds to about 15 seconds, the modified shaft spring rigidity k ₁ , ₁ , k ₁ , ₂ , k ₁ , ₃ , k ₁ obtained by the method of the present embodiment is used. _{, 4} (estimated values) are the average values of the spring constants of the normal shaft springs 18L and 18R, k ₁ , _1- , k ₁ , _2, -, k ₁ , _3- , k ₁ , _4- (, respectively. It was 0.76 times, 1.08 times, 1.04 times, and 1.08 times the average value of the reference value).

As described above, even when the rigidity (spring constant) of the shaft spring 18R on the right side of the front wheel (wheelset 13a) of the front bogie 12a is set to 1/2 times the normal state, the method of the present embodiment uses the method of the railroad vehicle. It can be seen that the same result as the value set when simulating (numerical analysis) the running of the railroad vehicle is obtained assuming that the motion state has 86 degrees of freedom.

Further, assuming that the rigidity (spring constant) of the shaft spring 18R on the right side of the front wheel (wheel set 13a) of the front bogie 12a is 1/2 times the normal value, theoretically, the average value of the shaft spring rigidity is 0 at the normal time. It becomes .75 times (= (1.0 + 0.5) ÷ 2). In the result shown in FIG. 14, the rigidity (spring constant) of the shaft spring of the front wheel (wheel axle 13a) of the front bogie 12a is 0.76 times that in the normal state, which is close to 0.75 times.

Further, in the results shown in FIGS. 13 and 14, the rigidity of the shaft spring 18L on the opposite side (left side) of the rigidity (spring constant) of the shaft spring 18R in the direction in which the railroad vehicle bends (on the right side in the traveling direction) The spring constant) is smaller (see the top graphs of FIGS. 13 and 14). Therefore, when determining the presence or absence of an abnormality in the rigidity (spring constant) of the shaft springs 18L and 18R in a curved track, it is determined whether or not there is an abnormality in the rigidity (spring constant) of the shaft spring in the direction opposite to the bending direction of the railroad vehicle. Is easier to do.

<Summary>
As described above, in the present embodiment, the inspection device 300 uses the measured values of the longitudinal force (F _{Wx, i} ^L + F _{Wx, i} ^R + F _{Wx, i + 1} ^L + F _{Wx, i + 1} ^R ) to obtain the shaft spring 18L. The state of 18R is detected. Specifically, in the inspection device 300, the average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction (k _{1, i} (z _{t, j −} aθ _{t, j)} Axle spring stiffness k _{1, i} , k _{1, i + 1} is derived using a mathematical formula expressing −z _{w, i} ), k _{1, i + 1} (z _{t, j} + aθ _{t, j −} z _{w, i + 1} )). .. The formula is derived based on the equation of motion (Equation (1)) representing the vertical movement of the carriages 12a and 12b and the equation of motion (Equation (2)) representing the pitching of the carriages 12a and 12b. Then, the inspection device 300 determines whether or not the rigidity (spring constant) of the shaft springs 18L and 18R is normal based on the derived shaft spring rigidity k _{1, i} and k _{1, i + 1} .
Therefore, the state of rigidity (spring constant) of the shaft springs 18L and 18R can be accurately detected. This makes it possible to accurately determine whether or not the rigidity (spring constant) of the shaft springs 18L and 18R is normal.

Here, the above formula is based on the load ( _FASzj ^L , _FASzj ^R ) received by the air springs 22L and 22R, and the left shaft damper 19L and the right shaft damper 19L arranged at intervals in the left-right direction. The average value of the force received by 19R (c ₁ {2z _{t, j} ·-(z _{w, i} · + z _{w, i + 1} ·)}) and the moment of force received by the axle dampers 19L and 19R from the axle dampers 19L and 19R. _{(a 1 c 1 {-2a 1} θ t, j · - (z w, i · -z w, i + 1 ·)}) and the centrifugal force the bogie 12a, 12b is subjected _(m ^t v 2 1/2 _{(1 / R i sinφ rail, i +} 1 / R i + 1 sinφ rail, i + 1)) and, carriage 12a, 12b is subjected to gravity _{(m t g (1-1 / 2cosφ} rail, i -1 / 2cosφ rail, i + 1)) and, The moment of force (h ₁ (F _{Wx, i} ^L + F _{Wx, i} ^R + F _{Wx, i + 1} ^L + F _{Wx, i + 1} ^R ) received by the trolleys 12a and 12b based on the front-rear direction force) and the trolleys 12a and 12b in the vertical direction. Yes inertia _{(m t z t, j ··} ) and, carriage 12a in pitching, 12b based on the receive sum of moments of force and _{(I t, y θ t,} j ··), a distance in the lateral direction The average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals (k _{1, i} (z _{t, j} −a θ _{t, j −} z _{w, i} ), k _1, It is a formula for deriving _{i + 1} (z _{t, j} + aθ _{t, j-} z _{w, i + 1} )), and the inspection device 300 uses the formula to determine the shaft spring rigidity k _{1, i} , k _{1, i + 1} . Therefore, the physical quantity indicating the state of the shaft springs 18L and 18R can be directly evaluated.

Further, in the present embodiment, when the shaft spring rigidity k _{1, i} , k _{1, i + 1} derived as described above exceeds the upper limit value, the inspection device 300 has the shaft spring rigidity k _{1, i} , Let k _{1, i + 1} be the upper limit value. Further, when the shaft spring rigidity k _{1, i} , k _{1, i + 1} derived as described above exceeds the lower limit value, the inspection device 300 determines the shaft spring rigidity k _{1, i} , k _{1, i + 1} . The lower limit is used. Therefore, it is possible to prevent the values of the shaft spring rigidity k _{1, i} and k _{1, i + 1 from} becoming extremely large or small. Therefore, it is possible to more accurately determine whether or not the shaft springs 18L and 18R are normal.

Further, in the present embodiment, the inspection device 300 generates an autocorrelation matrix R from the data y of the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected front shaft spring rigidity) derived as described above. .. The inspection device 300 uses the eigenvalue having the largest value among the eigenvalues obtained by decomposing the autocorrelation matrix R into singular values, and uses the eigenvalues k _{1, i} , k _{1, i + 1} (corrected front shaft spring rigidity). ), The coefficient α of the modified autoregressive model that approximates the data y is determined. Then, the inspection device 300 corrects the shaft spring rigidity k _{1, i} and k _{1, i + 1} by using the determined coefficient α (the corrected shaft spring rigidity is derived). Therefore, the noise contained in the shaft spring rigidity k _{1, i} and k _{1, i + 1} can be appropriately reduced without adjusting the cutoff frequency or the like. Therefore, it is possible to more accurately determine whether or not the shaft springs 18L and 18R are normal.

<Modification example>
As described above, a low-pass filter or a band-pass filter may be used instead of the modified autoregressive model. Further, when the time series data of the shaft spring rigidity k _{1, i} , k _{1, i + 1} is stable, the inspection device 300 uses the time series data of the shaft spring rigidity k _{1, i} , k _{1, i + 1} as it is. , It may be determined whether or not the shaft springs 18L and 18R (rigidity (spring constant)) are normal. Further, in such a case, it is not necessary to change the shaft spring rigidity to the upper and lower limit values of k _{1, i} and k _{1, i + 1} .
Further, as described above, the pillow spring does not have to be an air spring, and the load received by the bogie from the pillow spring may be calculated according to the type of spring used.

(Second Embodiment)
Next, the second embodiment will be described.
In the first embodiment, a case where the inspection device 300 mounted on the railroad vehicle determines whether or not the shaft springs 18L and 18R (rigidity (spring constant)) are normal 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 300 is arranged at the command center. This data processing device receives the measurement data transmitted from the railroad vehicle, and uses the received measurement data to check whether the shaft springs 18L and 18R (rigidity (spring constant)) of the railroad vehicle to be inspected are normal. Judge whether or not. As described above, in the present embodiment, the functions of the inspection device 300 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, detailed description of the same parts as those of the first embodiment will be omitted by adding the same reference numerals as those given in FIGS. 1 to 14.

FIG. 15 is a diagram showing an example of the configuration of the inspection system. In FIG. 15, the inspection system includes data collecting devices 1510a and 1510b and a data processing device 1520. FIG. 15 also shows an example of the functional configuration of the data collecting devices 1510a and 1510b and the data processing device 1520. The hardware of the data collecting devices 1510a and 1510b and the data processing device 1520 can be realized by, for example, those shown in FIG. Therefore, detailed description of the hardware configuration of the data collection devices 1510a and 1510b and the data processing device 1520 will be omitted.

Each railroad vehicle is equipped with one data collection device 1510a and one 1510b. The data processing device 1520 is located at the command center. The command center, for example, centrally manages the operation of a plurality of rolling stock.

< Data collection devices 1510a, 1510b>
The data collection devices 1510a and 1510b can be realized by the same device. The data acquisition devices 1510a and 1510b include data acquisition units 1511a and 1511b and data transmission units 1512a and 1512b.

<< Data acquisition units 1511a, 1511b >>
The data acquisition units 1511a and 1511b have the same functions as the track information acquisition unit 501 and the railway vehicle state information acquisition unit 502. That is, the data acquisition units 1511a and 1511b, like the data acquisition unit 301, measure data ( _{FWx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R , P _j ^L , P _j ^R , z _ASj ^L , z _ASj ^R , z _b , z _{t, j} ..., z _{t, j} ·, z _{t, j} , z _{w, i} ·, z _{w, i + 1} ·, z _{w, i} , z Acquire _{w, i + 1} , v).

<< Data transmitters 1512a, 1512b >>
The data transmission units 1512a and 1512b transmit the measurement data of the railway vehicle to be inspected acquired by the data acquisition units 1511a and 1511b to the data processing device 1520. In the present embodiment, the data transmission units 1512a and 1512b transmit the measurement data of the railway vehicle to be inspected acquired by the data acquisition units 1511a and 1511b to the data processing device 1520 by wireless communication. At this time, the data transmission units 1512a and 1512b add the identification number of the railroad vehicle on which the data collection devices 1510a and 1510b are mounted to the measurement data of the railroad vehicle to be inspected acquired by the data acquisition units 1511a and 1511b. .. In this way, the data transmission units 1512a and 1512b transmit data to which the identification number of the railway vehicle is added as the data of the measurement data of the railway vehicle to be inspected.

<Data processing device 1520>
<< Data receiver 1521 >>
The data receiving unit 1521 receives the data of the measurement data of the railway vehicle to be inspected transmitted by the data transmitting units 1512a and 1512b. The identification number of the railway vehicle that is the source of the measured value is added to the measurement data of the railway vehicle to be inspected.

<< Data storage unit 1522 >>
The data storage unit 1522 stores the measurement data of the railway vehicle to be inspected received by the data reception unit 1521. The data storage unit 1522 stores the measurement data of the railway vehicle to be inspected for each identification number of the railway vehicle. Based on the current operation status of the railroad vehicle and the reception time of the measurement data of the railroad vehicle to be inspected, the data storage unit 1522 determines the traveling position of the railroad vehicle at the reception time of the measurement data of the railroad vehicle to be inspected. The information of the specified running position and the measurement data of the railroad vehicle to be inspected are stored in association with each other. The data collection devices 1510a and 1510b may collect information on the current traveling position of the railway vehicle, and the collected information may be added to the measurement data of the railway vehicle to be inspected.

<< Data reader 1523 >>
The data reading unit 1523 reads out the measurement data of the railway vehicle to be inspected stored by the data storage unit 1522. The data reading unit 1523 can read the measurement data specified by the operator from the measurement data of the railway vehicle to be inspected stored by the data storage unit 1522. In addition, the data reading unit 1523 can also read out the measured values that match the predetermined conditions from the measurement data of the railway vehicle to be inspected at a predetermined timing. In the present embodiment, the measurement data of the railway vehicle to be inspected read by the data reading unit 1523 is determined based on, for example, at least one of the identification number of the railway vehicle and the traveling position.

The shaft spring state detection unit 302, the determination unit 303, and the output unit 304 are the same as those described in the first embodiment. Therefore, the detailed description thereof will be omitted here. The shaft spring state detection unit 302 uses the measurement data of the railroad vehicle to be inspected read by the data reading unit 1523 instead of the measurement data of the railcar to be inspected acquired by the data acquisition unit 301. Derived the shaft spring rigidity (corrected shaft spring rigidity) of the railroad vehicle to be inspected.

<Summary>
As described above, in the present embodiment, the data collecting devices 1510a and 1510b mounted on the railroad vehicle collect the measurement data of the railroad vehicle to be inspected and transmit it to the data processing device 1520. The data processing device 1520 arranged at the command center stores the measurement data of the rolling stock to be inspected received from the data collecting devices 1510a and 1510b, and uses the stored measurement data of the rolling stock to be inspected to be inspected. It is determined whether or not the shaft springs 18L and 18R (rigidity (spring constant)) of the railroad vehicle are normal. Therefore, in addition to the effects described in the first embodiment, for example, the following effects are exhibited. That is, the data processing device 1520 reads the measurement data of the railroad vehicle to be inspected at an arbitrary timing, and at an arbitrary timing, the rigidity (spring) of the shaft springs 18L and 18R in each railroad vehicle managed by the command center. It can be determined whether or not the constant) is normal.

<Modification example>
In the present embodiment, the case where the measurement data of the railroad vehicle to be inspected is directly transmitted from the data collecting devices 1510a and 1510b to the data processing device 1520 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.
Further, in the present embodiment, the case where the data collecting devices 1510a and 1510b acquire all of the measured data has been described as an example. However, it is not always necessary to do this. For example, among the measurement data, variables obtained from the measured values (z _b , z _{t, j} ·, z _{t, j} , z _{w, i} ·, z _{w, i + 1} ·, z _{w, i} , z _{w, i + 1} ) May be derived in the data processing device 1520.
In addition, in this embodiment as well, various modifications described in the first embodiment can be adopted.

(Third Embodiment)
Next, a third embodiment will be described. In the first embodiment, the shaft spring stiffnesses k _{1, i} and k _{1, i + 1} are derived in a predetermined sampling period by performing the calculations of the equations (3) and (4). In this way, when the value of the denominator of the equations (3) and (4) is "0", so-called zero division calculation is performed. Therefore, it is necessary to limit the range of the shaft spring rigidity k _{1, i} and k _{1, i + 1} (see equations (28a) and (28b)). Further, in the first embodiment, time series data is derived as data y of the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected front shaft spring rigidity). Therefore, it is necessary to remove the noise component.

From the above, in the first embodiment, the calculation load for deriving the shaft spring rigidity k _{1, i} and k _{1, i + 1} becomes high. Therefore, in the present embodiment, the measurement data in the inspection section ( _{FWx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R , P _j ^L , P _j ^R , z _ASj ^L , z _{Based on ASj} ^R , z _b , z _{t, j} ..., z _{t, j} ·, z _{t, j} , z _{w, i} ·, z _{w, i + 1} ·, z _{w, i} , z _{w, i + 1} , v) Then, the shaft spring rigidity k _{1, i} and k _{1, i + 1} in the inspection section are derived one by one for each wheel set. As described above, the configuration and processing for deriving the shaft spring rigidity k _{1, i} , k _{1, i + 1} are mainly different between the present embodiment and the first embodiment. Therefore, in the description of the present embodiment, detailed description of the same parts as those of the first embodiment will be omitted by adding the same reference numerals as those given in FIGS. 1 to 14.

FIG. 16 is a diagram showing an example of the functional configuration of the inspection device 1600. The inspection device 1600 replaces the inspection device 300. The hardware configuration of the inspection device 1600 is, for example, the same as that shown in FIG.

In FIG. 16, the inspection device 1600 has a data acquisition unit 1601, a shaft spring state detection unit 1602, a determination unit 1603, and an output unit 1604 as its functions.

<< Data acquisition unit 1601 >>
The data acquisition unit 1601 acquires the measured values required for the calculation described later at a predetermined sampling cycle when the railway vehicle to be inspected is traveling in the inspection section. Similar to the data acquisition unit 301, the data acquisition unit 1601 has measurement data ( _{FWx, i} ^L , F _{Wx, i} ^R , F _{Wx, i + 1} ^L , F _{Wx, i + 1} ^R , P _j ^L , P _j ^R , z. _ASj ^L , z _ASj ^R , z _b , z _{t, j} ..., z _{t, j} ·, z _{t, j} , z _{w, i} ·, z _{w, i + 1} ·, z _{w, i} , z _{w, i + 1} , v) is obtained. In the first embodiment, the data acquisition unit 301 outputs the measurement data to the shaft spring state detection unit 302 every time the measurement data is obtained in a predetermined sampling cycle. On the other hand, in the present embodiment, the data acquisition unit 1601 may collectively output the measurement data in the inspection section to the shaft spring state detection unit 1602 when the measurement data in the inspection section is obtained. However, similarly to the data acquisition unit 301, the data acquisition unit 1601 may output the measurement data to the shaft spring state detection unit 302 each time the measurement data is obtained in a predetermined sampling cycle.

<< Shaft spring state detector 1602 >>
The shaft spring state detection unit 1602 derives the rigidity (spring constant) k ₁ (k _{1, i} , k _{1, i + 1} ) of the shaft springs 18L and 18R using the measurement data obtained by the data acquisition unit 1601. To do. In the present embodiment, the shaft spring state detection unit 1602 has a shaft spring rigidity lead-out unit 1602a.
<<< Shaft spring rigidity lead-out unit 1602a >>>
The shaft spring rigidity derivation unit 1602a is activated when the data acquisition unit 1601 obtains the measurement data in the inspection section. The shaft spring rigidity derivation unit 1602a derives the shaft spring rigidity k _{1, i} , k _{1, i + 1} in the inspection section by using the measurement data in the inspection section obtained by the data acquisition unit 1601.

Equation (3) is an equation representing the average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the front wheels (wheel sets 13a and 13c). In equation (3), the product of k _{1, i} and (z _{t, j-} aθ _{t, j-} z _{w, i} ) is on the left side of the front wheels ( axles 13a, 13c) arranged with a space in the left-right direction. It is the average value of the forces received by the shaft spring 18L and the right shaft spring 18R. Further, k _{1 and i} are average values of rigidity (spring constant) of the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the front wheels (wheel sets 13a and 13c). Therefore, (z _{t, j-} aθ _{t, j-} z _{w, i} ) is the displacement of the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the front wheels ( wheel axles 13a, 13c). Represents the average value of.

In equation (3) _, assuming that only the product of k _{1, i} and (z _{t, j} −aθ _{t, j −} z _{w, i} ) is on the left side, and the other constants and variables in equation (3) are on the right side. It becomes like the following equation (29).

Equation (4) is an equation representing the average value of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the rear wheels (wheel sets 13b and 13d). In equation (4), the product of k _{1, i + 1} and (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) is the left side of the rear wheels ( axles 13b, 13d) lined up with a space in the left-right direction. It is the average value of the forces received by the shaft spring 18L and the right shaft spring 18R. Further, k _{1 and i + 1} are average values of the rigidity (spring constant) of the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the rear wheels (wheel sets 13b and 13d). Therefore, (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) is the displacement of the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the rear wheels ( wheel axles 13b, 13d). Represents the average value of.

In equation (4), assuming that only the product of k _{1, i + 1} and (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) is the left side, and the other constants and variables in equation (4) are the right side, the following It becomes like the equation (30) of.

In the following description, ((z _{t, j −} aθ _{t, j −} z _{w, i} ), (z _{t, j} + aθ _{t, j −} z _{w, i + 1} ) on the left side of equations (29) and (30)). ) Is abbreviated as displacement, if necessary. Further, the equations on the right side of equations (29) and (30) are referred to as restoring force, if necessary.

The shaft spring rigidity deriving unit 1602a uses the measurement data of the same sampling period to displace (z _{t, j −} aθ _{t, j −} z _{w, i} ), (z _{t, j} + aθ _{t, j −} z _{w,). i + 1} ) is derived. As described in the first embodiment, θ _{t and j} are derived by solving Eq. (11). Further, the shaft spring rigidity derivation unit 1602a derives the restoring force by using the measurement data of the same sampling period. The shaft spring rigidity derivation unit 1602a creates a set of displacement and restoring force derived using measurement data of the same sampling period as one data set. The shaft spring rigidity derivation unit 1602a creates such a data set for the measurement data in the inspection section. As a result, a data set at each sampling time measured when the railroad vehicle to be inspected is traveling in the inspection section is created. In the following description, the data set at each sampling time measured when the railroad vehicle to be inspected is traveling in the inspection section is referred to as a data set in the inspection section, if necessary.

The shaft spring rigidity derivation unit 1602a derives a simple regression equation showing the relationship between the restoring force and the displacement based on the data set in the inspection section. Let the restoring force be FR _i and the displacement be DI _i . The objective variable is the restoring force FR _i , and the explanatory variable is the displacement DI _i . Then, the simple regression equation showing the relationship between the restoring force and the displacement is expressed by the following equation (31).

FR _i = α _i × DI _i + β _i ... (31)
α _i and β _i are regression coefficients. α _i is a regression coefficient that is multiplied by the explanatory variable DI _i , and corresponds to the slope of the simple regression equation. β _i corresponds to the intercept of the simple regression equation. The subscript i is a symbol for identifying the wheel sets 13a, 13b, 13c, and 13d (i = 1, 2, 3, and 4 correspond to the wheel sets 13a, 13b, 13c, and 13d, respectively).

Derivation of the simple regression equation of Eq. (31) is equivalent to deriving the regression coefficients α _i and β _i . The regression coefficients α _i and β _i are derived, for example, by the method of least squares.

Axial spring rigidity deriving unit 1602a includes regression coefficients alpha _i, of the beta _i, a regression coefficient alpha _i representing the inclination of the single regression equation, the axial spring rigidity _k 1, _i in the test _section, derived as _{k 1, i + 1.} The regression coefficients α _i and β _i are derived for each wheel set 13a to 13d.

The value of (z _{t, j} −a θ _{t, j −} z _{w, i} ) on the left side of equation (29) when the subscript i is 1 and the subscript j is 1 is the displacement DI ₁ on the wheel set 13a. Become. When the subscript i is 1 and the subscript j is 1, the value on the right side of the equation (29) is the restoring force FR ₁ on the wheel set 13a. By using the displacement DI ₁ and the restoring force FR ₁ thus obtained, the regression coefficient α ₁ with respect to the wheel set 13a is derived. The regression coefficient α ₁ is k _{1, i} of Eq. (29) when the subscript i is 1. That is, the regression coefficient α ₁ is an average value k ₁ , _{1 of the} forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the wheel axle 13a.

The value of (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) on the left side of equation (30) when the subscript i is 1 and the subscript j is 1 is the displacement DI ₂ on the wheel set 13b. .. When the subscript i is 1 and the subscript j is 1, the value on the right side of the equation (30) is the restoring force FR ₂ on the wheel set 13b. By using the displacement DI ₂ and the restoring force FR ₂ obtained in this way, the regression coefficient α ₂ with respect to the wheel set 13b is derived. The regression coefficient α ₂ is k _{1, i + 1} of the equation (30) when the subscript i is 1. That is, the regression coefficient α ₂ is an average value k ₁ and _{2 of the} forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the wheel axle 13b.

The value of (z _{t, j} −a θ _{t, j −} z _{w, i} ) on the left side of equation (29) when the subscript i is 3 and the subscript j is 2, is the displacement DI ₃ on the wheel set 13c. Become. When the subscript i is 3 and the subscript j is 2, the value on the right side of the equation (29) is the restoring force FR ₃ on the wheel set 13c. By using the displacement DI ₃ and the restoring force FR ₃ thus obtained, the regression coefficient α ₃ with respect to the wheel set 13c is derived. The regression coefficient α ₃ is k _{1, i} of Eq. (29) when the subscript i is 3. That is, the regression coefficient α ₃ is an average value k ₁ , _{3 of the} forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the wheel axle 13c.

When the subscript i is 3 and the subscript j is 2, the value of (z _{t, j} + aθ _{t, j-} z _{w, i + 1} ) on the left side of the equation (30) is the displacement DI ₄ on the wheel set 13d. .. When the subscript i is 3 and the subscript j is 2, the value on the right side of the equation (30) is the restoring force FR ₄ on the wheel set 13d. By using the displacement DI ₄ and the restoring force FR ₄ thus obtained, the regression coefficient α ₄ with respect to the wheel set 13d is derived. The regression coefficient α ₄ is k _{1, i + 1} of Eq. (30) when the subscript i is 3. That is, the regression coefficient α ₄ is an average value k ₁ , _{4 of the} forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction on the wheel axle 13d.
The shaft spring rigidity deriving unit 1602a derives the shaft spring rigidity k _{1, i} and k _{1, i + 1} in the inspection section as described above.

<< Judgment unit 1603 >>
The determination unit 1603 determines whether or not there is an abnormality in the rigidity (spring constant) of the shaft springs 18L and 18R based on the shaft spring rigidity k _{1, i} and k _{1, i + 1} derived by the shaft spring state detection unit 1602. To do. For example, the determination unit 1603 has the shaft spring rigidity k _{1, i} , k _{1, i + 1} derived by the shaft spring state detection unit 1602 and the normal shaft spring rigidity k _{1, i} −, k _{1, i + 1.} Based on the result of comparison with −, it is determined whether or not there is an abnormality in the rigidity (spring constant) of the shaft springs 18L and 18R. For example, the determination unit 1603 has the shaft spring rigidity k _{1, i} , k _{1, i + 1} derived by the shaft spring state detection unit 1602 and the normal shaft spring rigidity k _{1, i} −, k _{1, i + 1.} When the absolute value of the difference from-exceeds the threshold value, it is determined that the rigidity (spring constant) of the shaft springs 18L and 18R is abnormal, and when not, the rigidity (spring constant) of the shaft springs 18L and 18R is determined. Is not abnormal.

In the first embodiment, the shaft spring rigidity k _{1, i} and k _{1, i + 1} (corrected shaft spring rigidity) are derived each time measurement data is obtained at a time determined by a predetermined sampling cycle. Therefore, it is determined whether or not the rigidity (spring constant) of the shaft springs 18L and 18R is abnormal at a time determined by a predetermined sampling cycle. On the other hand, in the present embodiment, one shaft spring rigidity k _{1, i} and k _{1, i + 1} are derived for one wheel set 13a to 13d using the measurement data in the inspection section. Therefore, when the measurement data in the inspection section is obtained, it is determined only once whether or not the rigidity (spring constant) of the shaft springs 18L and 18R is abnormal for one wheel set 13a to 13d.

<< Output 1604 >>
The output unit 1604 outputs information based on the result determined by the determination unit 1603. Specifically, when the determination unit 1603 determines that the rigidity (spring constant) of all the shaft springs 18L and 18R is normal, the output unit 1604 outputs information indicating that fact. Further, when the determination unit 1603 determines that the rigidity (spring constant) of at least the shaft springs 18L and 18R is abnormal, the output unit 1604 outputs information indicating that fact. At this time, the output unit 1604 also outputs information for identifying the shaft spring whose rigidity (spring constant) is determined to be abnormal. 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 of the inspection device 300 can be adopted.

An arbitrary section is preset as the inspection section. For example, a straight track may be an inspection section, or a curved track may be an inspection section. Further, when the railroad vehicle uses a curved track that rotates clockwise in the traveling direction as the inspection section, the determination unit 1603 determines whether or not the left shaft spring 18L is abnormal, and determines whether or not the right shaft spring 18R is abnormal. It is not necessary to judge. On the other hand, when the railroad vehicle uses a curved track counterclockwise in the direction of travel as the inspection section, the determination unit 1603 determines whether or not the right shaft spring 18R is abnormal, and determines whether or not the left shaft spring 18L is abnormal. It is not necessary to judge.

<Operation flowchart>
Next, an example of processing in the inspection device 1600 of the present embodiment will be described with reference to the flowchart of FIG.
First, in step S1701, the data acquisition unit 1601 acquires the measurement data in the inspection section. Then, the process of step S1702 is executed. The processing after step S1702 is started after the railroad vehicle travels in the inspection section and the measurement data in the inspection section is acquired.

Next, in step S1702, the shaft spring rigidity derivation unit 1602a creates a data set in the inspection section using the measurement data of the same sampling period.
Next, in step S1703, the shaft spring rigidity deriving unit 1602a derives a simple regression equation showing the relationship between the restoring force FR _i and the displacement DI _i based on the data set in the inspection section. The shaft spring rigidity derivation unit 1602a derives the regression coefficient α _i of the simple regression equation as the shaft spring stiffness k _{1, i} , k _{1, i + 1} in the inspection section.

Next, in step S1704, the determination unit 1603 determines the rigidity (spring constant) of the shaft springs 18L and 18R based on the shaft spring rigidity k _{1, i} and k _{1, i + 1} derived by the shaft spring state detection unit 1602. ) Is determined to be present. Then, the determination unit 1603 determines whether or not the rigidity (spring constant) of all the shaft springs 18L and 18R is normal.

As a result of this determination, if the rigidity (spring constant) of all the shaft springs 18L and 18R is normal, the process proceeds to step S1705. When the process proceeds to step S1705, the output unit 1604 outputs normal information including that the rigidity (spring constant) of all the shaft springs 18L and 18R is normal. When the process of step S1705 is completed, the process according to the flowchart of FIG. 17 is completed.

On the other hand, if the rigidity (spring constant) of at least one of the shaft springs 18L and 18R is abnormal as a result of the determination in step S1704, the process proceeds to step S1706. When the process proceeds to step S1706, the output unit 1604 outputs abnormal information including the presence of a shaft spring whose rigidity (spring constant) is determined to be abnormal. When the process of step S1706 is completed, the process according to the flowchart of FIG. 17 is completed.

<Calculation example>
Next, a calculation example will be described. Similar to the <calculation example> of the first embodiment, the present embodiment is based on the result of simulating (numerical analysis) the running of the railroad vehicle traveling at 270 km / hr, assuming that the moving state of the railroad vehicle has 86 degrees of freedom. Data corresponding to the measurement data in the form was acquired. Using the data acquired in this way, the shaft spring rigidity is derived by the method described in this embodiment, and the value set in the simulation is compared with the value obtained by the method described in this embodiment. did.

FIG. 18 is a diagram showing the relationship between the restoring force FR ₁ and the displacement DI ₁ when all the shaft springs 18L and 18R are normal. From the results of simulating all the shaft springs 18L and 18R as normal values, data corresponding to the measurement data in this embodiment was acquired. Using the data acquired in this way, a data set was created as described in the present embodiment. Of the data sets created in this way, when the data set for the front wheels (wheel sets 13a) of the front carriage 12a is plotted, each point shown in FIG. 18 is obtained. Based on the points obtained in this way, a simple regression equation was derived by the least squares method. Graph 1801 shown in FIG. 18 shows a simple regression equation derived in this way.

FIG. 19 shows the relationship between the restoring force FR ₁ and the displacement DI ₁ when the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheel set 13a) of the front bogie 12a is halved from the normal state. It is a figure which shows. Data corresponding to the measurement data in this embodiment was obtained from the result of simulating the rigidity (spring constant) of the left shaft spring 18L of the front wheel (wheel axle 13a) of the front bogie 12a as 1/2 times the normal value. Using the data acquired in this way, a data set was created as described in the present embodiment. Among the data sets created in this way, when the data set for the front wheels (wheel sets 13a) of the front carriage 12a is plotted, each point shown in FIG. 19 is obtained. Based on the points obtained in this way, a simple regression equation was derived by the least squares method. Graph 1901, shown in FIG. 19, shows a simple regression equation thus derived.

FIG. 20 shows the relationship between the restoring force FR ₁ and the displacement DI ₁ when the rigidity (spring constant) of the right shaft spring 18R of the front wheel (wheel set 13a) of the front bogie 12a is halved from the normal state. It is a figure which shows. From the result of simulating the rigidity (spring constant) of the shaft spring 18R on the right side of the front wheel (wheel axle 13a) of the front bogie 12a as 1/2 of the normal time, data corresponding to the measurement data in this embodiment was acquired. Using the data acquired in this way, a data set was created as described in the present embodiment. Among the data sets created in this way, when the data set for the front wheels (wheel sets 13a) of the front carriage 12a is plotted, each point shown in FIG. 20 is obtained. Based on the points obtained in this way, a simple regression equation was derived by the least squares method. Graph 2001 shown in FIG. 20 shows the simple regression equation thus derived.

When executing the simulation assuming that all the shaft springs 18L and 18R are normal, the value set in the simulation (the average of the rigidity (spring constant) of the shaft springs 18L and 18R of the front wheel (wheel axle 13a) of the front bogie 12a). Value) is used as the reference value.

The shaft spring rigidity k ₁ , ₁ in the inspection section derived from the graph 1801 shown in FIG. 18 was 103% (1.48 × 10 ⁶ N / m) of the reference value. Therefore, it can be seen that the method of the present embodiment can accurately estimate that the shaft springs 18L and 18R are normal.

Axial spring rigidity _{k 1, 1} in the test section is derived from the graph 1901 shown in Figure 19, it was 56% of the reference value ^{(8.00 × 10 5 N / m} ). The shaft spring stiffness _{k 1, 1} in the test section is derived from the graph 2001 shown in Figure 20, it was 69% of the reference value ^{(9.99 × 10 5 N / m} ). Therefore, it can be seen that the shaft spring rigidity k1 _{and i} in the inspection section derived by the method of the present embodiment show a remarkable difference between when the shaft springs 18L and 18R are normal and when they are abnormal. Therefore, it can be seen that the method of the present embodiment can reliably detect the abnormality of the shaft springs 18L and 18R.

<Summary>
As described above, in the present embodiment, the inspection device 1600 includes the displacement DI _i (= (z _{t, j −} aθ _{t, j −} z _{w, i} )) included in the left side of the equations (29) and (30). Multiple data including the value of (z _{t, j} + aθ _{t, j-} z _{w, i + 1} )) and the value of the restoring force FR _i , which is the calculated value on the right side of equations (29) and (30). Create a set. Eqs. (29) and (30) are the average values of the forces received by the left shaft spring 18L and the right shaft spring 18R arranged at intervals in the left-right direction, as in the equations (3) and (4). It is a mathematical formula that expresses.

Based on a plurality of data sets, the inspection device 1600 has a restoring force FR _{i represented} by the right side of the equations (29) and (30) and a displacement DI _i included in the left side of the equations (29) and (30). A simple regression equation representing the relationship with is derived, and the regression coefficients α _i representing the slope of the derived simple regression equation are derived as the axial spring stiffness k _{1, i} and k _{1, i + 1} in the inspection section.

Therefore, the shaft spring rigidity k _{1, i} and k _{1, i + 1} can be derived without calculating the equations (3) and (4). Therefore, the calculation load when deriving the shaft spring rigidity k _{1, i} and k _{1, i + 1} can be reduced.

In the method of the present embodiment, it is not possible to derive the time series data of the shaft spring rigidity k _{1, i} , k _{1, i + 1 in} the inspection section. Therefore, for example, when deriving the time series data of the shaft spring rigidity k _{1, i} , k _{1, i + 1} (corrected front shaft spring rigidity) in the inspection section, the method of the first embodiment is applied. On the other hand, for example, the axial spring rigidity _k 1 in the test interval, _{i, k 1, i + 1} of the time series data is not necessary to derive, to derive the axial spring rigidity _k 1, _{i, k 1, i + 1} in the test section When reducing the calculation load at the time, the method of the present embodiment is applied.
In addition, this embodiment may be applied to the second embodiment.

(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 present invention can be used, for example, for inspecting railway vehicles.

Claims (13)

1. It is an inspection system that inspects the state of the axle spring of a railroad vehicle having a vehicle body, a bogie, an axle, an axle box, and an axle spring.
   A data acquisition means for acquiring a measured value of a physical quantity measured by running the railway vehicle on a track, and
   It has a shaft spring state detecting means for detecting the state of the shaft spring of the railroad vehicle by using the measured value of the physical quantity acquired by the data acquisition means.
   The physical quantity whose measured value is acquired by the data acquisition means includes a force in the front-back direction.
   The front-rear direction force is a force in the front-rear direction generated in a member arranged between the wheel set and the carriage on which the wheel set is provided.
   The member is a member for supporting the axle box.
   An inspection system characterized in that the front-rear direction is a direction along a traveling direction of the railway vehicle.
2. The shaft spring state detecting means uses the sum of the measured values of the front-rear directional forces with respect to all the members arranged between the one bogie and the wheel axle to obtain the state of the shaft spring of the railroad vehicle. The inspection system according to claim 1, wherein the inspection system is used.
3. The shaft spring state detecting means further includes a shaft spring rigidity deriving means that derives the rigidity of the shaft spring as a physical quantity indicating the state of the shaft spring by using a mathematical formula expressing the force received by the shaft spring.
   The mathematical formula is derived based on the equation of motion representing the vertical movement of the trolley and the equation of motion representing the pitching of the trolley.
   The pitching is a motion of rotating around a left-right direction as a rotation axis.
   The vertical direction is a direction perpendicular to the orbit.
   The inspection system according to claim 1 or 2, wherein the left-right direction is a direction perpendicular to the orbit, which is a vertical direction, and a direction perpendicular to the front-rear direction.
4. The railroad vehicle further has a pillow spring and a shaft damper.
   The shaft spring state detecting means uses a mathematical formula expressing the force received by the shaft spring to indicate the state of the shaft spring by indicating the average value of the rigidityes of the two shaft springs arranged at intervals in the left-right direction. It also has a shaft spring rigidity derivation means to be derived as a physical quantity.
   The formula is the load received by the pillow spring, the average value of the forces received by the two shaft dampers arranged at intervals in the left-right direction, the moment of force received by the carriage from the shaft damper in pitching, and the above. Includes the gravity received by the trolley, the moment of force received by the trolley based on the front-rear force, the inertial force in the vertical direction of the trolley, and the sum of the moments of force received by the trolley due to pitching.
   The pitching is a motion of rotating around a left-right direction as a rotation axis.
   The vertical direction is a direction perpendicular to the orbit.
   The left-right direction is a direction perpendicular to the up-down direction and the front-back direction.
   The inspection system according to claim 1 or 2, wherein the physical quantity whose measured value is acquired by the data acquisition means further includes the internal pressure of the pillow spring and the vertical acceleration of the carriage.
5. The railroad vehicle further has a pillow spring and a shaft damper.
   The rigidity of the shaft spring derived by the shaft spring rigidity deriving means is an average value of the rigidity of two shaft springs arranged at intervals in the left-right direction.
   The formula is the average value of the load received by the pillow spring, the force received by the two shaft dampers arranged at intervals in the left-right direction, and the moment of force received by the carriage from the shaft damper in the pitching. , The gravity received by the trolley, the moment of the force received by the trolley based on the front-rear direction force, the inertial force of the trolley in the vertical direction, and the sum of the moments of the force received by the trolley due to the pitching. Including
   The inspection system according to claim 3, wherein the physical quantity whose measured value is acquired by the data acquisition means further includes the internal pressure of the pillow spring and the vertical acceleration of the carriage.
6. The formula further includes the centrifugal force received by the dolly.
   The inspection system according to claim 4 or 5, wherein the physical quantity whose measured value is acquired by the data acquisition means further includes a traveling speed of the railway vehicle.
7. When the physical quantity indicating the state of the shaft spring derived by using the formula exceeds a predetermined upper limit value, the shaft spring rigidity deriving means sets the value indicating the state of the shaft spring as the upper limit value, and the above-mentioned The sixth aspect of claim 6, wherein when the physical quantity indicating the state of the shaft spring derived by using the mathematical formula is less than a predetermined lower limit value, the value indicating the state of the shaft spring is set as the lower limit value. Inspection system.
8. The shaft spring state detecting means has a value indicating the state of the shaft spring so as to reduce noise included in the time series data of the physical quantity indicating the state of the shaft spring derived by the shaft spring rigidity deriving means. The inspection system according to any one of claims 3 to 7, further comprising a frequency component adjusting means for adjusting a frequency component of time-series data.
9. The frequency component adjusting means derives a coefficient in the modified self-return model using the time series data of the physical quantity indicating the state of the shaft spring derived by the shaft spring rigidity deriving means, and uses the derived coefficient. By modifying the physical quantity indicating the state of the shaft spring derived by the shaft spring rigidity derivation means, the frequency component of the signal of the physical quantity indicating the state of the shaft spring derived by the shaft spring rigidity derivation means can be obtained. Adjust and
   The modified autoregressive model is an expression expressing a predicted value of a physical quantity indicating the state of the shaft spring by using an actual value of a physical quantity indicating the state of the shaft spring and the coefficient with respect to the actual value.
   The coefficients are derived using an equation with the first matrix as the coefficient matrix and the autocorrelation vector as the constant vector.
   The autocorrelation vector contains the autocorrelation of the time series data of the physical quantity indicating the state of the shaft spring from 1 to m, which is the number of physical quantities indicating the state of the shaft spring used in the modified autoregressive model. Is a vector that
   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. wherein an s-number of the third matrix U _s and, matrix U is derived from _s sigma _s U _s ^T derived from the eigenvalues and orthogonal matrix U,
   The autocorrelation matrix is a matrix whose component is the autocorrelation of time series data of physical quantities indicating the state of the shaft spring 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 whose column component vector is the eigenvector of the autocorrelation matrix.
   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 8, 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.
10. Each of the shaft spring rigidity deriving means has an interval in the left-right direction based on a plurality of data sets including a displacement value included in the left side of the formula and a calculated value on the right side of the formula. Derived the average value of the rigidity of the two shaft springs lined up,
    In the formula, the product of the average value of the rigidity of the two shaft springs arranged at intervals in the left-right direction and the displacement is the left side, and the other constants and variables represented by the formula are the right side. Is a thing
    The displacement included in the left side of the formula is the average value of the displacements of the two shaft springs arranged at intervals in the left-right direction.
    Based on the plurality of data sets, the shaft spring rigidity deriving means derives a simple regression equation expressing the relationship between the restoring force, which is a calculated value on the right side of the equation, and the displacement included in the left side of the equation. Any one of claims 3 to 6, wherein the regression coefficient representing the slope of the derived simple regression equation is derived as the average value of the rigidity of the two shaft springs arranged at intervals in the left-right direction. The inspection system described in the section.
11. Claims 1 to 10 further include a determining means for determining whether or not the shaft spring is normal based on a physical quantity indicating the state of the shaft spring detected by the shaft spring state detecting means. The inspection system according to any one of the above.
12. It is an inspection method for inspecting the state of the axle spring of a railroad vehicle having a vehicle body, a bogie, an axle, an axle box, and an axle spring.
    A data acquisition process for acquiring measured values of physical quantities measured by running the railroad vehicle on a track, and
    It has a shaft spring state detection step of detecting the state of the shaft spring of the railroad vehicle by using the measured value of the physical quantity acquired by the data acquisition step.
    The physical quantity whose measured value is acquired by the data acquisition step includes a force in the front-back direction.
    The front-rear direction force is a force in the front-rear direction generated in a member arranged between the wheel set and the carriage on which the wheel set is provided.
    The member is a member for supporting the axle box.
    An inspection method characterized in that the front-rear direction is a direction along a traveling direction of the railway vehicle.
13. It is a program for causing a computer to execute a process for inspecting the state of a shaft spring of a railroad vehicle having a vehicle body, a bogie, a wheel set, an axle box, and a shaft spring.
    A data acquisition process for acquiring measured values of physical quantities measured by running the railroad vehicle on a track, and
    Using the measured value of the physical quantity acquired in the data acquisition step, a computer is made to execute a shaft spring state detection step of detecting the state of the shaft spring of the railroad vehicle.
    The physical quantity whose measured value is acquired by the data acquisition step includes a force in the front-back direction.
    The front-rear direction force is a force in the front-rear direction generated in a member arranged between the wheel set and the carriage on which the wheel set is provided.
    The member is a member for supporting the axle box.
    The program is characterized in that the front-rear direction is a direction along the traveling direction of the railway vehicle.

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