JP3779258B2 - Vehicle abnormality detection device and vehicle - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a vehicle that travels on a track such as a railway vehicle. In particular, in a vehicle having a vibration system in which a carriage part of a vehicle body is connected to a wheel shaft by a spring system, it is only possible to detect a track abnormality. In addition, it is possible to detect vehicle abnormalities with high accuracy, regardless of the track conditions. Outing Place as well as The present invention relates to a vehicle equipped with the device.
[0002]
[Prior art]
2. Description of the Related Art Various techniques have been developed for detecting on-line abnormalities and trolleys on-line based on the vibration of a running railway vehicle.
[0003]
For example, the abnormality detection device disclosed in Japanese Patent Laid-Open No. 63-192653 is mainly composed of a control device and a dolly acceleration sensor, and the control device is mounted on a certain vehicle. A cart acceleration sensor for detecting the acceleration of the vehicle is provided (see Patent Document 1).
[0004]
As shown in FIG. 8, the control device of this abnormality detection device acquires the acceleration of the cart detected by the cart acceleration sensor (step S11), and removes the noise of the acquired cart acceleration using a fast Fourier transform (FFT) or a filter. (Step S12). Next, the control device determines whether or not the acceleration of the carriage after removing the noise exceeds a predetermined threshold (step S13). If the acceleration of the carriage exceeds the predetermined threshold (“Yes” in step S13), On the other hand, it is determined that there is a “trolley abnormality” (step S14). On the other hand, if the predetermined threshold is not exceeded (“No” in step S13), it is determined that there is “no cart abnormality” (step S15).
[0005]
However, since the above-described abnormality detection device is a simple device that detects an abnormality of the carriage by determining the threshold value of the acceleration of the carriage, when a large acceleration disturbance is input to the wheel axis by a long rail welded part or a point passage, etc. In some cases, this was erroneously detected as a cart abnormality.
[0006]
For this reason, the abnormality detection device disclosed in Japanese Patent Application Laid-Open No. 2000-6807 includes a plurality of carriage acceleration sensors, and these carriage acceleration sensors are respectively provided on the carriages of each vehicle. Each bogie acceleration sensor is connected to a control device mounted on one vehicle in a series of linked vehicles by a lead-through line laid between the vehicles (see Patent Document 2).
[0007]
As shown in FIG. 9, the control device of this abnormality detection device acquires the acceleration of the cart detected by each cart acceleration sensor (here, the cart is assumed to be three) (steps S21, S22, and S23). ) In order to extract the vibration that each carriage receives from the track to the same extent, the phase of the vibration determined by the distance between the carriage and the running speed and the traveling speed is corrected (steps S24, S25, and S26). ). Next, the control device obtains the average value of the acceleration of the carriage after the phase correction (step S27), compares the average value with the acceleration of each carriage (steps S28, S31, and S34), If the values are approximate (“Yes” in steps S28, S31, and S34), it is determined that the corresponding carriage is “no abnormality” (steps S30, S33, and S36), and both values are determined. Is not approximate (“No” in steps S28, S31, and S34), it is determined that the corresponding carriage is “abnormal” (steps S29, S32, and S35).
[0008]
[Patent Document 1]
JP 63-192653 A (the second column, upper left column)
[Patent Document 2]
JP 2000-6807 A (page 2-3)
[0009]
[Problems to be solved by the invention]
However, in the abnormality detection device disclosed in the latter Japanese Patent Laid-Open No. 2000-6807, an abnormality is detected by comparing the detection values of the trolley acceleration sensors provided in each of the plurality of trolleys with these average values. Therefore, there is no problem as in the former JP-A-63-192653, and there is an advantage that an abnormality occurring in a specific carriage or track can be detected. A lead-through line for connecting to the control device is necessary, and there is a disadvantage that the entire abnormality detection device is complicated and expensive.
[0010]
The present invention has been made in view of the above situation, detects vibrations of both the bogie and the wheel shaft of the vehicle, and the cause of the vibration is in the bogie or the track based on the detected vibration values of the bogie and the wheel shaft. In addition to detecting track abnormalities, it is possible to detect vehicle abnormalities with high accuracy regardless of track conditions. Outing Place as well as It aims at providing the vehicle carrying this apparatus.
[0012]
[Means for Solving the Problems]
Book A vehicle abnormality detection device according to the invention is a vehicle abnormality detection device that detects vibration of a vehicle and detects abnormality of a vehicle and a track of the vehicle based on the detected vibration, and detects vibration of a vehicle carriage. Trolley vibration detecting means for detecting, wheel shaft vibration detecting means for detecting the vibration of the wheel shaft of the vehicle, the vibration value of the carriage detected by the cart vibration detecting means, and the vibration value of the wheel shaft detected by the wheel shaft vibration detecting means; And a specifying means for specifying whether the cause of the vibration is in the carriage or in the track.
[0013]
According to the above invention, by detecting the vibration of both the bogie and the wheel shaft of the vehicle, and identifying whether the cause of the vibration is in the bogie or the track based on the detected vibration value of the bogie and the wheel shaft, It is possible not only to detect the abnormality of the vehicle, but also to detect the abnormality of the carriage with high accuracy regardless of the state of the track. In addition, according to the present invention, it is possible to simplify the entire abnormality detection device, such as eliminating the need for a communication line such as a lead-through line between a plurality of vehicles in order to recognize the abnormality of the track, and to reduce the cost. Is possible.
[0014]
As an example of a specific configuration of the above invention, the abnormality of the track is detected by determining the threshold value of the vibration value of the detected wheel shaft, and the track is not abnormal and is detected in the same manner. A threshold value is determined for the vibration value of the carriage, and when the vibration value of the carriage exceeds the threshold value, an abnormality of the carriage is detected (see FIG. 2).
[0015]
In the present invention, the means for detecting the vibration of each of the carriage and the wheel shaft is a vehicle for each of the carriage and the wheel axle in order to facilitate the processing of the specifying means (for example, the control device) based on the detection result by the means. It is desirable to arrange or configure such that vibrations in the vertical direction and / or the horizontal direction are detected. For example, an acceleration sensor can be used as means for detecting the vibration.
[0016]
As another specific example of the above-mentioned invention, a normal carriage estimated using a physical model from the detected vibration value of the wheel shaft while detecting an abnormality of the track by determining a threshold value of the vibration value of the detected wheel shaft Is compared with the detected vibration value of the cart (see FIG. 3).
[0017]
According to this specific example, even when an abnormal vibration value of a track is detected due to a track disturbance, a normal bogie vibration value can be obtained by a physical model. It is easy to detect an abnormality in the vibration value of the carriage, and there is little possibility of erroneously detecting the carriage abnormality.
[0018]
Note that the parameters of the normal physical model used here are set in advance through experiments or the like.
[0019]
As another specific example of the above invention, the abnormality of the track is detected by determining the threshold value of the detected vibration value of the wheel shaft, and the carriage is detected by using the detected vibration value of the wheel shaft and the physical model for identification. The vibration value is estimated. Based on this estimated value and the detected vibration value of the carriage, the parameters of the physical model are identified online and updated. A normal parameter corresponding to this parameter is prepared in advance, and an abnormality of the carriage is detected by comparing the updated parameter with the normal parameter (see FIGS. 4 to 7).
[0020]
At this time, the parameter of the physical model for identification is a value corresponding to the target part for which abnormality is to be detected, and an initial value is set in advance.
[0021]
According to this specific example, since the abnormality of the carriage can be grasped in units of parameters, not only the recognition of the abnormality of the carriage but also the location of the abnormality of the carriage can be specified according to the parameter.
[0022]
Also, during online identification, it is determined whether or not the identification has converged. If the identification does not converge, it is recognized that the cart is abnormal. It is also possible to configure so as to specify (FIGS. 5 and 7).
[0023]
By configuring in this way, depending on the design of the physical model, due to an anomaly that occurred in a location that was not considered in this physical model, the estimated value and the vibration value of the detected carriage were greatly different, and identification failed. Even in this case, it is possible to detect at least the abnormality of the carriage.
[0024]
For this reason, only when the identification converges, it is also possible to compare parameters and identify an abnormal portion of the carriage.
[0025]
In each of the above inventions, the detected vibration values of the carriage and the wheel shaft are subjected to noise removal by passing a filter or fast Fourier transform as a pre-process prior to each process described above. It is desirable.
[0026]
Furthermore, the apparatus according to the present invention is applicable to a vehicle that travels on a track such as a railway vehicle, and particularly to a vehicle having a vibration system in which a bogie part of a vehicle body is connected to a wheel shaft by a spring system. It is desirable. The device according to the present invention may be mounted on one of a series of vehicles, or may be mounted on a plurality of vehicles.
[0027]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, the vehicle abnormality detection according to the present invention will be described. Outing The device will be specifically described with reference to the accompanying drawings.
[0028]
(First embodiment)
FIG. 1 is a diagram showing a hardware configuration of a vehicle abnormality detection device according to a first embodiment of the present invention. In FIG. 1, a vehicle to which the abnormality detection device according to the present embodiment is applied is shown as viewed from the front-rear direction. This vehicle is a general railway vehicle, and trucks 2 and 2 (only one of them is shown) are attached to the front and rear of the vehicle body 5 at two locations. Air springs 4, 4 are arranged on the left and right sides of the vehicle body 5 between the vehicle body 5 and each carriage 2. Further, a hydraulic damper 6 is provided between the vehicle body 5 and each carriage 2 for attenuating vibrations of the vehicle body 5 in the left-right direction with respect to the carriage 2. Two axles 1, 1 extending in the left-right direction and having wheels 1a, 1a at both ends thereof are attached via two springs 3, 3 on the left and right, respectively, at two front and rear positions below each carriage 2.
[0029]
As shown in FIG. 1, the abnormality detection device according to the present embodiment is mainly attached to a wheel shaft 1, a wheel shaft acceleration sensor 7 for detecting vibrations in the vertical direction and / or the left-right direction of the wheel shaft 1 by acceleration, and a carriage 2. Mounted on the vehicle 2 and detecting the vertical and / or horizontal vibrations of the cart 2 by acceleration, and a control device attached to the inside of the vehicle body 5 and connected to the wheel acceleration sensor 7 and the cart acceleration sensor 8 9 and.
[0030]
In the present embodiment, the wheel-axis acceleration sensor 7 and the bogie acceleration sensor 8 are each attached to one vehicle in a series of vehicles. However, in the present invention, a plurality of wheel-axis accelerations are provided in one vehicle. The sensor 7 and / or the bogie acceleration sensor 8 may be attached, and a lead-through line or the like is required, but it is also possible to attach it over a plurality of vehicles.
[0031]
The abnormality detection device according to the present embodiment has the hardware configuration as described above, and the control device 9 performs the abnormality detection processing according to the present invention in the procedure described below with reference to the flowchart of FIG. Is supposed to run.
[0032]
As shown in FIG. 2, the control device 9 acquires the acceleration of the wheel shaft 1 detected by the wheel shaft acceleration sensor 7 (step S100), and performs the fast Fourier transform processing (FFT) or the filter processing on the acquired acceleration of the wheel shaft 1 ( Step S101), the acquired acceleration noise is removed.
[0033]
Next, the control device 9 determines whether or not the acceleration of the wheel shaft 1 after noise removal exceeds a predetermined threshold (step S102), and if it exceeds (“Yes” in step S102), the vehicle It is determined that there is an abnormality in the traveling track, and information to that effect is output (step S103). On the other hand, when the acceleration of the wheel shaft 1 after noise removal does not exceed the predetermined threshold (“No” in step S102), the control device 9 determines that there is no abnormality in the track on which the vehicle is traveling.
[0034]
In parallel with the processing of steps S100 to S103, the control device 9 acquires the acceleration of the carriage 2 detected by the carriage acceleration sensor 8 (step S104), and the acquired acceleration of the carriage 2 is subjected to fast Fourier transform processing ( FFT) or filtering (step S105), and noise removal of the acquired acceleration is performed.
[0035]
Next, the control device 9 determines whether or not the acceleration of the carriage 2 after noise removal exceeds a predetermined threshold (step S106), and if not (“No” in step S106), the carriage 9 It is determined that there is no abnormality in the carriage 2 to which the acceleration sensor 8 is attached, and information to that effect is output (step S109).
[0036]
On the other hand, in the control device 9, the acceleration of the wheel shaft 1 after noise removal does not exceed the predetermined threshold (“No” in step S102), and the acceleration of the carriage 2 after noise removal exceeds the predetermined threshold It is determined whether or not the condition (Yes in step S106) is satisfied (step S107). Only when the condition is satisfied, it is determined that there is an abnormality in the carriage 2 to which the carriage acceleration sensor 8 is attached. Then, information to that effect is output (step S108).
[0037]
Each of the above threshold values is stored in advance in a memory provided in the control device 9. Further, the output in the above steps S103, S108, and S109 is notified to the user by, for example, providing the control device 9 with a display device, a printing device, and / or an alarm device such as lamps and buzzers. It is possible to implement it.
[0038]
(Second Embodiment)
The vehicle abnormality detection device according to the present embodiment has the same hardware configuration as that of the first embodiment, and the control device 9 has a procedure as described next with reference to the flowchart of FIG. Thus, the abnormality detection process according to the present invention is executed.
[0039]
As shown in FIG. 3, the control device 9 acquires the acceleration of the wheel shaft 1 detected by the wheel shaft acceleration sensor 7 (step S120), and performs the fast Fourier transform process (FFT) or the filter process on the acquired acceleration of the wheel shaft 1 ( Step S121), the acquired acceleration noise is removed.
[0040]
Next, the control device 9 determines whether or not the acceleration of the wheel shaft 1 after noise removal exceeds a predetermined threshold (step S122), and if it exceeds (“Yes” in step S122), the vehicle Is determined to be abnormal, and information to that effect is output (step S123). On the other hand, when the acceleration of the wheel shaft 1 after noise removal does not exceed the predetermined threshold (“No” in step S122), the control device 9 determines that there is no abnormality in the track on which the vehicle is traveling, Information to that effect is output (step S124).
[0041]
In parallel with the processing of steps S120 to S124, the control device 9 acquires the acceleration of the carriage 2 detected by the carriage acceleration sensor 8 (step S125), and the acquired acceleration of the carriage 2 is subjected to a fast Fourier transform process ( FFT) or filtering (step S126), and noise removal of the acquired acceleration is performed.
[0042]
Next, the control device 9 estimates the acceleration of the carriage 2 using a physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2 in a normal state (step S127). It is determined whether or not the estimated value approximates the acceleration of the carriage 2 after noise removal (step S128).
[0043]
When the estimated acceleration of the carriage 2 and the acceleration of the carriage 2 after noise removal are not approximate (“No” in step S128), the control device 9 causes the carriage 2 to which the carriage acceleration sensor 8 is attached. Is determined to be abnormal, and information to that effect is output (step S129). On the other hand, if approximate ("Yes" in step S128), the control device 9 determines that there is no abnormality in the cart 2 to which the cart acceleration sensor 8 is attached, and outputs information to that effect. (Step S130).
[0044]
Other configurations and operations of the present embodiment are the same as those of the first embodiment described above, and the same parts are denoted by the same reference numerals and detailed description thereof is omitted.
[0045]
(Third embodiment)
The vehicle abnormality detection device according to the present embodiment has the same hardware configuration as that of the first embodiment, and the control device 9 has a procedure as described next with reference to the flowchart of FIG. Thus, the abnormality detection process according to the present invention is executed.
[0046]
As shown in FIG. 4, the control device 9 acquires the acceleration of the wheel shaft 1 detected by the wheel shaft acceleration sensor 7 (step S150), and performs the fast Fourier transform processing (FFT) or the filter processing on the acquired acceleration of the wheel shaft 1 ( Step S151), the acquired acceleration noise is removed.
[0047]
Next, the control device 9 determines whether or not the acceleration of the wheel shaft 1 after noise removal exceeds a predetermined threshold (step S152), and if it exceeds (“Yes” in step S152), the vehicle It is determined that there is an abnormality in the traveling track, and information to that effect is output (step S153). On the other hand, if the acceleration of wheelset 1 after noise removal does not exceed the predetermined threshold (“No” in step S152), it is determined that there is no abnormality in the track on which the vehicle is traveling, and information to that effect Is output (step S154).
[0048]
In parallel with the processing of steps S150 to S154, the control device 9 acquires the acceleration of the carriage 2 detected by the carriage acceleration sensor 8 (step S155), and the acquired acceleration of the carriage 2 is subjected to a fast Fourier transform process ( FFT) or filtering (step S156), and noise removal of the acquired acceleration is performed.
[0049]
Next, the control device 9 estimates the acceleration of the carriage 2 based on the identification parameters, using the identification physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2. (Step S157). Then, the control device 9 performs online identification of the parameter based on the estimated value and the acceleration of the carriage 2 after noise removal (step S158), and updates the parameter (step S159). An appropriate initial value is set in advance for the identification parameter prior to the start of the entire process.
[0050]
When the parameters are updated, the control device 9 reads the normal parameters (step S160), compares the identification parameters with the corresponding normal parameters (step S161), and if there is a mismatch (“No match” in step S161), it is determined that there is an abnormality in the portion of the carriage 2 corresponding to the parameter that does not match (that is, which part of the carriage 2 is abnormal), While specifying, information to that effect is output (step S162). On the other hand, when all the parameters match (“match” in step S161), the control device 9 determines that there is no abnormality in the cart 2 to which the cart acceleration sensor 8 is attached. Information is output (step S163). The normal parameters are set in advance through experiments or the like.
[0051]
Other configurations and operations of the present embodiment are the same as those of the first embodiment described above, and the same parts are denoted by the same reference numerals and detailed description thereof is omitted.
[0052]
(Fourth embodiment)
The vehicle abnormality detection device according to the present embodiment has the same hardware configuration as that of the first embodiment, and the control device 9 has a procedure as described below using the flowchart of FIG. Thus, the abnormality detection process according to the present invention is executed. Note that the abnormality detection process according to the present embodiment is different from the abnormality detection process according to the third embodiment in that parameter comparison is performed when identification converges.
[0053]
As shown in FIG. 5, the control device 9 acquires the acceleration of the wheel shaft 1 detected by the wheel shaft acceleration sensor 7 (step S170), and performs the fast Fourier transform process (FFT) or the filter process on the acquired acceleration of the wheel shaft 1 ( Step S171), noise removal of the acquired acceleration is performed.
[0054]
Next, the control device 9 determines whether or not the acceleration of the wheel shaft 1 after noise removal exceeds a predetermined threshold (step S172). If it exceeds (“Yes” in step S172), the control device 9 It is determined that there is an abnormality in the traveling track, and information to that effect is output (step S173). On the other hand, if the acceleration of wheelset 1 after noise removal does not exceed the predetermined threshold (“No” in step S172), it is determined that there is no abnormality in the track on which the vehicle is traveling, and information to that effect Is output (step S174).
[0055]
In parallel with the processing of steps S170 to S174, the control device 9 acquires the acceleration of the carriage 2 detected by the carriage acceleration sensor 8 (step S175), and the acquired acceleration of the carriage 2 is subjected to a fast Fourier transform process (step S175). FFT) or filtering (step S176), and noise removal of the acquired acceleration is performed.
[0056]
Next, the control device 9 estimates the acceleration of the carriage 2 based on the identification parameters, using the identification physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2. (Step S177). Then, the control device 9 performs online identification of the parameter based on the estimated value and the acceleration of the carriage 2 after noise removal (step S178), and updates the parameter (step S179). An appropriate initial value is set in advance for the identification parameter prior to the start of the entire process.
[0057]
The control device 9 also determines whether or not the identification has converged during online identification in step S178 (step S181). If the identification has not converged (“No” in step S181), the parameter Since the update cannot be performed normally, and therefore, the location of the abnormality described later cannot be performed normally, it is determined that there is an abnormality in the carriage 2 to which the carriage acceleration sensor 8 is attached, and only information to that effect is output ( Step S182).
[0058]
On the other hand, when the identification converges (“Yes” in step S181), the control device 9 reads the normal parameters (step S180), and compares the identification parameters with the corresponding normal parameters. (Step S183) If there is something that does not match ("mismatch" in Step S183), it is determined that there is an abnormality in the portion of the carriage 2 corresponding to the parameter that does not match (that is, which part of the carriage 2 is abnormal) It is determined whether or not there is, and information indicating that is output while identifying the abnormal part (step S184). On the other hand, when all the parameters match (“match” in step S183), the control device 9 determines that there is no abnormality in the cart 2 to which the cart acceleration sensor 8 is attached. Information is output (step S185).
[0059]
Other configurations and operations of the present embodiment are the same as those of the first embodiment described above, and the same parts are denoted by the same reference numerals and detailed description thereof is omitted.
[0060]
(Fifth embodiment)
The vehicle abnormality detection device according to the present embodiment has the same hardware configuration as that of the first embodiment, and the control device 9 has a procedure as described next with reference to the flowchart of FIG. Thus, the abnormality detection process according to the present invention is executed.
[0061]
As shown in FIG. 6, the control device 9 acquires the acceleration of the wheel shaft 1 detected by the wheel shaft acceleration sensor 7 (step S190), and performs the fast Fourier transform process (FFT) or the filter process on the acquired acceleration of the wheel shaft 1 ( Step S191), the acquired acceleration noise is removed.
[0062]
Next, the control device 9 determines whether or not the acceleration of the wheel shaft 1 after noise removal exceeds a predetermined threshold value (step S192). If it exceeds (“Yes” in step S192), the control device 9 Is determined to be abnormal, and information to that effect is output (step S193). On the other hand, if the acceleration of wheelset 1 after noise removal does not exceed the predetermined threshold (“No” in step S192), it is determined that there is no abnormality in the track on which the vehicle is traveling, and information to that effect Is output (step S194).
[0063]
In parallel with the processing of steps S190 to S194, the control device 9 acquires the acceleration of the carriage 2 detected by the carriage acceleration sensor 8 (step S195), and the acquired acceleration of the carriage 2 is subjected to fast Fourier transform processing ( FFT) or filter processing (step S196), and noise removal of the acquired acceleration is performed.
[0064]
Next, the control device 9 estimates the acceleration of the carriage 2 based on the identification parameters, using the identification physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2. (Step S197). Then, the control device 9 performs online identification of the parameter based on the estimated value and the acceleration of the carriage 2 after noise removal (step S198), and updates the parameter (step S199). An appropriate initial value is set in advance for the identification parameter prior to the start of the entire process.
[0065]
Further, the control device 9 estimates the acceleration of the carriage 2 using a physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2 in a normal state (step S201). It is determined whether or not the value approximates the acceleration of the carriage 2 after noise removal (step S202).
[0066]
When the estimated normal acceleration of the carriage 2 and the acceleration of the carriage 2 after noise removal are approximate (“Yes” in step S202), the control device 9 has the carriage acceleration sensor 8 attached. It is determined that there is no abnormality in the existing cart 2 and information to that effect is output (step S205).
[0067]
On the other hand, if the estimated normal acceleration of the carriage 2 and the acceleration of the carriage 2 after noise removal are not approximate (“No” in step S202), the control device 9 reads the normal parameters. (Step S200), the identification parameters are respectively compared with the corresponding normal parameters (Step S203), and if there is a mismatch ("mismatch" in Step S203), the cart corresponding to the mismatched parameter It is determined that there is an abnormality in the portion 2 (that is, it is determined which part of the carriage 2 is abnormal), and information indicating that is output while identifying the abnormal part (step S204). On the other hand, when all the parameters match (“match” in step S203), the control device 9 determines that there is no abnormality in the cart 2 to which the cart acceleration sensor 8 is attached. Information is output (step S205).
[0068]
Other configurations and operations of the present embodiment are the same as those of the first embodiment described above, and the same parts are denoted by the same reference numerals and detailed description thereof is omitted.
[0069]
(Sixth embodiment)
The vehicle abnormality detection device according to the present embodiment has the same hardware configuration as that of the first embodiment, and the control device 9 has a procedure as described next with reference to the flowchart of FIG. Thus, the abnormality detection process according to the present invention is executed. The abnormality detection process according to the present embodiment is different from the abnormality detection process according to the fifth embodiment in that parameter comparison is performed when the identification is converged.
[0070]
As shown in FIG. 7, the control device 9 acquires the acceleration of the wheel shaft 1 detected by the wheel shaft acceleration sensor 7 (step S210), and performs the fast Fourier transform process (FFT) or the filter processing on the acquired acceleration of the wheel shaft 1 ( Step S211), the acquired acceleration noise is removed.
[0071]
Next, the control device 9 determines whether or not the acceleration of the wheel shaft 1 after noise removal exceeds a predetermined threshold (step S212), and if it exceeds (“Yes” in step S212), the control device 9 It is determined that there is an abnormality in the traveling track, and information to that effect is output (step S213). On the other hand, if the acceleration of wheelset 1 after noise removal does not exceed the predetermined threshold (“No” in step S212), it is determined that there is no abnormality in the track on which the vehicle is traveling, and information to that effect Is output (step S214).
[0072]
In parallel with the processing in steps S210 to S214, the control device 9 acquires the acceleration of the carriage 2 detected by the carriage acceleration sensor 8 (step S215), and the acquired acceleration of the carriage 2 is subjected to a fast Fourier transform process ( FFT) or filtering (step S216), and noise removal of the acquired acceleration is performed.
[0073]
Next, the control device 9 estimates the acceleration of the carriage 2 based on the identification parameters, using the identification physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2. (Step S217). Then, the control device 9 performs online identification of the parameter based on the estimated value and the acceleration of the carriage 2 after noise removal (step S218), and updates the parameter (step S219). An appropriate initial value is set in advance for the identification parameter prior to the start of the entire process.
[0074]
In addition, the control device 9 estimates the acceleration of the carriage 2 using a physical model that receives the acceleration of the wheel shaft 1 after noise removal and outputs the acceleration of the carriage 2 in a normal state (step S221). It is determined whether or not the value approximates the acceleration of the carriage 2 after noise removal (step S222).
[0075]
When the estimated normal acceleration of the carriage 2 and the acceleration of the carriage 2 after noise removal are approximate (“Yes” in step S222), the control device 9 has the carriage acceleration sensor 8 attached. It is determined that there is no abnormality in the existing cart 2 and information to that effect is output (step S227).
[0076]
On the other hand, when the estimated acceleration of the carriage 2 at normal time and the acceleration of the carriage 2 after noise removal are not approximate (“No” in step S222), the control device 9 performs the online identification in step S218. At this time, it is determined whether or not the identification has converged (step S223). If the identification has not converged (“No” in step S223), the parameter cannot be updated normally, and therefore, an abnormal point described later. Therefore, it is determined that there is an abnormality in the carriage 2 to which the carriage acceleration sensor 8 is attached, and only information to that effect is output (step S226).
[0077]
On the other hand, when the identification converges (“Yes” in step S223), the control device 9 reads the normal parameters (step S220), and compares the identification parameters with the corresponding normal parameters. (Step S224) If there is something that does not match ("mismatch" in Step S224), it is determined that there is an abnormality in the portion of the carriage 2 corresponding to the parameter that does not match (that is, which part of the carriage 2 is abnormal) It is determined whether or not there is an error), and information indicating that is output while identifying the abnormal part (step S225). On the other hand, when all the parameters match (“match” in step S224), the control device 9 determines that there is no abnormality in the cart 2 to which the cart acceleration sensor 8 is attached. Information is output (step S227).
[0078]
Other configurations and operations of the present embodiment are the same as those of the first embodiment described above, and the same parts are denoted by the same reference numerals and detailed description thereof is omitted.
[0079]
【The invention's effect】
Vehicle abnormality detection according to the present invention Outing Place as well as According to the vehicle, by detecting the vibration of both the bogie and the wheel shaft of the vehicle, and identifying whether the cause of the vibration is in the bogie or the track based on the detected vibration value of both the bogie and the wheel shaft, Not only can the abnormality of the track be detected, but also the abnormality of the carriage can be detected with high accuracy regardless of the state of the track.
[Brief description of the drawings]
FIG. 1 is a diagram showing an example in which an abnormality detection apparatus according to a first embodiment of the present invention is applied to a vehicle.
FIG. 2 is a flowchart showing a processing procedure by the control device of the vehicle abnormality detection device according to the first embodiment.
FIG. 3 is a flowchart showing a processing procedure by a control device of a vehicle abnormality detection device according to a second embodiment.
FIG. 4 is a flowchart showing a processing procedure by a control device of a vehicle abnormality detection device according to a third embodiment.
FIG. 5 is a flowchart showing a processing procedure by a control device of a vehicle abnormality detection device according to a fourth embodiment.
FIG. 6 is a flowchart showing a processing procedure by a control device of a vehicle abnormality detection device according to a fifth embodiment.
FIG. 7 is a flowchart showing a processing procedure by a control device of a vehicle abnormality detection device according to a sixth embodiment.
FIG. 8 is a flowchart showing a processing procedure performed by a control device of a conventional vehicle abnormality detection device.
FIG. 9 is a flowchart showing a processing procedure by a control device of another conventional abnormality detection device.
[Explanation of symbols]
1 Wheel axle
2 carts
3 Spring
5 body
7 Wheel axis acceleration sensor
8 bogie acceleration sensor
9 Control unit

Claims (6)

Based on the detected vibration, a vibration of a railway vehicle having a wheel shaft, a cart connected to the wheel shaft via a shaft spring, and a vehicle body connected to the cart via an air spring and a left-right motion damper is detected. A vehicle abnormality detection device for detecting an abnormality in a vehicle and a track on which the vehicle travels ,
Trolley vibration detecting means for detecting left and right vibration of the trolley of the vehicle;
Wheel shaft vibration detecting means for detecting left and right vibration of the wheel shaft of the vehicle;
Identification means for identifying whether the cause of vibration is in the carriage or in the track based on the vibration value of the carriage detected by the carriage vibration detection means and the vibration value of the wheel shaft detected by the wheel shaft vibration detection means. And
The specifying means determines whether or not the vibration value detected by the wheel shaft vibration detecting means exceeds a predetermined threshold value, and if the vibration value of the wheel shaft exceeds a predetermined threshold value, the cause of the vibration is in the track while specific inputs the vibration value of the wheel axis, the damping coefficient of the previous Kihidari rightward movement damper bogie vibration system model for identification and outputs vibration value of the bogie, the detected vibration values by the carriage vibration detecting means Based on the online identification, it is determined whether or not the identified coefficient approximates the coefficient at the normal time, and if it is not approximated, the cause of the vibration should be identified as the cart A vehicle abnormality detection device. When determining whether or not the identified coefficient approximates a normal coefficient, the specifying means, based on the type of coefficient that is not approximated, the abnormal location of the carriage, the air spring, the shaft spring, The vehicle abnormality detection device according to claim 1 , wherein the vehicle abnormality detection device is specified as one of the left and right motion dampers. The identification means determines whether or not the identification has converged when performing online identification.If the identification does not converge, the identification means identifies that the cause of the vibration is in the carriage, and approximates when the identification has converged. based on the type of no factor, said air spring the anomaly of the carriage, the shaft spring or vehicle according to claim 1 or 2, characterized in that are no in order to identify any of the lateral movement damper, Anomaly detection device. Each vibration value used in a specific section, respectively, after being detected by the detection means, the vehicle according to any one of claims 1 to 3, characterized in that through the filter abnormality detection apparatus. Each vibration value used in a specific section, respectively, after being detected by the detection means, the vehicle abnormality detection according to any one of claims 1 to 3, characterized in that is obtained by fast Fourier transform apparatus. A vehicle comprising the vehicle abnormality detection device according to any one of claims 1 to 5 .

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