Monitoring device, monitoring method, and program

Abstract

To provide a monitoring device, a monitoring method, and a program capable of monitoring a measured value appropriately.SOLUTION: A monitoring device includes: a nonlinear expanding and contracting unit in which a measured waveform is expanded / contracted nonlinearly based on a distance between each measured value of a measured waveform and each reference measured value of a reference waveform; and a determination unit determining whether or not there is abnormality in the measured waveform based on a predetermined value obtained by expanding / contacting the measured waveform nonlinearly.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a monitoring device, a monitoring method, and a program. [Background technology]

[0002] For example, when an accelerometer is attached to a vehicle to acquire acceleration data during travel and monitor the vehicle and track conditions, it is necessary to accurately determine the vehicle's position. Patent Document 1 describes an example of a train position determination method. The train position determination method described in Patent Document 1 includes the steps of acquiring curvature measurement data, extracting a portion of stored curvature data where the deviation from the curvature measurement data is minimum, and obtaining the deviation between the extracted portion and the curvature measurement data as a minimum deviation value. If the minimum deviation value is equal to or less than a threshold, the train's position is determined based on the distance position at the portion where the deviation value is minimum. If the minimum deviation value exceeds the threshold, the train's position is determined based on the running distance calculated from the running speed obtained from the axle rotation speed. That is, in the train position determination method described in Patent Document 1, the position is determined based on the curvature comparison result in sections where it is easy to compare the stored curvature data with the curvature measurement data, and the position is determined based on the axle rotation speed in sections where it is not easy. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-19333 Summary of the Invention [Problem to be solved by the invention]

[0004] When determining the position using the train position determination method described in Patent Document 1, in sections where it is not easy to determine the position based on the results of curvature matching, the position is determined based on the axle rotation speed. Therefore, in sections where it is not easy to determine the position based on the results of curvature matching, for example, when it is difficult to determine the accurate position from the integral of the axle rotation speed due to an error in the distance per axle rotation or wheel slippage, the position cannot be determined with high accuracy. When the position cannot be determined with high accuracy, for example, when monitoring measurement values ​​by comparing them with reference values, there is a problem in that the measurement values ​​may not be monitored appropriately.

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a monitoring device, a monitoring method, and a program that can appropriately monitor measurement values. [Means for solving the problem]

[0006] In order to solve the above problem, the monitoring device of the present disclosure includes a nonlinear stretching unit that stretches the measured waveform nonlinearly based on the distance between each measured value of the measured waveform and each reference measured value of a reference waveform, and a judgment unit that judges whether or not there is an abnormality in the measured waveform based on a predetermined value obtained by nonlinearly stretching the measured waveform.

[0007] The monitoring method disclosed herein includes a step of nonlinearly stretching or shrinking the measured waveform based on the distance between each measured value of the measured waveform and each reference measured value of a reference waveform, and a step of determining whether or not there is an abnormality in the measured waveform based on a predetermined value obtained by nonlinearly stretching or shrinking the measured waveform.

[0008] The program of the present disclosure causes a computer to execute the steps of nonlinearly stretching or shrinking the measured waveform based on the distance between each measured value of the measured waveform and each reference measured value of a reference waveform, and determining whether or not there is an abnormality in the measured waveform based on a predetermined value obtained by nonlinearly stretching or shrinking the measured waveform. [Effects of the Invention]

[0009] According to the monitoring device, monitoring method, and program of the present disclosure, it is possible to appropriately monitor measurement values. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram for explaining a configuration example of an acceleration monitoring device according to a first embodiment of the present disclosure. [Figure 2] 2 is a side view showing an example of installation of acceleration sensor 32 (acceleration sensors 32a to 32c) in vehicle 3 (vehicles 3a to 3c) shown in FIG. [Figure 3] FIG. 2 is a plan view schematically illustrating an example configuration of a track according to an embodiment of the present disclosure. [Figure 4] 2 is a schematic diagram showing an example of the configuration of a reference acceleration waveform database 261 shown in FIG. 1. FIG. [Figure 5] 2 is a schematic diagram showing an example of the configuration of a measured acceleration waveform database 263 shown in FIG. 1. FIG. [Figure 6] 1 is a schematic diagram for explaining an example of operation of an acceleration monitoring device according to an embodiment of the present disclosure. FIG. [Figure 7] 2 is a schematic diagram showing an example of the configuration of a monitoring result database 265 shown in FIG. 1. FIG. [Figure 8] 4 is a flowchart showing an example of operation of the acceleration monitoring device according to the first embodiment of the present disclosure. [Figure 9] 3A to 3C are schematic diagrams for explaining an example of the operation of the acceleration monitoring device according to the first embodiment of the present disclosure. [Figure 10] 10 is a flowchart showing an example of operation of the acceleration monitoring device according to the second embodiment of the present disclosure. [Figure 11] FIG. 10 is a block diagram showing a configuration example of an acceleration monitoring device according to a third embodiment of the present disclosure. [Figure 12] FIG. 11 is a schematic diagram showing an example of the configuration of a measured acceleration waveform database according to a third embodiment of the present disclosure. [Figure 13] 10 is a flowchart showing an example of operation of the acceleration monitoring device according to the third embodiment of the present disclosure. [Figure 14]FIG. 10 is a schematic diagram for explaining an example of operation of the acceleration monitoring device according to the third embodiment of the present disclosure. [Figure 15] 10A and 10B are waveform diagrams for explaining the effects of the acceleration monitoring device according to the embodiment of the present disclosure. [Figure 16] FIG. 10 is a waveform diagram (comparative example) for explaining the action and effect of the acceleration monitoring device according to the embodiment of the present disclosure. [Figure 17] FIG. 1 is a schematic block diagram illustrating the configuration of a computer according to at least one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, a monitoring device, a monitoring method, and a program according to an embodiment of the present disclosure will be described with reference to the drawings. Note that the same or corresponding components in each drawing are designated by the same reference numerals and descriptions thereof will be omitted as appropriate.

[0012] First Embodiment A monitoring device, a monitoring method, and a program according to a first embodiment of the present disclosure will be described below with reference to FIGS. 1 to 9, 15, and 16. FIG. 1 is a block diagram illustrating an example configuration of an acceleration monitoring device according to a first embodiment of the present disclosure. FIG. 2 is a side view illustrating an example installation of acceleration sensors 32 (acceleration sensors 32a to 32c) in vehicles 3 (vehicles 3a to 3c) shown in FIG. 1. FIG. 3 is a plan view schematically illustrating an example configuration of a track according to an embodiment of the present disclosure. FIG. 4 is a schematic diagram illustrating an example configuration of a reference acceleration waveform database 261 shown in FIG. 1. FIG. 5 is a schematic diagram illustrating an example configuration of a measured acceleration waveform database 263 shown in FIG. 1. FIG. 6 is a schematic diagram illustrating an example operation of an acceleration monitoring device according to an embodiment of the present disclosure. FIG. 7 is a schematic diagram illustrating an example configuration of a monitoring result database 265 shown in FIG. 1. FIG. 8 is a flowchart illustrating an example operation of an acceleration monitoring device according to a first embodiment of the present disclosure. FIG. 9 is a schematic diagram illustrating an example operation of an acceleration monitoring device according to a first embodiment of the present disclosure. FIG. 15 is a waveform diagram illustrating the effects of an acceleration monitoring device according to an embodiment of the present disclosure. FIG. 16 is a waveform diagram (comparative example) for explaining the action and effect of the acceleration monitoring device according to the embodiment of the present disclosure.

[0013] (Configuration of acceleration monitoring device 2) The acceleration monitoring device 2 shown in Figure 1 is one example of the configuration of a monitoring device according to the present disclosure. The acceleration monitoring device 2 is an example of a monitoring device in which the measurement waveform according to the present disclosure is an acceleration waveform measured by a vehicle traveling on a track. However, the measurement waveform according to the present disclosure is not limited to an acceleration waveform measured by a vehicle traveling on a track. The monitoring device according to the present disclosure can be applied to any measurement waveform that is a time series of measurement values.

[0014] The acceleration monitoring device 2 is configured as, for example, one element of a rubber-tired new transit system (AGT: Automated Guideway Transit) 1. The rubber-tired new transit system 1 shown in FIG. 1 includes, for example, the acceleration monitoring device 2, a plurality of vehicles 3, a plurality of ground devices 4, and an operation management device 5.

[0015] The traffic management device 5 is a device that controls the operation of a plurality of trains consisting of a plurality of vehicles 3, and transmits and receives predetermined control signals to and from the vehicles 3 via the ground equipment 4. The ground equipment 4 relays communication between the traffic management device 5 and the vehicles 3, for example.

[0016] In this embodiment, the vehicle 3 travels on track T1 shown in FIG. 3 as an example. Track T1 has two travel lanes DL1 and DL2, each with a predetermined travel direction. Track T1 also has stations ST1 and ST2. In this case, one section SEC1 extends from station ST1 to station ST2. Two regions of interest RI1 and RI2, which are portions of track T1, are defined in advance. In this embodiment, a region of interest is an area in which accelerations occurring in that region are monitored. In the example shown in FIG. 3, the regions of interest RI1 and RI2 are areas surrounding the expansion joints EJ1 and EJ2, respectively. Relatively large accelerations occur on track T1 at steps at expansion joints and other locations, and at branch points (not shown).

[0017] 1, the vehicle 3 includes an on-board device 31, one or more acceleration sensors 32, and a location identification information acquisition device 33. The on-board device 31 includes a control unit 311, a storage unit 312, and a communication unit 313 as a functional configuration formed by a combination of hardware and software.

[0018] In the on-board equipment 31, the control unit 311 automatically controls a power source such as a motor, a steering device, boarding and alighting devices, and the like (not shown) equipped on the vehicle 3, based on a control signal received by the communication unit 313 from the traffic management device 5 via the wayside equipment 4. The control unit 311 also acquires acceleration detected by the acceleration sensor 32 at a predetermined sampling period, stores it in the memory unit 313, and transmits it to the traffic management device 5 via the wayside equipment 4 at a predetermined timing via the communication unit 313. The control unit 311 also acquires position identification information identified by the position identification information acquisition device 33 at a predetermined sampling period, stores it in the memory unit 313, and transmits it to the traffic management device 5 via the wayside equipment 4 at a predetermined timing via the communication unit 313. The on-board equipment 31, for example, transmits time-series data output by the acceleration sensor 32 and time-series data output by the position identification information acquisition device 33, acquired over one section between stations, together to the traffic management device 5 via the wayside equipment 4 upon arrival at a station. However, the timing of transmitting the acceleration data and the position identification information is not limited to this.

[0019] The acceleration sensor 32 detects, for example, triaxial acceleration and outputs the detection results to the control unit 311. The position identification information acquisition device 33 acquires information for identifying the position of the vehicle 3 and outputs the information to the control unit 311. The position identification information acquisition device 33 acquires, for example, a signal corresponding to the rotation speed of tires 302 (FIG. 2) provided on the vehicle 3 and outputs a signal representing the speed of the vehicle 3 as position identification information. Alternatively, the position identification information acquisition device 33 acquires latitude and longitude representing the current position obtained by receiving radio waves emitted by satellites of the Global Positioning System (GPS) and outputs the latitude and longitude as position identification information.

[0020] A plurality of acceleration sensors 32 may be attached to each of the cars 3a to 3c constituting the train 30, as shown in FIG. 2 as acceleration sensors 32a to 32c. In the example shown in FIG. 2, two bogies 303 of each of the cars 3a to 3c are attached with acceleration sensors 32a and 32c, respectively. Furthermore, an acceleration sensor 32b is attached to each carbody 301 of each of the cars 3a to 3c. In this case, the acceleration sensors 32a to 32c detect acceleration in three axes, for example, forward / backward, left / right, and up / down, and output signals representing the detected acceleration. However, the acceleration measured may be in any one or two directions, rather than all three directions. The bogie 303 rotatably supports rubber tires 302 and is attached to the carbody 301 via shock absorbers 304 such as air springs. In the example shown in FIG. 2, the car 3a is provided with an on-board device 31 and a location information acquisition device 33.

[0021] On the other hand, the acceleration monitoring device 2 is composed of, for example, a computer and its peripheral devices and peripheral circuits, and has the following functional components formed by a combination of hardware such as a computer and software such as a program executed by the computer. That is, the acceleration monitoring device 2 has, as its functional components, a control unit 21, a communication unit 22, an acquisition unit 23, a monitoring unit 24, a database management unit 25, and a storage unit 26. The monitoring unit 24 also has a nonlinear expansion / contraction unit 241 and a determination unit 242.

[0022] The storage unit 26 also stores a reference acceleration waveform database 261 , a plurality of reference acceleration waveform files 262 , a measured acceleration waveform database 263 , a plurality of measured acceleration waveform files 264 , and a monitoring result database 265 .

[0023] The reference acceleration waveform database 261 is information for managing information related to reference acceleration waveforms, which are acceleration waveforms that serve as a reference for measured acceleration waveforms, which are acceleration waveforms newly measured in each vehicle 3 to be monitored. The reference acceleration waveforms are, for example, acceleration waveforms measured in each region of interest (region of interest RI1, region of interest RI2, etc.) by a standard vehicle 3. FIG. 4 shows an example of the configuration of the reference acceleration waveform database 261. The reference acceleration waveform database 261 shown in FIG. 4 stores, in association with each other, a region of interest identification code, a vehicle identification code, a section identification code, a driving lane identification code, an acceleration sensor identification code, a measurement position, a measurement direction, a positive peak / negative peak / effective value, and a reference acceleration waveform file name. The region of interest identification code is a code that uniquely identifies the region of interest shown in FIG. 3. The vehicle identification code is a code that uniquely identifies the vehicle 3 that measured the reference acceleration waveform. The section identification code is a code that uniquely identifies the section in which the region of interest is located. The travel lane identification code is a code that uniquely identifies the travel lane in which the vehicle 3 that measured the data traveled. The acceleration sensor identification code is a code that uniquely identifies the acceleration sensor 32 that measured the data or identifies each vehicle 3 individually. The measurement position indicates whether the measurement is on the carbody side (sprung) or the bogie side (unsprung) of the shock absorber 304 (spring). The measurement direction indicates whether the acceleration direction is up-down, back-and-forth, or left-and-right. The positive peak / negative peak / effective value are the positive peak value, negative peak value, and effective value of the reference acceleration waveform. The reference acceleration waveform file name is the name of the reference acceleration waveform file 262 that represents the reference acceleration waveform. Row C1 of the reference acceleration waveform database 261 shown in FIG. 4 corresponds, for example, to the reference acceleration waveform AWB1 (file name "FB001") measured in the region of interest RI1 shown in FIG. 3. 3. Row C2 of the reference acceleration waveform database 261 shown in FIG. 4 corresponds to, for example, the reference acceleration waveform AWB2 (file name "FB201") measured in the region of interest RI2 shown in FIG.

[0024] The reference acceleration waveform file 262 is a file representing the reference acceleration waveform measured in each of the regions of interest RI1, RI2, etc. In this embodiment, the measurement values ​​included in the reference acceleration waveform are also referred to as reference measurement values. In this case, the reference acceleration waveform is a time series of the reference measurement values.

[0025] The measured acceleration waveform database 263 is information for managing information related to measured acceleration waveforms, which are acceleration waveforms measured for each section (such as section SEC1) of each monitored vehicle 3. FIG. 5 shows an example of the configuration of the measured acceleration waveform database 263. The measured acceleration waveform database 263 shown in FIG. 5 stores the measurement date and time (year, month, day, hour, minute, and second), vehicle identification code, section identification code, driving lane identification code, acceleration sensor identification code, measurement position, measurement direction, driving start / end times, and measured acceleration waveform file name in association with each other. The vehicle identification code, section identification code, driving lane identification code, acceleration sensor identification code, measurement position, and measurement direction are the same as the respective items in the reference acceleration waveform database 261. The driving start / end times are the driving start time (date and time) and driving end time (date and time) for the relevant section. The measured acceleration waveform file name is the name of the measured acceleration waveform file 264 representing the measured acceleration waveform. For example, the name of the file representing the measured acceleration waveform AWM1 measured in the section SEC1 shown in FIG. 6 is "FM001."

[0026] The measured acceleration waveform file 263 is a file that represents the measured acceleration waveform measured in the monitored vehicle 3. The measured acceleration waveform is a time series of measurement values.

[0027] The monitoring result database 265 is information that compiles the monitoring results (or evaluation results) of acceleration values ​​(peak values, RMS values, etc.) based on newly measured acceleration waveforms for each region of interest (region of interest RI1, region of interest RI2, etc.). FIG. 7 shows an example of the configuration of the monitoring result database 265. The monitoring result database 265 shown in FIG. 7 stores a region of interest identification code, a driving lane identification code, a vehicle identification code, a measurement date and time, an acceleration sensor identification code, a measurement direction, and monitoring results in association with each other. The region of interest identification code, a driving lane identification code, a vehicle identification code, a section identification code, an acceleration sensor identification code, and a measurement direction are the same as the respective items in the reference acceleration waveform database 261. In this example, the monitoring results are the positive peak value, the negative peak value, and the RMS value measured in the region of interest.

[0028] The control unit 21 controls the various units 22 to 26. The communication unit 22 receives, for example, an acceleration waveform, which is time-series data of acceleration measured in the vehicle 3, from the traffic management device 5, for example, for each section SEC1, in accordance with an instruction from the control unit 21 (or the acquisition unit 23). The acceleration time-series data is time-series data of acceleration measurement values, such as a measured acceleration waveform. However, the communication unit 22 may also receive, for example, an acceleration waveform measured in the vehicle 3 directly from the vehicle 3, for example, for each section SEC1, in accordance with an instruction from the control unit 21 (or the acquisition unit 23). FIG. 6 shows an example of the measured acceleration waveform AWM1. The control unit 21 (or the acquisition unit 23) acquires (a file including data indicating) the measured acceleration waveform AWM1 from, for example, the traffic management device 5, and stores it in the storage unit 26 as a measured acceleration waveform file 264. The control unit 21 (or the acquisition unit 23) also registers information about the stored measured acceleration waveform file 264 in a measured acceleration waveform database 263. The control unit 21 (or the acquisition unit 23) can acquire the following information when acquiring, for example, the measured acceleration waveform AWM1 from the traffic management device 5. That is, the control unit 21 (or the acquisition unit 23) can acquire the measurement date and time of the measured acceleration waveform AWM1, the identification code of the vehicle 3 that performed the measurement, the identification code of the section SEC1 that performed the measurement, the identification code of the traveling lane, the identification code of the acceleration sensor 32 that performed the measurement, information indicating the direction of acceleration, information indicating the start and end times of traveling, and time series data of position identification information corresponding to the measured acceleration waveform AWM1.

[0029] The acquisition unit 23 acquires, for example, from the memory unit 26 (or from the vehicle 3), a measured acceleration waveform (measured acceleration waveform file 264), which is an acceleration waveform measured by the vehicle 3 traveling on the track T1 to be monitored (evaluated).

[0030] The monitoring unit 24 monitors the acceleration values ​​of the nonlinearly stretched measured acceleration waveform, which is an acceleration waveform that is made to correspond to a reference acceleration waveform by nonlinearly stretching or shrinking the time axis of the measured acceleration waveform. In this case, the nonlinear stretching unit 241 in the monitoring unit 24 nonlinearly stretches or shrinks the time axis of the measured acceleration waveform based on the distance between each measurement value of the measured acceleration waveform and each reference measurement value of the reference acceleration waveform. In addition, the determination unit 242 determines whether or not there is an abnormality in the measured acceleration waveform based on a predetermined value obtained by nonlinearly stretching or shrinking the measured acceleration waveform.

[0031] Furthermore, for example, when the acceleration value (maximum value or effective value) for each predetermined section of the measured acceleration waveform measured by the first vehicle 3 exceeds a predetermined threshold value for that section, the monitoring unit 24 determines whether there is an abnormality in the first vehicle 3 or in the track T1 as follows: That is, the monitoring unit 24 determines whether there is an abnormality in the first vehicle 3 or in the track T1 based on the result of comparing the acceleration value (maximum value or effective value) for each section of the measured acceleration waveform measured by a second vehicle 3 different from the first vehicle 3 with the threshold value for that section.

[0032] During monitoring, the monitoring unit 24 first nonlinearly stretches and contracts the time axis of the measured acceleration waveform to be monitored by a matching process with a reference acceleration waveform, which is a reference acceleration waveform, using the nonlinear stretching unit 241. The matching process minimizes the distance between the two time series data, i.e., the measured acceleration waveform and the reference acceleration waveform, so as to increase the correlation coefficient between the two time series data. The nonlinear stretching unit 241 nonlinearly stretches and contracts the time axis of the measured acceleration waveform to obtain a nonlinear stretched measured acceleration waveform, which is an acceleration waveform that corresponds to the reference acceleration waveform. The nonlinear stretching unit 241 performs a matching process with, for example, the measured acceleration waveform AWM1 shown in FIG. 6 and the reference acceleration waveform AWB1 or AWB2 shown in FIG. 3 to obtain, for example, the nonlinear stretched measured acceleration waveform AWM1P1c or AWM1P2c shown in FIG. 6. Techniques for increasing the correlation coefficient between waveforms by performing nonlinear stretching include dynamic programming (DP) matching (a matching method using dynamic programming) and dynamic time warping. DP matching, or dynamic time warping, is a technique for nonlinearly stretching or shrinking waveforms to minimize the distance between corresponding points on two waveforms. The distance can be defined as the sum of squares of the distances (Σ(xi - yi)^2) or the sum of the absolute values ​​of the differences (Σ|xi - yi|). Here, xi and yi are the reference measurement values ​​of the reference waveform and the measurement values ​​of the measurement waveform. The nonlinearly stretched measurement acceleration waveform AWM1P1c is an acceleration waveform that corresponds to the reference acceleration waveform AWB1 by nonlinearly stretching or shrinking the time axis of the acceleration waveform AWM1P1, which is part of the measurement acceleration waveform AWM1. The nonlinearly stretched measurement acceleration waveform AWM1P2c is an acceleration waveform that corresponds to the reference acceleration waveform AWB2 by nonlinearly stretching or shrinking the time axis of the acceleration waveform AWM1P2, which is part of the measurement acceleration waveform AWM1.

[0033] Next, the determination unit 242 determines whether the measured acceleration waveform has an abnormality based on a predetermined value obtained by nonlinearly stretching or shrinking the measured acceleration waveform. In this embodiment, the predetermined value is the amount of stretching or shrinking of each measurement value of the nonlinearly stretched measured acceleration waveform. The determination unit 242 determines that the measured acceleration waveform has an abnormality if each amount of stretching or shrinking is equal to or greater than a predetermined stretch or shrink threshold. FIG. 9 schematically illustrates an example of the relationship between a reference acceleration waveform, a measured acceleration waveform, and a nonlinearly stretched measured acceleration waveform. The reference acceleration waveform and the measured acceleration waveform shown in FIG. 9 are assumed to have been measured in the same section and the same travel lane. The horizontal axis represents time, and the vertical axis represents acceleration. However, the time on the horizontal axis may be replaced with distance based on the measurement time of each measurement value and the speed information and position information of the vehicle 3. In the example shown in FIG. 9, the reference acceleration waveform includes peaks P1 and P3. The measured acceleration waveform includes peaks P11 corresponding to peak P1 and P13 corresponding to peak P3, as well as a new peak P12. Peak P12 corresponds to, for example, some abnormality occurring on the track T1. In the example shown in FIG. 9, the position of peak P12a on the time axis corresponding to peak P12, which is not present in the reference acceleration waveform, shifts toward peak P11 in the nonlinearly stretched acceleration waveform due to DP matching. Meanwhile, the positions of peak P11a corresponding to peak P11 and peak P13a corresponding to peak P13 on the time axis remain largely unchanged. In the example shown in FIG. 9, a large stretch along the time axis may result in an erroneous acceleration evaluation. In this embodiment, the amount of stretching refers to the time difference between the measurement time t1 of a measurement point before nonlinear stretching and the stretched measurement time t2 of the same measurement point after nonlinear stretching. When the horizontal axis represents distance, the amount of stretching refers to the difference in position between the same measurement point before and after stretching. Hereinafter, the amount of stretching in the case of a time difference is also referred to as the time axis stretching amount.

[0034] As described above, the determination unit 242 determines whether or not the amount of expansion or contraction of each measurement value of the nonlinear expansion or contraction measurement acceleration waveform is equal to or greater than a predetermined expansion or contraction amount threshold. If the amount of expansion or contraction is equal to or greater than the expansion or contraction amount threshold, the monitoring unit 24 determines that an abnormality has occurred in the track or vehicle without performing evaluation using DP matching, for example, assuming that the track condition has changed significantly. The monitoring unit 24 also performs similar processing on multiple vehicles 3, and if the analysis of a certain section of multiple vehicles 3 results in a state where the amount of expansion or contraction is determined to be abnormal as described above, it determines that an abnormality has occurred in the track T1. The monitoring unit 24 also determines that an abnormality has occurred in the vehicle 3 if it determines that an abnormality has occurred only in a specific vehicle 3.

[0035] The expansion / contraction threshold can be, for example, the distance (wheelbase) between the front and rear wheels of the vehicle 3, or the time obtained by dividing that distance by the speed. When passing through the EJ (expansion joint) position of the track T1, large acceleration occurs when the front and rear wheels pass, but if the peaks of large acceleration are spaced apart by more than this expansion / contraction threshold, it can be determined that an abnormality other than the EJ in question has occurred on the track.

[0036] When the determination unit 242 determines that none of the expansion / contraction amounts of the measurement values ​​of the nonlinear expansion / contraction measurement acceleration waveform is equal to or greater than a predetermined expansion / contraction amount threshold, the monitoring unit 24 monitors (evaluates) the acceleration values ​​of the nonlinear expansion / contraction measurement acceleration waveform (for example, the nonlinear expansion / contraction measurement acceleration waveform AWM1P1c and the nonlinear expansion / contraction measurement acceleration waveform AWM1P2c in FIG. 6). At this time, the monitoring unit 24 obtains, for example, the maximum positive peak value P111, the maximum negative peak value P112, and the effective value of the nonlinear expansion / contraction measurement acceleration waveform AWM1P1c shown in FIG. 6, and registers them in the monitoring result database 265. In addition, the monitoring unit 24 obtains the maximum positive peak value P121, the maximum negative peak value P122, and the effective value of the nonlinear expansion / contraction measurement acceleration waveform AWM1P2c shown in FIG. 6, and registers them in the monitoring result database 265. In addition, the monitoring unit 24 determines whether or not there is an abnormality by, for example, comparing the measured acceleration waveform with the reference acceleration waveform AWB1 or the reference acceleration waveform AWB2, comparing it with the measured acceleration waveform of the same vehicle 3 or another vehicle 3, or comparing it with a predetermined threshold value, etc.

[0037] In addition, the database management unit 25 constructs or modifies the reference acceleration waveform database 261, and searches for, displays, and prints data registered in the monitoring result database 265, for example, in response to a predetermined input operation by the operator.

[0038] (Example of operation of acceleration monitoring device 2) Next, an example of the operation of the acceleration monitoring device 2 shown in Fig. 1 will be described with reference to Fig. 8. Fig. 8 shows an example of the process (S101 to S103) for creating the reference acceleration waveform database 261 and an example of the process (S201 to S212) for monitoring the measured acceleration waveform.

[0039] 8, when constructing the reference acceleration waveform database 261, first, the communication unit 22 and the acquisition unit 23 are used to acquire the reference acceleration waveform for each vehicle, travel lane, and measurement position / direction, for example, offline from the vehicle 3 (or online via the traffic management device 5, etc.) (step S101). Next, the database management unit 25 is used to associate the peak occurrence positions of the acceleration waveform with the regions of interest (step S102). Then, the database management unit 25 is used to create a database of the reference acceleration waveform (step S103).

[0040] Also, as shown in FIG. 8, when monitoring the measured acceleration waveform, the monitoring unit 24 is used to specify vehicle information (step S201), acquire acceleration data of the vehicle 3 to be analyzed (step S202), and the nonlinear stretching unit 241 performs DP matching between the multiple reference acceleration waveforms in the reference acceleration waveform database 261 and the acquired measured acceleration waveform (step S203).

[0041] Next, the determination unit 242 determines whether the amount of time axis expansion / compression during DP matching is equal to or greater than the expansion / compression amount threshold (step S204). If the amount of time axis expansion / compression during DP matching is equal to or greater than the expansion / compression amount threshold (step S204: Yes), the determination unit 242 determines whether the amount of time axis expansion / compression for only a certain vehicle is equal to or greater than the expansion / compression amount threshold (step S206). If the amount of time axis expansion / compression for only a certain vehicle is equal to or greater than the expansion / compression amount threshold (step S206: Yes), the determination unit 242 determines that an abnormality has occurred in the vehicle (step S207). If the amount of time axis expansion / compression for only a certain vehicle is not equal to or greater than the expansion / compression amount threshold (step S206: No), the determination unit 242 determines that an abnormality has occurred in the track in the target section (step S208).

[0042] On the other hand, if the amount of time axis expansion / contraction during DP matching is not greater than the expansion / contraction amount threshold (step S204: No), the monitoring unit 24 is used to identify the acceleration waveform corresponding to the region of interest contained in the measured acceleration waveform, and abnormality detection is performed by monitoring the acceleration value (step S205).

[0043] Furthermore, the monitoring unit 24 evaluates the maximum value and the effective value for each section (step S209) and compares them with the evaluation results (D201) of the maximum value and the effective value for each section for other vehicles. If the maximum value or the effective value for only one vehicle is relatively large (step S210: Yes), the monitoring unit 24 determines that an abnormality has occurred in the vehicle (step S211), and if the maximum value and the effective value for only one vehicle are not relatively large (step S210: No), the monitoring unit 24 determines that an abnormality has occurred in the track in the target section (step S212).

[0044] (Supplementary explanation, actions, effects, etc. of the first embodiment) In this embodiment, the measured acceleration waveform is nonlinearly stretched or compressed based on the reference acceleration waveform. In this case, the amount of nonlinear stretching or compression is limited. In this embodiment, if the waveform needs to be stretched or compressed for more than a certain time (or a certain distance), it is assumed that the track condition has changed significantly, and an evaluation based on the nonlinear stretched or compressed measured acceleration is not performed, and it is determined that an abnormality has occurred in the track or vehicle.

[0045] In addition, similar processing is performed on multiple vehicles, and if the analysis of a certain section of multiple vehicles reveals that an abnormality in the amount of expansion or contraction exceeds the threshold, it is determined that an abnormality has occurred on the track.If it is determined that an abnormality in the amount of expansion or contraction has occurred only in a specific vehicle, it is determined that an abnormality has occurred in the vehicle.

[0046] When performing nonlinear compression and stretching, if processing involving extreme nonlinear compression and stretching of the time axis is performed, there is a possibility that errors will occur in extracting peaks from the waveform to be analyzed. In this embodiment, if extreme nonlinear compression and stretching occurs, it is possible to determine that some kind of abnormality has occurred, and monitoring will not continue without noticing the abnormality.

[0047] Furthermore, by evaluating the maximum and effective values ​​for each section (for example, between stations), it is possible to roughly determine whether or not an abnormality exists for the entire section. By identifying sections where nonlinear expansion / contraction occurs for a time (or distance) that exceeds the expansion / contraction threshold, as in this embodiment, it becomes possible to determine whether or not an abnormality exists in a location that was not originally anticipated. Furthermore, by combining evaluation based on the maximum and effective values ​​with evaluation based on the expansion / contraction amount, it becomes possible to determine the location of an abnormality that cannot be determined by simply distinguishing each section or extracting acceleration at a specific location by matching, thereby improving the efficiency of condition monitoring.

[0048] As described above, according to this embodiment, the measurement values ​​can be appropriately monitored.

[0049] Figures 15 and 16 show examples of acceleration waveforms obtained when the same vehicle is driven 10 times under the same track and speed conditions. Figure 15 shows an enlarged version of the reference acceleration waveform and the nonlinear stretch measurement acceleration waveform obtained when DP matching is performed using one of the 10 waveforms as the reference acceleration waveform. Figure 16 shows an enlarged version of the waveforms obtained around 56 seconds and 64.4 seconds when 10 waveforms are matched at the acceleration peak around 56 seconds. In the example shown in Figure 16, even if the timing of a certain acceleration peak position is adjusted to match, the timing of other acceleration peak positions will be shifted, which will require time for evaluation. On the other hand, when DP matching is performed, the acceleration peak positions are accurately matched, as shown in Figure 15.

[0050] Second Embodiment An acceleration monitoring device according to a second embodiment of the present disclosure will be described with reference to FIG. 10. FIG. 10 is a flowchart illustrating an example of the operation of the acceleration monitoring device according to the second embodiment of the present disclosure. The block configuration of the acceleration monitoring device according to the second embodiment is the same as that of the acceleration monitoring device 2 shown in FIG. 1. The acceleration monitoring device according to the second embodiment differs partially from the first embodiment in the operation of the determination unit 242 shown in FIG. 1. In the first embodiment, the amount of time-axis expansion / contraction is set to a predetermined value according to the present disclosure, and the determination unit 242 determines whether or not there is an abnormality in the measured acceleration waveform based on the amount of time-axis expansion / contraction. On the other hand, in the second embodiment, the correlation coefficient between the nonlinearly expanded / contracted measured acceleration waveform (nonlinearly expanded / contracted measured acceleration waveform) and the reference acceleration waveform is set to a predetermined value according to the present disclosure, and the determination unit 242 determines that there is an abnormality in the measured acceleration waveform if the correlation coefficient is equal to or less than a predetermined correlation coefficient threshold.

[0051] 10, the process of step S204a (corresponding to step S204 in FIG. 8) and the process of step S206a (corresponding to step S206 in FIG. 8) differ from the process of the first embodiment. In step S204a, the determination unit 242 determines whether the correlation coefficient after DP matching is equal to or less than the correlation coefficient threshold. In step S204a, the determination unit 242 determines whether the correlation coefficient of only a certain vehicle is equal to or less than the correlation coefficient threshold.

[0052] In the second embodiment, the nonlinear expansion / contraction unit 241 performs, for example, DP matching between the reference acceleration waveform and the measured acceleration waveform to be analyzed, and then the determination unit 242 of the second embodiment calculates a correlation coefficient between the matched waveforms. If the correlation coefficient is greater than the correlation coefficient threshold, the monitoring unit 24 determines that there is no significant change and continues the analysis. If the correlation coefficient is equal to or less than the correlation coefficient threshold, the monitoring unit 24 determines that there has been a significant change in the state and determines that an abnormality has occurred without analyzing the accelerations at the monitored positions.

[0053] Normally, under the same driving conditions, the correlation coefficient after DP matching will be at least 0.9. If it falls below this level, it is determined that a major abnormality has occurred, making it possible to determine an abnormality before comparing it with other data.

[0054] According to the second embodiment, the measurement values ​​can be appropriately monitored in the same manner as in the first embodiment.

[0055] Third Embodiment An acceleration monitoring device 2a (corresponding to the acceleration monitoring device 2 of the first embodiment) according to a third embodiment of the present disclosure will be described with reference to Figs. 11 to 14. Fig. 11 is a block diagram showing a configuration example of the acceleration monitoring device according to the third embodiment of the present disclosure. Fig. 12 is a schematic diagram showing a configuration example of a measured acceleration waveform database according to the third embodiment of the present disclosure. Fig. 13 is a flowchart showing an operation example of the acceleration monitoring device according to the third embodiment of the present disclosure. Fig. 14 is a schematic diagram for explaining an operation example of the acceleration monitoring device according to the third embodiment of the present disclosure.

[0056] 11, a monitoring unit 24a (corresponding to the monitoring unit 24 in FIG. 1) of the acceleration monitoring device 2 according to the third embodiment shown in FIG. 11 newly includes a position identification unit 243. Also, the configuration of a measured acceleration waveform database 263a (corresponding to the measured acceleration waveform database 263) stored in the storage unit 26 is partially different. Also, the storage unit 26 further stores a plurality of position information files 266.

[0057] The position information file 266 is a file containing time-series data of position identification information (hereinafter also referred to as position information) identified by the position identification information acquisition device 33 provided in the vehicle 3. As described above, the position identification information is, for example, a time-series of position information representing latitude and longitude acquired using a global positioning system. The position information in the position information file 266 can be linked using information representing each measurement value and measurement time in the measured acceleration waveform file 264. However, the sampling period of the acceleration is usually shorter than the sampling period of the position information. In this case, the position information is linked to at least a portion of each measurement value of the measured acceleration waveform.

[0058] The measured acceleration waveform database 263a corresponds to the measured acceleration waveform database 263 shown in FIG. 1, and as shown in FIG. 12, the measured acceleration waveform file name etc. is further associated with a position information file name which is the file name of the position information file 266.

[0059] The position identifying unit 243 identifies a position corresponding to a measurement value of the measured acceleration waveform where the time axis expansion / compression amount is equal to or greater than the expansion / compression amount threshold, using the position information in the position information file 266. In this case, the position identifying unit 243 identifies a position corresponding to a measurement value having a peak value (e.g., P12) in a section made up of multiple measurement values ​​where the time axis expansion / compression amount is equal to or greater than the expansion / compression amount threshold, as shown in Fig. 14. Fig. 14 shows the same reference acceleration waveform, measured acceleration waveform, and nonlinear expansion / compression acceleration waveform as Fig. 9.

[0060] As described above, when the sampling time of the position information is longer than the sampling time of the acceleration data, the position identification unit 243 performs, for example, interpolation to align the position information with the sampling time of the acceleration data. Examples of interpolation methods include linear interpolation using a general one-dimensional function and spline interpolation. This process upsamples, for example, GPS data acquired at a low sampling frequency, to obtain GPS data on the same time axis as the acceleration. The position identification unit 243 determines the location of a new abnormality from the GPS data by combining the time when the maximum acceleration value (absolute value) occurred within a time (distance) band in which movement occurred in the direction of the large time axis (distance axis).

[0061] 13, the position specifying unit 243 extracts a section where the amount of time axis expansion or contraction is equal to or greater than the expansion or contraction amount threshold (step S301), acquires longitude / latitude information at the moment when acceleration is maximum (step S302), and records this as position information of the peak value in the monitoring result database 265, for example. However, the method of outputting the specified position information is arbitrary. In FIG. 13, the processes of steps S101 to S103 and steps S201 to S212 are the same as those in FIG. 8.

[0062] According to the third embodiment, the measurement values ​​can be appropriately monitored as in the first and second embodiments, and when the time axis expansion / contraction amount reaches the expansion / contraction amount threshold, by combining, for example, GPS data, it is possible to identify location information where the state is thought to have changed significantly.

[0063] The third embodiment can also be combined with the second embodiment.

[0064] Although the embodiments of the present disclosure have been described above in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and design modifications within the scope of the present disclosure are also included. For example, the determination of the amount of expansion and contraction and the correlation coefficient in the first and second embodiments may be performed, and if one or both of them are satisfied, evaluation based on the nonlinear expansion and contraction measured acceleration waveform (step S205) may be performed. Furthermore, the monitoring and evaluation of the measured acceleration waveform may be performed, for example, for each section during operation, or may be performed all at once at the end of each day's operation. Furthermore, the nonlinear expansion and contraction unit 241 may nonlinearly expand or contract the reference waveform based on the distance between each measurement value of the measurement waveform (measured acceleration waveform) and each reference measurement value of the reference waveform (reference acceleration waveform).

[0065] <Computer Configuration> FIG. 17 is a schematic block diagram illustrating the configuration of a computer according to at least one embodiment. The computer 90 includes a processor 91 , a main memory 92 , a storage 93 , and an interface 94 . The acceleration monitoring devices 2 and 2a described above are implemented in a computer 90. The operations of the above-described processing units are stored in the form of a program in a storage 93. A processor 91 reads the program from the storage 93, loads it into a main memory 92, and executes the above-described processing in accordance with the program. The processor 91 also allocates storage areas in the main memory 92 corresponding to the above-described storage units in accordance with the program.

[0066] The program may be for realizing some of the functions to be performed by the computer 90. For example, the program may be combined with other programs already stored in storage or other programs implemented in other devices to perform the functions. In other embodiments, the computer may include a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or instead of the above configuration. Examples of PLDs include PAL (Programmable Array Logic), GAL (Generic Array Logic), CPLD (Complex Programmable Logic Device), and FPGA (Field Programmable Gate Array). In this case, some or all of the functions realized by the processor may be realized by the integrated circuit.

[0067] Examples of storage 93 include a hard disk drive (HDD), a solid state drive (SSD), a magnetic disk, a magneto-optical disk, a compact disc read-only memory (CD-ROM), a digital versatile disc read-only memory (DVD-ROM), and a semiconductor memory. Storage 93 may be an internal medium directly connected to the bus of computer 90, or an external medium connected to computer 90 via interface 94 or a communication line. Furthermore, when this program is distributed to computer 90 via a communication line, computer 90 that receives the program may load the program into main memory 92 and execute the above-described processing. In at least one embodiment, storage 93 is a non-transitory tangible storage medium.

[0068] <Additional Notes> The acceleration monitoring devices 2 and 2a described in the respective embodiments can be understood, for example, as follows.

[0069] (1) The acceleration monitoring devices 2 and 2a according to the first aspect include a nonlinear stretching unit 241 that stretches or contracts a measurement waveform nonlinearly based on the distance between each measurement value of the measurement waveform (measured acceleration waveform) and each reference measurement value of a reference waveform (reference acceleration waveform), and a determination unit 242 that determines whether or not there is an abnormality in the measurement waveform based on a predetermined value (amount of time axis stretching, correlation coefficient) obtained by stretching or contracting the measurement waveform nonlinearly. According to this aspect and the following aspects, the measurement values ​​can be monitored appropriately.

[0070] (2) The acceleration monitoring devices 2 and 2a according to the second aspect are the acceleration monitoring devices 2 and 2a of (1), in which the predetermined value is the amount of expansion / contraction (time axis expansion / contraction amount) of each measurement value of the measurement waveform that has been nonlinearly expanded / contracted, and the judgment unit 242 judges that there is an abnormality in the measurement waveform if the amount of expansion / contraction is equal to or greater than a predetermined expansion / contraction amount threshold (step S204).

[0071] (3) The acceleration monitoring device 2a according to the third aspect is the acceleration monitoring device 2a of (2), and further includes a position identification unit 243 in which position information is linked to at least a portion of each measurement value of the measurement waveform, and which uses the position information to identify the position corresponding to the measurement value whose expansion / contraction amount is equal to or greater than the expansion / contraction amount threshold.

[0072] (4) The acceleration monitoring device 2a according to the fourth aspect is the acceleration monitoring device 2a of (3), in which the position identification unit 243 identifies the position corresponding to the measurement value having a peak value among the plurality of measurement values ​​whose expansion / contraction amount is equal to or greater than the expansion / contraction amount threshold.

[0073] (5) The acceleration monitoring devices 2 and 2a according to the fifth aspect are the acceleration monitoring devices 2 and 2a of (1), in which the predetermined value is a correlation coefficient between the nonlinearly stretched measured waveform and the reference waveform, and the judgment unit 242 judges that there is an abnormality in the measured waveform when the correlation coefficient is equal to or less than a predetermined correlation coefficient threshold.

[0074] (5) The acceleration monitoring devices 2 and 2a according to the fifth aspect are the acceleration monitoring devices 2 or 2a of (1) to (5), and the measured waveform and the reference waveform are acceleration waveforms measured by a vehicle 3 traveling on a track T1. [Explanation of symbols]

[0075] 1. Rubber-tired New Transportation System 2, 2a Acceleration monitoring device 3, 3a, 3b, 3c vehicles 23 Acquisition Department 24, 24a Monitoring section 241 Nonlinear expansion section 242 Judgment section 243 Location identification part 26 Memory section 32 Acceleration sensor 33 Location identification information acquisition device 301 Body 303 Cart 304 Shock absorber

Claims

1. a nonlinear stretching unit that stretches or shrinks the measurement waveform nonlinearly based on the distance between each measurement value of the measurement waveform and each reference measurement value of the reference waveform; a determination unit that determines whether or not the measured waveform is abnormal based on a predetermined value obtained by nonlinearly stretching and contracting the measured waveform; Equipped with the measurement waveform and the reference waveform are acceleration waveforms measured by a vehicle traveling on a track, the predetermined value is an amount of expansion or contraction of each measurement value of the measurement waveform that has been nonlinearly expanded or contracted, the determination unit determines that the measured waveform is abnormal when the amount of expansion / contraction is equal to or greater than a predetermined expansion / contraction amount threshold, The expansion / contraction amount threshold is defined as a value related to the distance between the front wheels and the rear wheels of the vehicle. monitoring equipment.

2. Position information is associated with at least a portion of each measurement value of the measurement waveform, a position specifying unit that specifies a position corresponding to the measurement value where the expansion / contraction amount is equal to or greater than the expansion / contraction amount threshold value using the position information; The monitoring device according to claim 1 further comprising:

3. The position specifying unit specifies a position corresponding to the measurement value having a peak value among the plurality of measurement values ​​whose expansion / contraction amount is equal to or greater than the expansion / contraction amount threshold. The monitoring device according to claim 2 .

4. the predetermined value is a correlation coefficient between the nonlinearly stretched and compressed measured waveform and the reference waveform, The determination unit determines that the measured waveform is abnormal when the correlation coefficient is equal to or smaller than a predetermined correlation coefficient threshold. The monitoring device of claim 1 .

5. stretching or shrinking the measured waveform nonlinearly based on the distance between each measured value of the measured waveform and each reference measured value of the reference waveform; a step of determining whether or not the measured waveform has an abnormality based on a predetermined value obtained by nonlinearly stretching and contracting the measured waveform; Including, the measurement waveform and the reference waveform are acceleration waveforms measured by a vehicle traveling on a track, the predetermined value is an amount of expansion or contraction of each measurement value of the measurement waveform that has been nonlinearly expanded or contracted, In the determining step, it is determined that there is an abnormality in the measured waveform when the expansion / contraction amount is equal to or greater than a predetermined expansion / contraction amount threshold value, The expansion / contraction amount threshold is defined as a value related to the distance between the front wheels and the rear wheels of the vehicle. Monitoring method.

6. stretching or shrinking the measured waveform nonlinearly based on the distance between each measured value of the measured waveform and each reference measured value of the reference waveform; a step of determining whether or not the measured waveform has an abnormality based on a predetermined value obtained by nonlinearly stretching and contracting the measured waveform; A program that causes a computer to execute the the measurement waveform and the reference waveform are acceleration waveforms measured by a vehicle traveling on a track, the predetermined value is an amount of expansion or contraction of each measurement value of the measurement waveform that has been nonlinearly expanded or contracted, In the determining step, it is determined that there is an abnormality in the measured waveform when the expansion / contraction amount is equal to or greater than a predetermined expansion / contraction amount threshold value, The expansion / contraction amount threshold is defined as a value related to the distance between the front wheels and the rear wheels of the vehicle. program.

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