JP6689479B1 - Diagnostic system and method - Google Patents

Abstract

An object of the present invention is to obtain a diagnostic system capable of increasing the possibility of realizing at least one of highly accurate analysis and efficient analysis of device deterioration. The diagnostic system according to the present invention includes a deterioration amount indicating a degree of deterioration of a device corresponding to each of a plurality of dates and times calculated based on measurement data obtained by measuring a state of a device mounted on a vehicle at a plurality of dates and times. , A data acquisition unit (12) for acquiring operation information including route information indicating a route on which the vehicle has traveled, and the route information to acquire first information indicating a track record of a traveling state of the vehicle, and A deterioration analysis unit (14) for analyzing deterioration of the device using the information and the deterioration amounts of a plurality of dates and times.

Description

  The present invention relates to a diagnostic system and a diagnostic method for diagnosing deterioration of equipment mounted on a railway vehicle.

  2. Description of the Related Art Conventionally, in a railway vehicle (hereinafter, also simply referred to as a vehicle), maintenance and inspection of equipment mounted therein are performed for normal traveling, passenger comfort, and the like. During maintenance, deterioration of each device such as the pantograph, wheels, and brakes is confirmed. Degradation of equipment is performed by visual confirmation by an operator, measurement of the shape of the equipment by a measuring device, or the like. For example, Patent Document 1 discloses a technique of photographing a wear plate of a pantograph with a stereo camera and obtaining the amount of wear of the wear plate of the pantograph from shape information calculated using the taken image. In the technique described in Patent Document 1, the newly acquired shape information is compared with the past shape information at the same installation position with the same knitting number to obtain the wear amount of the sliding plate of the pantograph.

JP, 2016-191648, A

  In order to prevent the wear amount of the contact plate of the pantograph from exceeding a predetermined limit value, it is desirable to analyze the tendency of the time change of the contact plate and predict the future wear amount. By predicting the amount of wear of the contact plate, the contact plate can be replaced before it falls below the use limit value set as the lower limit value for use. Patent Document 1 also describes that when the traveling distance of the vehicle can be acquired, the wear amount can be estimated based on the traveling distance, but how to specifically acquire the traveling distance. Is not stated.

  The analysis of device deterioration can be used not only for the purpose of prediction but also for evaluation of the pantograph product itself. As described above, the analysis of the deterioration of the device is useful for the maintenance and inspection of the device, but the deterioration amount of each device such as the wear amount of the contact plate does not always depend only on the traveling distance. For example, the deterioration amount of the device may depend on at least one of various pieces of information such as the number of curves on the route along which the vehicle travels, the speed of the vehicle, and the weight of the vehicle. Therefore, in the analysis of the deterioration of the device, it may not be possible to perform a highly accurate analysis only by considering the traveling distance. In addition, there are cases where efficient analysis cannot be performed only by considering the travel distance.

  The present invention has been made in view of the above, and an object of the present invention is to obtain a diagnostic system capable of increasing the possibility of realizing at least one of highly accurate analysis and efficient analysis of device deterioration. To do.

  In order to solve the above-mentioned problems and achieve the object, the diagnostic system according to the present invention has a plurality of dates and times calculated based on measurement data obtained by measuring the states of the devices mounted on the railway vehicle at a plurality of dates and times. And a data acquisition unit that acquires the deterioration amount indicating the degree of deterioration of the device corresponding to each of the above and operation information including the route information indicating the route on which the railway vehicle has traveled. The diagnostic system further uses the route information to acquire first information indicating a track record of the running state of the railway vehicle, and analyzes deterioration of the device using the first information and the deterioration amounts of a plurality of dates and times. An analysis unit is provided.

  The diagnostic system according to the present invention has the effect of increasing the possibility of realizing at least one of highly accurate analysis and efficient analysis of device deterioration.

The figure which shows the structural example of the railroad management system concerning Embodiment 1 of this invention. The figure which shows an example of the data collection device and measurement system of Embodiment 1. The figure which shows the structural example of the analysis apparatus of Embodiment 1. The figure which shows the structural example of the vehicle equipment of Embodiment 1. The figure which shows the structural example of the diagnostic system of Embodiment 1. FIG. 2 is a diagram showing a configuration example of a computer system that realizes the railway management system of the first embodiment. The figure which shows the sliding plate of a pantograph which is an example of the degradation diagnostic object of Embodiment 1. The figure which shows an example of the shape of the contact plate measured by the measuring system of Embodiment 1. The figure which shows an example of the analysis result of the analysis apparatus of Embodiment 1. The flowchart which shows an example of the diagnostic processing procedure in the diagnostic system of Embodiment 1. The figure which shows the structural example of the inspection data of Embodiment 1. The figure which shows an example of the driving data of Embodiment 1. The figure which shows an example of the line state information contained in the operation information of Embodiment 1. The figure which shows an example of the route information of Embodiment 1. The figure which shows an example of the analysis result of the performance record of the apparatus deterioration of Embodiment 1. The figure which shows the example of a display of the prediction result of the abrasion amount of a contact plate in Embodiment 1. The figure which shows the wear of the wheel cross section which is an example of the deterioration of Embodiment 1. The figure which shows the structural example of the diagnostic system concerning Embodiment 2. The figure which shows the structural example of the diagnostic system concerning Embodiment 3. The figure which shows an example of the inspection data of Embodiment 3. The figure which shows an example of the grouping result of Embodiment 3. The figure which shows an example of the trace information of Embodiment 3.

  Hereinafter, a diagnostic system and a diagnostic method according to an embodiment of the present invention will be described in detail with reference to the drawings. The present invention is not limited to this embodiment.

Embodiment 1.
FIG. 1 is a diagram showing a configuration example of a railway management system according to a first embodiment of the present invention. The railway management system 3 is a device that manages the life cycle of the vehicle 5 by collecting and analyzing various information of the vehicle 5, which is a railway vehicle. As a result, the efficiency of maintenance of the vehicle 5 can be improved.

  As shown in FIG. 1, the railway management system 3 of the present embodiment includes a diagnostic system 1 according to the present invention and a database system 2. The railway management system 3 is realized by, for example, a cloud system, but is not limited to this.

  As shown in FIG. 1, the database system 2 includes a storage unit 21 that stores various data, a communication unit 22, and a data management unit 23. The communication unit 22 of the database system 2 receives the traveling data of the vehicle 5 via the wireless device 42, the operation information from the operation management system 41, the inspection data from the inspection system 60, and the storage unit 21. Store to. The data management unit 23 manages the data stored in the storage unit 21. The data management unit 23 uses the organization information including at least the vehicle number included in each of the inspection data, the operation information, and the travel data, and manages them in association with each other.

  The diagnostic system 1 is a diagnostic device that diagnoses deterioration of the vehicle 5 using the data accumulated in the database system 2. As a result, the diagnostic system 1 can provide users, such as a railway operator, a manufacturer of the vehicle 5, a manufacturer of equipment mounted on the vehicle 5, and the like, with information used for efficient maintenance. Further, the diagnosis system 1 can also transmit the analysis result of the railway management system 3 and the like to the terminal device 9 of the user.

  The vehicle 5 includes a pantograph 51, wheels 52, an underfloor device 53, and an on-board device 54. The underfloor equipment 53 is, for example, a VVVF (Variable Voltage Variable Frequency) inverter device, a line breaker, an auxiliary power supply device, and a compressor. The pantograph 51, the wheels 52, and the underfloor equipment 53 are examples of vehicle-mounted equipment (hereinafter, also simply referred to as equipment) mounted on the vehicle 5, and the vehicle 5 includes other brakes, carriages, gears, and gear boxes not shown. Equipment such as is also installed, and the equipment installed in the vehicle 5 is not limited to the example shown in FIG. Further, the vehicle body of the vehicle 5 is also an example of a device mounted on the vehicle 5. That is, the device mounted on the vehicle 5 that is the diagnosis target of the present embodiment includes at least one of the pantograph 51, the wheels 52, the brake, the vehicle body, the motor, and the truck. The on-board device 54 transmits a control command to the devices mounted on the vehicle 5, and receives from each device a response to the control command, information indicating the state of each device, and the like. Note that FIG. 1 schematically shows the vehicle 5 and each device mounted on the vehicle 5, and does not show the actual shape of the vehicle 5, the shape of each device, and the mounting position. The vehicle 5 measures not only the state of each device, but also the traveling distance, the speed, and the like, and the on-board device 54 also acquires these measurement results. Further, when the vehicle 5 measures the train weight, the temperature inside the car, the outside air temperature, etc., the on-board device 54 also acquires these measurement results.

  The on-board device 54 wirelessly transmits the control command for controlling each device, the response and information received from each device, and each measurement result as traveling data. The wireless signal transmitted from the vehicle 5 is received by the wireless device 42. The wireless device 42 transmits the received traveling data to the operation management system 41, and the operation management system 41 transmits the received traveling data to the database system 2. The wireless device 42 transmits the received traveling data to the operation management system 41, and the operation management system 41 transmits the received traveling data to the database system 2. As a result, the database system 2 can acquire the travel data of the vehicle 5 via the wireless device 42 and the operation management system 41. In addition, in FIG. 1, one wireless device 42 is illustrated for simplification of the drawing, but generally, a plurality of wireless devices 42 are arranged, for example, along a line. Further, although one vehicle 5 is shown in FIG. 1, a plurality of vehicles 5 may constitute a train of one formation.

  The operation management system 41 also manages the operation of the plurality of vehicles 5 on the plurality of routes. The operation management system 41 holds operation plans for a plurality of routes and manages the operation of the plurality of vehicles 5 according to the operation plans. When a plurality of vehicles 5 form a train of one set, an operation plan determines when and which route to run for each set. The operation management system 41 also holds, as formation information, information (vehicle number) indicating which vehicle 5 is used in each formation. Further, the operation management system 41 also holds an operation record indicating which train traveled on which route. The operation management system 41 also includes route state information indicating the distance and the number of stop stations for each route. The operation management system 41 transmits operation information, which is information including an operation plan, operation results, route state information, and formation information, to the database system 2. In addition, when the on-board device 54 also manages the operation record, the database system 2 may acquire the operation record from the on-board device 54.

  The communication unit 22 of the database system 2 acquires the inspection data from the inspection system 60 and stores it in the storage unit 21. The inspection system 60 is provided, for example, at a vehicle depot or around the vehicle depot. The inspection system 60 includes an analysis device 6, a data collection device 7, and a measurement system 8. The analysis device 6 may be included in the railway management system 3.

  FIG. 2 is a diagram showing an example of the data collection device 7 and the measurement system 8 according to the present embodiment. The measurement system 8 is generally provided around the vehicle depot or in the vehicle depot. In the example illustrated in FIG. 2, the measurement system 8 includes an overhead line device 81 that is a measurement device that measures the vehicle 5 from above, an in-orbit device 82 that is a measurement device that is provided on a track 84 on which the vehicle 5 travels, A trackside device 83, which is a measuring device for measuring the vehicle 5 from the side, is provided. The overhead line device 81 is, for example, a stereo camera or an ultrasonic sensor. The in-orbit device 82 is, for example, a vibration sensor, an acceleration sensor, a camera, or the like. The data collection device 7 is, for example, a personal computer. The trackside device 83 is, for example, a camera. The trackside device 83 may include a sensor that reads the vehicle number of the vehicle 5.

  Here, the example in which the measurement system 8 includes these three types of measurement devices has been described, but the types of measurement devices are not limited to these. The measurement system 8 may be one or two of these three types, or may include a measurement device other than these three types. In addition, when measuring the wear amount of the sliding plate of the pantograph 51, an overhead wire device 81 is provided, and when measuring the deterioration of the wheels 52, an in-track device 82 is provided. A measuring device may be installed.

  Each measurement device that constitutes the measurement system 8 transmits the measured measurement data to the data collection device 7. The data collection device 7 transmits the measurement data received from each measurement device to the analysis device 6.

  The analysis device 6 uses the measurement data received from each measurement device to perform analysis for inspection of each device mounted on the vehicle 5. FIG. 3 is a diagram showing a configuration example of the analysis device 6 of the present embodiment. As shown in FIG. 3, the analysis device 6 includes a communication unit 61, a measurement data storage unit 62, an analysis unit 63, an analysis result presentation unit 64, a reflection unit 65, and an inspection data generation unit 66.

  The communication unit 61 receives the measurement data of each measurement device from the data collection device 7, and stores it in the measurement data storage unit 62. The measurement data storage unit 62 stores the measurement data of each measuring device. The analysis unit 63 uses the measurement data stored in the measurement data storage unit 62 to perform analysis for inspection of each device mounted on the vehicle 5. The analysis result presentation unit 64 presents the analysis result obtained by the analysis by the analysis unit 63 to an operator who conducts the inspection. The reflection unit 65 receives an input regarding an analysis result from an operator who performs an inspection, and outputs the input information to the inspection data generation unit 66. The inspection data generation unit 66 generates inspection data based on the analysis result and the input information. The inspection data generation unit 66 presents the inspection data to an operator or the like. Further, the inspection data generation unit 66 outputs the inspection data to the communication unit 61, and the communication unit 61 transmits the inspection data to the database system 2. The communication unit 61 may also transmit the measurement data stored in the measurement data storage unit 62 and the analysis result of the analysis unit 63 to the database system 2. Details of the analysis result and the inspection data will be described later.

  Next, a configuration example of the on-board device 54 mounted on the vehicle 5 will be described. FIG. 4 is a diagram showing a configuration example of the on-board device 54 of the present embodiment. As shown in FIG. 4, the on-board device 54 includes a wireless device 541 and a control device 542. The wireless device 541 transmits / receives data to / from the wireless device 42. The control device 542 controls the vehicle 5 by controlling the on-vehicle devices 50-1, 50-2, ... Which are a plurality of on-vehicle devices mounted on the vehicle 5 based on the control information inside the vehicle 5. . The on-vehicle devices 50-1, 50-2, ... Are, for example, the pantograph 51, the wheels 52, the underfloor device 53, the brake (not shown), and the like shown in FIG. Further, the control device 542 collects the above-mentioned travel data and transmits it to the wireless device 42 via the wireless device 541. Hereinafter, when each of the in-vehicle devices 50-1, 50-2, ... Is not individually distinguished, the in-vehicle device 50 is also described.

  Next, a configuration example of the diagnosis system 1 in the railway management system 3 of this embodiment will be described. FIG. 5 is a diagram showing a configuration example of the diagnostic system 1 according to the present embodiment. As shown in FIG. 5, the diagnostic system 1 according to the present embodiment includes a communication unit 11, a data acquisition unit 12, a data storage unit 13, a deterioration analysis unit 14, a deterioration prediction unit 15, a replacement time estimation unit 16, and a display unit 17. Equipped with.

  The communication unit 11 can communicate with the database system 2, the terminal device 9, and the like. The data acquisition unit 12 acquires data used for device diagnosis from the database system 2 via the communication unit 11 and stores the data in the data storage unit 13. The data used for diagnosing the device includes inspection data, running data, and operation information regarding the device to be diagnosed. As will be described later, the inspection data includes a deterioration amount indicating the degree of deterioration of the device corresponding to each of the plurality of dates and times calculated based on the measurement data. Note that the device diagnosis according to the present embodiment includes at least one of analysis of the actual result of device deterioration, prediction of device deterioration, evaluation of device deterioration, and the like. The device to be diagnosed may be designated by the user or may be automatically diagnosed with respect to all the in-vehicle devices 50 that require deterioration analysis and the like according to a predetermined procedure. For example, when the user gives an instruction to start the diagnosis of the device, the diagnosis system 1 may automatically perform the diagnosis for all the in-vehicle devices 50 that require the analysis of the deterioration and the like. The instruction to start the diagnosis of the device by the user and the designation of the device to be diagnosed by the user may be performed through the terminal device 9, or by using an input unit (not shown in FIG. 5) of the diagnostic system 1. May be done.

  As described above, the travel data is data acquired from the vehicle 5 and includes at least one of a control command in the vehicle 5, a response to the control command, and a state value obtained by measuring the state of the vehicle 5.

  Further, the data acquisition unit 12 acquires route information indicating the route traveled by each vehicle 5, that is, which route each vehicle 5 has traveled from the operation record and formation information, and stores the route information in the data storage unit 13. To do. When one formation is composed of one vehicle, formation information is unnecessary. The route information may include a plan for each vehicle 5 on which route the vehicle is to travel. Details of the route information will be described later.

  The deterioration analysis unit 14 analyzes the deterioration of the device based on the data stored in the data storage unit 13. Specifically, the deterioration analysis unit 14 acquires the first information indicating the actual result of the traveling state of the vehicle 5 by using the route information, and uses the first information and the deterioration amounts of a plurality of dates and times to identify the device. Analyze deterioration. The first information is, for example, the actual value of the mileage of the railway vehicle on which the device to be diagnosed is mounted. The analysis of the deterioration of the equipment includes, for example, calculation of a tendency of the wear amount of the pantograph 51 with respect to time, analysis of the wear amount of the wheels 52, analysis of the occurrence state of flats which are flat scratches generated on the wheels 52, wear of brakes. And analysis of the degree of deterioration of the truck. The analysis of device deterioration is not limited to these. A specific example of the device deterioration analysis will be described later. The deterioration analysis unit 14 may analyze the deterioration of the device based on the data stored in the storage unit 21 without using the data acquisition unit 12 and the data storage unit 13. When the deterioration analysis unit 14 analyzes the deterioration of the device based on the data stored in the storage unit 21, the data management unit 23 generates the route information executed by the data acquisition unit 12, and outputs the route information. It may be managed in the storage unit 21.

  The deterioration prediction unit 15 uses the analysis result of the deterioration analysis unit 14 to predict the future deterioration amount of the device. Specifically, the future deterioration of the device is predicted based on the analysis result of the deterioration analysis unit 14 and the data stored in the data storage unit 13. The replacement time estimation unit 16, which is an estimation unit, estimates the time at which the device needs to be replaced or adjusted based on the prediction result of the deterioration of the device. Specific examples of prediction of device deterioration and estimation of replacement time will be described later. The display unit 17 displays the analysis result of the deterioration analysis unit 14, the prediction result of the deterioration prediction unit 15, the estimation result of the replacement time estimation unit 16, and the like.

  Next, a hardware configuration of each system and each device according to the present embodiment will be described. As described above, the railway management system 3 of this embodiment is realized by, for example, a cloud system. In the cloud system, the hardware of the computer system and the device such as a server for each function can be arbitrarily set. For example, one computer system may have a function as a plurality of devices, or a plurality of computer systems may have a function as one device. Therefore, the railway management system 3 may be realized by one computer system or may be realized by a plurality of computers. Note that the railway management system 3 is not limited to this example, and may be realized by a system other than the cloud system. For example, the railway management system 3 may be realized by one computer system, and the diagnostic system 1 and the database system 2 may be realized by one computer system. In any case, the railway management system 3 is realized by one or more computer systems.

  A configuration example of a computer system that realizes the railway management system 3 will be described. FIG. 6 is a diagram showing a configuration example of a computer system that realizes the railway management system 3 of the present embodiment. As shown in FIG. 6, this computer system includes a control unit 101, an input unit 102, a storage unit 103, a display unit 104, a communication unit 105, and an output unit 106, which are connected via a system bus 107. There is.

  In FIG. 6, the control unit 101 is, for example, a CPU (Central Processing Unit) or the like. The control unit 101 executes a railway management program in which each process executed by the railway management system 3 of this embodiment is described. The input unit 102 is composed of, for example, a keyboard and a mouse, and is used by a user of the computer system to input various kinds of information. The storage unit 103 includes various memories such as a RAM (Random Access Memory) and a ROM (Read Only Memory), and a storage device such as a hard disk, and is a program to be executed by the control unit 101 and necessary obtained in the course of processing. Store data etc. The storage unit 103 is also used as a temporary storage area for programs. The display unit 104 includes an LCD (Liquid Crystal Display) and displays various screens for the user of the computer system. The communication unit 105 is a communication circuit or the like that performs communication processing. The communication unit 105 may be composed of a plurality of communication circuits respectively corresponding to a plurality of communication systems. The output unit 106 is an output interface that outputs data to an external device such as a printer or an external storage device. Note that FIG. 6 is an example, and the configuration of the computer system is not limited to the example of FIG. For example, the computer system may not include the output unit 106. Moreover, when the railway management system 3 is realized by a plurality of computer systems, all of these computer systems may not be the computer systems shown in FIG. For example, some computer systems may not include at least one of the display unit 104, the output unit 106, and the input unit 102 shown in FIG.

  Here, an operation example of the computer system until the diagnostic program in which the processing of the diagnostic system 1 is described in the railway management program of the present embodiment is ready to be executed will be described. In the computer system having the above configuration, for example, a diagnostic program is stored in a storage unit from a CD-ROM or a DVD-ROM set in a CD (Compact Disc) -ROM drive or a DVD (Digital Versatile Disc) -ROM drive (not shown). It is installed in 103. Then, when the diagnostic program is executed, the diagnostic program read from the storage unit 103 is stored in the area of the storage unit 103 which serves as a main storage device. In this state, the control unit 101 executes the processing as the diagnostic system 1 of the present embodiment according to the diagnostic program stored in the storage unit 103. The operation example of the computer system until the program in which the processing of the database system 2 is described in the railway management program becomes executable is the same as that of the railway management program.

  In the above description, the program describing the processing in the diagnostic system 1 is provided using the CD-ROM or the DVD-ROM as the recording medium, but the present invention is not limited to this, and the configuration of the computer system and the provided program Depending on the capacity and the like, for example, a program provided by a transmission medium such as the Internet via the communication unit 105 may be used.

  The communication unit 22 of the database system 2 shown in FIG. 1 is realized by the communication unit 105 shown in FIG. 6, and the storage unit 21 shown in FIG. 1 is a part of the storage unit 103 shown in FIG. The data management unit 23 shown in FIG. 1 is realized by the control unit 101 shown in FIG.

  The communication unit 11 of the diagnostic system 1 shown in FIG. 5 is realized by the communication unit 105 shown in FIG. The data storage unit 13 shown in FIG. 5 is a part of the storage unit 103 shown in FIG. The data acquisition unit 12, the deterioration analysis unit 14, the deterioration prediction unit 15, and the replacement time estimation unit 16 illustrated in FIG. 5 are realized by the control unit 101 illustrated in FIG. The display unit 17 shown in FIG. 5 is realized by the control unit 101 and the display unit 104 shown in FIG.

  The analysis device 6 shown in FIG. 3 is realized by a computer system. The configuration of the computer system that realizes the analysis device 6 is the same as that of the computer system shown in FIG. The analysis device 6 may be composed of a plurality of computer systems. When the analysis device 6 is composed of a plurality of computer systems, some of them may not include at least one of the display unit 104, the output unit 106, and the input unit 102. The communication unit 61 shown in FIG. 3 is realized by the communication unit 105 shown in FIG. The measurement data storage unit 62 shown in FIG. 3 is a part of the storage unit 103 shown in FIG. The analysis unit 63 shown in FIG. 3 is realized by the control unit 101 shown in FIG. The analysis result presentation unit 64 and the inspection data generation unit 66 shown in FIG. 3 are realized by the control unit 101 and the display unit 104 shown in FIG. When the inspection data generating unit 66 displays the inspection data, the display unit 104 is also used to implement the inspection data generating unit 66. The reflection unit 65 shown in FIG. 3 is realized by the input unit 102 shown in FIG.

  The control device 542 of the on-board device 54 shown in FIG. 4 is also realized by a computer system. The configuration of the computer system that realizes the control device 542 is similar to that of the computer system shown in FIG. The operation management system 41 is also realized by a computer system. The configuration of the computer system that realizes the operation management system 41 is similar to the computer system illustrated in FIG. Each of the control device 542 and the operation management system 41 may also be configured by a plurality of computer systems. When the control device 542 and the operation management system 41 are configured by a plurality of computer systems, some of them may not include at least one of the display unit 104, the output unit 106, and the input unit 102. .

  The terminal device 9 is realized by a computer system. The configuration of the computer system that realizes the terminal device 9 is similar to that of the computer system illustrated in FIG. Further, the terminal device 9 may be a computer system such as a tablet or a smartphone.

  Next, the operation of this embodiment will be described. First, as an example of the diagnosis of the device of the present embodiment, a diagnosis regarding the wear amount of the contact plate of the pantograph 51 will be described. The wear amount of the contact plate of the pantograph 51 is an example of the deterioration amount indicating the degree of deterioration of the device. FIG. 7 is a diagram showing a slide plate of a pantograph 51, which is an example of a deterioration diagnosis target of the present embodiment. The shape of the contact plate 511 shown in FIG. 7 is an example, and the shape of the contact plate 511 is not limited to the example shown in FIG. The pantograph 51 includes a contact plate 511, and the contact between the contact plate 511 and the trolley wire 55 that is an overhead wire causes the pantograph 51 to collect electric power from the trolley wire 55. Although the pantograph 51, the wheels 52, and the like are illustrated as the devices to be mounted on the vehicle 5 in the present embodiment, the sliding plates 511 and the like that configure the pantograph 51 are also devices to be mounted on the vehicle 5. That is, the components that make up a certain device are also the devices mounted on the vehicle 5.

  The friction plate 511 wears mainly due to two factors: mechanical contact with the trolley wire 55 and arc discharge generated when the trolley wire 55 is separated from the trolley wire 55. If the abrasion of the contact strip 511 progresses, it may not be possible to collect electricity. Therefore, the wear amount of the abrasion plate 511 is generally set to a limit value at which the abrasion plate 511 can be used. This limit value is set, for example, for each railway operator. When the vehicle 5 is inspected, the amount of wear of the contact plate 511 is confirmed, and when the amount of wear exceeds a limit value, the contact plate 511 is replaced.

  Therefore, in the inspection system 60, the measurement system 8 performs measurement for detecting the amount of wear of the sliding plate 511. An example of this measurement is capturing an image with a stereo camera, measuring the shape of the contact plate 511 with an ultrasonic sensor, or the like. The specific method of measurement is not limited to these and may be any measurement that can grasp the shape of the contact plate 511. The analysis device 6 acquires the measurement data measured by the measurement system 8 via the data collection device 7, and analyzes the acquired measurement data.

  As shown in FIG. 7, the longitudinal direction of the sliding plate 511 is the X axis, and the lateral direction of the sliding plate 511 is the Y axis. The positive direction of the X-axis is to the right of the paper, the positive direction of the Y-axis is the direction obtained by rotating the positive direction of the X-axis by 90 degrees, and the Z-axis is defined so that the XYZ coordinate system is the right-handed system. To do. At this time, the upper surface of the contact plate 511 whose normal line faces the positive direction of the Z axis comes into contact with the trolley wire 55. As shown in FIG. 7, the origin of the XYZ coordinate system is provided on the upper surface when no wear occurs. In this case, the wear generally progresses in the negative direction of the Z axis.

  FIG. 8 is a diagram showing an example of the shape of the sliding plate 511 measured by the measuring system 8 of the present embodiment. FIG. 8 shows the shape of the contact plate 511 when the XYZ coordinate system is defined as shown in FIG. The vertical axis of FIG. 8 corresponds to the Z axis of the XYZ coordinate system of FIG. 7. The numerical value on the vertical axis in FIG. 8 indicates the amount of displacement from the origin, that is, the state without wear. Therefore, the absolute value of the numerical value on the vertical axis of FIG. 8 is the wear amount. The plane orthogonal to the vertical axis in FIG. 8 corresponds to the XY plane in FIG. In FIG. 8, the numerical value shown on the axis orthogonal to the vertical axis indicates the position of the sliding plate 511 in the X-axis direction. Similarly, although the numerical values are not shown, the depth direction of the paper surface of FIG. 8 indicates the position of the sliding plate 511 in the Y-axis direction. It should be noted that the definition of the XYZ coordinate system shown in FIGS. 7 and 8 is an example, and it is sufficient that it is defined so that the shape of the contact plate 511 can be understood, and the definition of the coordinate system is the example shown in FIGS. 7 and 8. Not limited to.

  The wear amount of the contact plate 511 generally increases as time passes. That is, wear progresses over time. The inspection system 60 can present information for grasping the progress of wear to the worker who performs the inspection. Specifically, the analysis device 6 accumulates the measurement data, analyzes the accumulated measurement data, and displays the analysis result. This makes it easier for the operator to grasp the tendency of the wear of the contact strip 511 to change over time.

  FIG. 9 is a diagram showing an example of the analysis result of the analysis device 6 according to the present embodiment. FIG. 9 shows the result of analysis performed by the analysis device 6 based on the measurement data of the shape of the contact strip 511 measured on different days. Note that here, the measurement cycle, that is, the number of days from one measurement day to the next measurement day is fixed, but the measurement cycle may not be fixed. In the upper part of FIG. 9, three measurement data with different measurement dates are shown. These three measurement data are examples of the measurement data respectively measured at a plurality of dates and times. Similar to the example shown in FIG. 8, the measurement data on each measurement day represents the shape of the contact plate 511 in the XYZ coordinate system. In the lower part of FIG. 9, the analysis unit 63 of the analysis device 6 calculates the maximum value 200 of each wear amount from these three measurement data, and associates the calculated maximum value 200 with the measurement date to analyze the result. The example obtained as is shown. The wear amount actual value 201 shown in FIG. 9 shows a change in the wear amount when the horizontal axis is the date. Note that, as in FIG. 8, the vertical axis of FIG. 9 is actually the displacement in the Z-axis direction from the time when no wear occurs, so the actual wear amount value 201 is shown as a negative value. The absolute value of this value is the actual value of the amount of wear as the amount of wear. The analysis result presentation unit 64 presents the analysis result to the worker by displaying such an analysis result as a graph as shown in FIG. 9. The actual wear amount value 201 is an example of a deterioration amount indicating the degree of deterioration of the device corresponding to each of a plurality of dates and times calculated based on the measurement data. Further, at this time, the analysis result presentation unit 64 displays the measurement data shown in the upper part of FIG. 9 together with the analysis result. Although an example in which the measurement data is displayed together with the analysis result is shown here, only the analysis result may be displayed depending on the device to be analyzed and the content of the analysis.

  By visually observing the analysis result, the operator can confirm how the wear amount of the sliding plate 511 changes with time. Further, the wear amount actual value 201 of FIG. 9 corresponds to the maximum value 200 of the wear amount on each measurement day, but the place to be inspected when evaluating the deterioration of the contact plate 511 is the maximum wear amount value. Not necessarily. For example, the wear amount at a location other than the maximum value may be the target of the inspection because the influence of wear varies depending on the position of the sliding plate 511 in the Y-axis direction. In such a case, the operator changes the point to be extracted from the measurement data from the maximum value 200 to the evaluation target point 202. In detail, for example, the diagram shown in FIG. 9 is displayed, and the evaluation target point 202 may be input by selecting it with the mouse on the display screen, or the position in the XY plane to be the evaluation target point 202. The coordinates may be input as numerical values. The reflection unit 65 receives an input of information indicating the evaluation target point 202 and passes it to the inspection data generation unit 66. The inspection data generation unit 66 corrects the analysis result based on the information received from the reflection unit 65 and generates inspection data. The wear amount actual value 301 shown in FIG. 9 is an example of inspection data.

  The analysis device 6 may hold and store the correspondence between the measurement data and the input information received by the reflecting unit 65, and machine-learn the stored information. For example, a machine learning model such as a neural network is used to learn measured data that is an input and input information that is a result as teacher data. As a result, when receiving the measurement data, the analysis device 6 may estimate the input information using the learned model and display the estimated input information together with the analysis result. The analysis device 6 transmits the set of the measurement data and the input information to the database system 2, and the diagnostic system 1 receives the information from the database system 2 so that the diagnostic system 1 performs the machine learning described above. You can go.

  As described above, in the inspection system 60, the operator can check the actual value and perform the inspection. Further, although the worker can predict the future change in the wear amount of the contact plate 511 to some extent based on the inspection data, the wear amount of the contact plate 511 does not actually depend on the elapsed days itself. . As described above, the main causes of wear of the contact plate 511 are mechanical contact and arc discharge. Therefore, for example, when the vehicle 5 is not operated due to a failure or the like and remains at the vehicle depot, the progress of wear is suppressed. Therefore, in order to predict the wear amount of the contact strip 511, it is desirable to consider not only the elapsed time but also the correlation with other information. Considering that the main factors of wear of the contact plate 511 are mechanical contact and arc discharge, it is considered that the amount of wear of the contact plate 511 substantially depends on the traveling distance of the vehicle 5. Therefore, if the wear amount is expressed as a function of the traveling distance, it can be expected that a more accurate function is obtained than when the wear amount is expressed as a function of the elapsed time. On the other hand, there are some aspects where the details of what causes wear of the contact plate 511 and how it progresses are not clear. Therefore, it is considered effective to analyze the amount of wear of the contact strip 511 in association with various pieces of information regarding the vehicle 5 in order to elucidate the mechanism of occurrence of wear of the contact strip 511. It is considered that not only the sliding plate 511 but also the in-vehicle device 50 of the vehicle 5 as a whole is analyzed by associating the measurement data with various pieces of information about the vehicle 5, and is effective for clarifying the mechanism of deterioration.

For example, assume that the wear of the contact plate 511 depends on ten state quantities of the vehicle 5 from a ₁ to a ₁₀ . In this case, the amount of wear of the contact plate 511 can be expressed by a function f (a ₁ , a ₂ , ..., A ₁₀ ) relating to a ₁ to a ₁₀ . The state quantity of the vehicle 5 is, for example, the traveling distance, the number of curves of the route traveled, the number of times the vehicle travels at a speed equal to or higher than a certain value, or the like. Of these, if a function indicating the wear amount is calculated in consideration of only one state quantity, the accuracy of the function will be lower than that obtained when a function of 10 state quantities a ₁ to a ₁₀ is obtained. The accuracy of the prediction when the prediction is performed using the function is also low. Therefore, if it is known what the state quantities a ₁ to a ₁₀ are, it is possible to realize highly accurate prediction by measuring all of them and obtaining a function based on the measurement data. However, in practice, since the mechanism of wear of the contact plate 511 has not been completely clarified, it is not possible to determine what state quantity should be considered. Even if the wear of the contact plate 511 depends on the 10 state quantities a ₁ to a ₁₀ , the contribution to the wear of the contact plate 511 is small among these state quantities, and the state quantity should be considered. There is a possibility that the amount of wear of the friction plate 511 can be predicted with sufficient accuracy.

  From the above, by making it possible to associate the inspection data of the wear amount of the sliding plate 511 with various pieces of information regarding the vehicle 5, it is possible to improve the accuracy of analysis such as calculation of a function indicating the wear amount of the sliding plate 511. Increases the possibility of achieving improvement. In the present embodiment, as shown in FIG. 1, the railway management system 3 collects and accumulates travel data, operation information, and inspection data, and uses these to start analysis of the wear amount of the sliding plate 511. By analyzing the deterioration of each device, it is possible to realize at least one of a highly accurate analysis and an efficient analysis of the device deterioration.

  When the analysis device 6 generates the inspection data, the analysis device 6 transmits the inspection data to the database system 2. As illustrated in FIG. 9, when the inspection data is generated using the past measurement data as well, the inspection data may include a portion that has already been transmitted. In this case, the analysis device 6 may send only the updated data to the database system 2. The database system 2 stores the received inspection data in the storage unit 21. At this time, the data management unit 23 stores the inspection data in the storage unit 21 for each device of each vehicle 5.

  Hereinafter, the operation of the diagnostic system 1 of the present embodiment will be described. FIG. 10 is a flowchart showing an example of a diagnostic processing procedure in diagnostic system 1 of the present embodiment. As shown in FIG. 10, the diagnostic system 1 acquires inspection data corresponding to the device to be diagnosed, travel data corresponding to the inspection data, and operation information (step S1). Specifically, the data acquisition unit 12 acquires the inspection data corresponding to the device to be diagnosed, the traveling data and the operation information corresponding to the inspection data from the database system 2 via the communication unit 11, and the data storage unit Store in 13. The inspection data, the travel data, and the operation information may be managed in association with each other using the organization information. If the database system 2 and the diagnostic system 1 are realized by the same computer system, step S1 need not be performed. In this case, the data storage unit 13 is integrated with the storage unit 21.

  FIG. 11 is a diagram showing a configuration example of inspection data according to the present embodiment. As shown in FIG. 11, the inspection data includes, for example, organization information (vehicle number) for identifying the vehicle 5, a device ID (IDentifier) indicating a device, and an analysis result for each date and time. That is, the inspection data includes the deterioration amount of the device corresponding to each of the plurality of dates and times calculated based on the measurement data measured at each of the plurality of dates and times. The analysis result included in the inspection data is an analysis result in which the input from the operator via the above-described reflection unit 65 is reflected, but the analysis result itself by the analysis unit 63 of the analysis device 6 is also included in the inspection data. May be included. Further, the inspection data may include the measurement data of the measurement system 8. Thus, in the database system 2, the inspection data is managed for each device of each vehicle 5. Therefore, the diagnostic system 1 can acquire the inspection data of the device to be diagnosed from the database system 2 by designating the vehicle 5 and the device to be diagnosed. The specific format of the inspection data is not limited to the example shown in FIG.

  FIG. 12 is a diagram showing an example of travel data according to the present embodiment. In the example shown in FIG. 12, the travel data includes organization information (vehicle number) and control commands, responses, state values, etc. corresponding to each device for each date and time. In addition, when the control command, the response, and the state value are periodically acquired, it is not necessary to individually add the date and time, and only the date and time of the first data of these data may be shown. The specific format of the traveling data is not limited to the example shown in FIG. The control command is, for example, a notch command, a brake command, or the like. The state value is, for example, the speed of the vehicle 5, the weight of the vehicle 5, the temperature inside the vehicle 5, the outside air temperature, the air spring pressure of the truck, the brake pipe pressure, the brake cylinder pressure, or the like.

  FIG. 13 is a diagram showing an example of route state information included in the operation information according to the present embodiment. As shown in FIG. 13, the line status information includes a line name, a distance that is the total distance of the line, the number of stop stations, curve information, and inspection information. Although not shown, the operation information may include organization information (vehicle number). In FIG. 13, the route name is described as an example of the route identification information for identifying the route, but the route identification information is not limited to the route name. The number of stops is indicated for each train type such as rapid, normal, and limited express. The curve information includes the position and curvature of the curve on the line. The curve information is not limited to the above-mentioned example as long as it is information about the curve of the route, and may be the total number of curves. The inspection information is information indicating that some abnormality is detected in the inspection of the route. The inspection information may include, for example, information indicating when the trolley wire is updated, presence / absence of abnormality of the trolley wire, and the like. When the inspection information includes such information about the trolley wire, the deterioration analysis unit 14 can analyze, for example, the relationship between the state of the trolley wire and the wear amount of the sliding plate 511 of the pantograph 51. The curve information and the inspection information of the route state information may not be included in the operation information and may be directly input to the diagnostic system 1. Alternatively, the database system 2 may collect the curve information and the inspection information from another device and add the curve information and the inspection information to the route state information of the operation information acquired from the operation management system 41.

  Returning to the description of FIG. After step S1, the diagnostic system 1 acquires route information of the corresponding vehicle from the traveling data and the operation information (step S2). Specifically, the data acquisition unit 12 generates route information by extracting the information corresponding to the route information of the corresponding vehicle from the travel data and the operation information stored in the data storage unit 13 to generate the route information. The information is stored in the data storage unit 13. The route information includes at least information indicating the route on which the vehicle has traveled, but here also includes information indicating a route on which the vehicle 5 will travel in the future. When the route information includes information indicating a route on which the vehicle 5 will travel in the future, the route information can be used in the prediction of the deterioration amount described later. The data acquisition unit 12 can acquire information indicating a route on which the vehicle 5 will travel in the future from the operation plan of the operation information. If the route information can be generated only from the operation information, the data acquisition unit 12 generates the route information from the operation information without using the travel data.

  FIG. 14 is a diagram showing an example of route information according to the present embodiment. As described above, the route information is generated based on the operation information, for example. The database system 2 stores route information for each vehicle number and date of the vehicle 5. The route information includes at least information indicating which route the vehicle 5 has traveled for each vehicle 5. In the example shown in FIG. 14, the route information includes route identification information for identifying a route such as a route name, information indicating a train type such as high speed and normal, and time zone information indicating a time zone in which the vehicle 5 operates. Indicates. As for the time zone information, the number of passengers, the temperature, etc. may differ depending on the time zone of the day, such as early morning, morning rush hours, daytime hours, evening rush hours, and night hours. It is divided into time zones and indicates whether or not each route has traveled in the time zone in which the vehicle 5 traveled. Further, information indicating the division between weekdays and holidays may be added to the time zone information. The division of time zones is not limited to the above example.

  Here, an example in which the data acquisition unit 12 of the diagnostic system 1 generates route information will be described, but the data management unit 23 of the database system 2 generates route information based on the operation information, and the diagnostic system 1 The route information may be acquired from the database system 2. Further, the diagnostic system 1 uses the route information by generating the route information and extracting the corresponding information from at least one of the travel data and the operation information, and using the information corresponding to the route information. Processing may be carried out. Also in this case, it is equivalent to performing the process using the route information.

  Returning to the description of FIG. After step S2, the diagnostic system 1 analyzes the record of the deterioration of the device based on the inspection data and the route information (step S3). Specifically, the deterioration analysis unit 14 analyzes the actual performance of deterioration of the device based on the inspection data and the route information stored in the data storage unit 13. For example, the deterioration analysis unit 14 uses the route information to refer to the corresponding route state information, so that the actual traveling state of the vehicle 5 at the date and time corresponding to each deterioration amount that is each analysis result in the inspection data. Is obtained, and the correspondence between the first information and the deterioration amount is obtained. An example of the first information is the past travel distance as described above, but the present invention is not limited to this, and may be information regarding the curve of the route traveled by the vehicle 5 equipped with the device, the number of stopped stations, and the like. . Furthermore, the first information may be inspection information described later regarding the route along which the vehicle 5 travels. The correspondence between the first information and the deterioration amount is indicated by, for example, a parameter indicating the relationship between the first information and the deterioration amount. As described above, the analysis result by the deterioration analysis unit 14 includes, for example, a parameter indicating the relationship between the first information and the deterioration amount. Specific examples of parameters will be described later.

  FIG. 15 is a diagram showing an example of an analysis result of the device deterioration record according to the present embodiment. The example shown in FIG. 15 shows an analysis result 305 analyzed by the deterioration analysis unit 14 using the inspection data of the wear amount of the contact plate 511 illustrated in FIG. 9. In FIG. 9, the wear amount actual value 301 is the date on the horizontal axis, but the analysis result 305 of FIG. 15 is shown by the travel distance on the horizontal axis. The measurement points 302, 303, 304 are points corresponding to the measurement days of the first, second, and third days shown in FIG. 9, respectively. In the example shown in FIG. 15, the amount of wear of the sliding plate 511 is close to a straight line by setting the travel distance on the horizontal axis. In this way, when the wear amount of the contact strip 511 has a higher correlation with the travel distance than the elapsed days, by setting the travel distance on the horizontal axis, it becomes easier to understand the wear tendency. It should be noted that, here, the travel distance is taken as an example, but instead of this, it is also possible to use the curve information of the route state information and to set the total number of curves on the horizontal axis. It is also possible to display in three dimensions to confirm the degree of dependence on both the distance traveled and the total number of curves.

  Further, for example, the deterioration analysis unit 14 can also perform analysis such as calculating the relationship between the travel distance and the deterioration amount of the device for each train type. Similarly, it is possible to perform an analysis such as calculating the relationship between the traveling distance and the deterioration amount of the device for each train type and each time zone. Further, an average value of the number of passengers for each time zone of each route is calculated, and the number of passengers for each route and time zone is stored in the data storage unit 13 as congestion degree information. The history of the weight of the vehicle 5 may be estimated by calculating the number of passengers based on the route information and the congestion degree information. The deterioration analysis unit 14 may analyze the amount of deterioration of the device using the weight history of the vehicle 5. As the congestion degree information, the weight itself may be held for each route and time period based on the number of passengers.

In addition, the deterioration analysis unit 14 uses not only the route state information but also the traveling data to perform an analysis such as obtaining a correlation between the integrated value of the time when the speed is a certain value or more and the wear amount of the contact strip 511. You can go. Similarly, the correlation between the various state values stored as the traveling data itself, the number of times of braking calculated from the traveling data, and the wear amount of the sliding plate 511 is obtained, and the one having a high correlation is plotted on the horizontal axis. It is also possible to display the amount of wear of the plate 511. Not only the amount of wear of the contact plate 511 but also the deterioration of each device can be similarly analyzed. The deterioration analysis unit 14 can select, for example, data having a high correlation with the deterioration amount indicating the deterioration of each device such as the wear amount of the sliding plate 511 and expressing the deterioration amount as a function of the selected data. Specifically, the deterioration analysis unit 14 approximates the wear amount f (R) of the contact strip 511 by a linear regression analysis as a linear function of the traveling distance R as shown in the following equation (1). Parameters b ₁ and b ₂ are calculated. Equation (1) is an example of performing a two-dimensional linear regression analysis, but multidimensional linear regression analysis is performed to calculate each parameter for calculating the wear amount of the contact strip 511 as a function of a plurality of variables. Good. In addition to the linear regression analysis, a regression analysis for approximating the relationship between variables such as the traveling distance and the wear amount of the contact strip 511 by a polynomial may be performed, and the coefficient of the polynomial may be obtained as each parameter. These parameters are examples of parameters indicating the relationship between the first information and the deterioration amount.
f (R) = b _{1 ·} R + b ₂ (1)

  Returning to the description of FIG. After step S3, the diagnostic system 1 predicts the deterioration of the device based on the analysis result of step S3 and the operation information (step S4). Specifically, the deterioration prediction unit 15 predicts the deterioration of the device based on the analysis result of the deterioration analysis unit 14 and the operation plan included in the operation information. For example, when the route information includes information indicating the route on which the future vehicle 5 travels, the deterioration prediction unit 15 uses the route information to acquire the second information indicating the future traveling state of the vehicle 5, A future deterioration amount of the device is predicted based on the second information and the parameter. The second information is the same kind of information as the first information such as the traveling distance, but the first information is past information, whereas the second information is future information. For example, when the wear amount of the sliding plate 511 is calculated as a function of the traveling distance by the analysis in step S3, the distance of each route is acquired from the route state information based on the operation plan or the route information. The running distance of the vehicle 5 for each future date and time is obtained, and the wear amount of the sliding plate 511 is predicted.

  Next, the diagnostic system 1 estimates the replacement time (step S5). Specifically, the replacement time estimation unit 16 estimates the replacement time of the device using the predicted value of the deterioration prediction unit 15 and the predetermined replacement condition of the device. The condition for replacing the device is, for example, a condition that the wear amount exceeds a limit value when the device is the sliding plate 511. Further, the replacement time estimation unit 16 may estimate the time when the device needs to be adjusted based on the prediction result and a predetermined condition for adjusting the device. One example of adjustment is the work of scraping the wheel 52 to remove wear and flats on the wheel cross section. The wheel cross section here is a cross section of the wheel 52 when the cut surface is a surface including the wheel 52, and the wear of the wheel cross section is such that the shape of the wheel 52 in this cross section is worn away from the original shape. Means These conditions regarding replacement and adjustment are defined for each device, and the replacement time estimation unit 16 holds the conditions for each device. This condition may be set in the diagnostic system 1 via the terminal device 9, or may be set by receiving the diagnostic system 1 from the analysis device 6, or may be set directly in the diagnostic system 1 by an operator or the like. It may be entered.

  Next, the display unit 17 presents the result (step S6). The display unit 17 displays, for example, the result obtained by the above processing. The displayed result may be the analysis result of step S3, the prediction result of step S4, the estimated value of the replacement time of step S5, or a combination thereof. May be. The display unit 17 may be capable of switching between a graph showing the deterioration amount with respect to the date and a graph showing the deterioration amount with respect to the first information. The diagnostic system 1 may transmit these results to the terminal device 9, and the terminal device 9 may display these results.

  FIG. 16 is a diagram showing a display example of the prediction result of the wear amount of the sliding plate 511 in the present embodiment. In the example shown in FIG. 16, the predicted value 306 calculated in step S4 is displayed together with the wear amount actual value 301 shown in FIG. In FIG. 16, since the date is plotted on the horizontal axis, the operator can easily understand the replacement time. The limit value 307 shown in FIG. 16 shows the limit value of the wear amount.

  As described above, in the present embodiment, the route information can be used to associate the inspection data with the information regarding the route on which the vehicle 5 has traveled, which corresponds to the inspection data. Can be analyzed. Therefore, the accuracy of analysis can be improved. Furthermore, if the analysis is performed using the traveling data, the accuracy of the analysis can be further improved.

  Further, in the above description, the wear amount of the sliding plate 511 of the pantograph 51 has been described as an example, but as described above, it is also possible to analyze and predict the deterioration of the other in-vehicle device 50. FIG. 17 is a diagram showing wear of a wheel cross section, which is an example of deterioration of the present embodiment. FIG. 17 schematically shows a cross section of the wheel 52 when the cross section passing through the axle 57 is a cut surface. The wheel 52 is provided with a flange as shown in the right end portion of the wheel 52 in FIG. The flat portion on the right side of the wheel 52 is a contact surface (wheel tread) that comes into contact with the track. The boundary between the flange and the wheel tread is a gently curved surface. In FIG. 17, the normal shape of the wheel 52 is indicated by a solid line, and the shapes of the wheel 52 when the shape of the wheel 52 changes due to two types of wear are indicated by dashed-dotted lines as wear shapes 521 and 522, respectively. .

  The wear shape 521 schematically shows the shape of the cross section of the wheel 52 when the flange wear of the wheel 52 is scraped. When the flange wear occurs, as indicated by the wear shape 521, the curved surface connecting the flange and the wheel tread becomes steeper or the thickness of the flange decreases as compared with the normal state. The wear shape 522 schematically shows the shape of the cross section of the wheel 52 when wear occurs such that the slope of the wheel tread changes. When the wheel cross-section wear, which is the wear that changes the cross-sectional shape of the wheel 52 as shown by the wear shapes 521 and 522, may cause a serious accident such as derailment of the vehicle 5. Therefore, when the wear of the cross section of the wheel progresses, the adjustment work of scraping the wheel tread of the wheel 52 is performed. Further, when the wear is more advanced and cannot be dealt with by the adjustment work, the wheels 52 are replaced. The condition of how much the wear of the wheel cross section progresses before the adjustment work is predetermined. Therefore, in the measurement system 8 of the inspection system 60, the in-orbit device 82 measures the cross section of the wheel with a measuring device such as a camera or a laser, and detects the wear generated on the wheel 52. The analysis device 6 analyzes the change in the wear amount of the wheel cross section, similarly to the wear amount of the sliding plate 511 described above. The amount of wear to be analyzed is, for example, at least one of the thickness of the flange, the thickness of the wheel 52, the radius of curvature of the curved surface connecting the flange and the wheel tread, the gradient of the wheel tread, and the like. Since the wear amount of these wheel cross sections depends on the shape of the track, the curve amount, etc., the diagnostic system 1 treats the wear amount of the wheel cross section as the deterioration amount, and analyzes the same as the wear amount of the sliding plate 511 described above. It is also possible to make a prediction. Further, the diagnostic system 1 can also estimate the adjustment or replacement timing of the wheels 52 using the above-mentioned adjustment and replacement conditions.

  Similarly, the measurement system 8 can perform measurement for detecting the inclination, the degree of rise, the damage to the insulator, and the like of the pantograph 51. Moreover, the measurement system 8 can perform measurement for detecting the appearance of the vehicle 5, that is, the scratches, dents, and the like of the vehicle body. In addition, the measurement system 8 measures the wear of the brakes, the insulation deterioration of the motor, the deterioration degree of the trolley, the deterioration of materials such as gears, gear boxes, and motors. Various measurements such as measurement for detecting the degree can be performed. Examples of the wear of the brake include wear of the brake shoe in the tread brake and wear of the lining in the disc brake. As an index indicating the degree of deterioration of the dolly, the number and size of scratches, cracks, and the like obtained by acquiring an image can be mentioned. Another index representing the degree of deterioration of the dolly is the height of the vehicle body calculated from the image. It is possible to grasp the degree of deterioration of the air spring due to obtaining the height of the vehicle body. Further, the temperature may be measured with a thermo camera or the like as the measurement for detecting the degree of deterioration of the device. For example, in order to detect the degree of deterioration of materials such as a trolley, a gear, a gear box, and a motor, the temperatures of locations corresponding to these may be measured. The diagnostic system 1 uses the inspection data generated using these measurement data to analyze the actual amount of deterioration indicating the degree of deterioration of these devices, as well as the amount of wear of the sliding plate 511, and to perform deterioration. It is possible to predict the amount and to estimate when it will be in a state that requires replacement or adjustment. In addition, the database system 2 collects various information of the vehicles 5 operated by a plurality of railway operators as well as the various vehicles 5 operated by a single railway operator. The diagnosis system 1 of the above-described form can provide the diagnosis result of the deterioration of the vehicle 5 to a plurality of railway operators.

  As described above, in the present embodiment, the diagnostic system 1 analyzes the deterioration of the device based on the inspection data for the inspection of the device of the vehicle 5 and the route information of the vehicle 5. Therefore, at least one of improvement in analysis accuracy and efficient analysis can be achieved. Furthermore, if the analysis is performed using the traveling data, the accuracy of the analysis can be further improved.

Embodiment 2.
FIG. 18 is a diagram showing a configuration example of a diagnostic system according to the second exemplary embodiment of the present invention. The railway management system according to the present embodiment is the same as the railway management system 3 according to the first embodiment except that a diagnostic system 1a is provided instead of the diagnostic system 1 according to the first embodiment. The terminal device 9, the inspection system 60, the operation management system 41, the wireless device 42, and the vehicle 5 of this embodiment are the same as those of the first embodiment. The same components as those in the first embodiment are designated by the same reference numerals as those in the first embodiment, and redundant description will be omitted. Hereinafter, differences from the first embodiment will be mainly described.

  As shown in FIG. 18, the diagnostic system 1a is the same as the diagnostic system 1 except that the learning unit 18 is added to the diagnostic system 1 of the first embodiment and a data storage unit 13a is provided instead of the data storage unit 13. is there. In the present embodiment, the deterioration prediction unit 15 stores the predicted result in the data storage unit 13a as the estimation result. The estimation result also stores the inspection data used for the prediction. When the learning unit 18 acquires the actual value of the deterioration amount, which is the deterioration amount included in the inspection data corresponding to the estimation result stored in the data storage unit 13a, the learning unit 18 calculates the difference between the actual value and the estimation result. The learning unit 18 generates a machine learning model such as a neural network by associating the parameters used for the prediction of the deterioration prediction unit 15 with the differences and using them as teacher data. This parameter is a parameter indicating the relationship between the above-described first information and the deterioration amount. That is, the learning unit 18 calculates the difference between the predicted value predicted by the deterioration prediction unit 15 and the actual value of the deterioration amount at the date and time corresponding to the predicted value calculated based on the measurement data, and the deterioration prediction unit The relationship between the parameter used for the prediction of 15 and the difference is learned.

  When the learning unit 18 receives the new inspection data, the learning unit 18 calculates the estimated difference value using the learned machine learning model. By using the estimated value of the difference, the deterioration prediction unit 15 corrects the parameter, so that highly accurate prediction can be realized. In addition, when learning the difference, the database system 2 may perform machine learning based on the information of the same device of all the vehicles 5 for which information is collected, or for each railway operator or for each route traveled. Machine learning may be performed. For example, the learning unit 18 calculates the difference between the predicted value obtained by calculating the relationship between the mileage and the wear amount for the rolling stock 511 of the pantograph 51 and the corresponding actual value for the vehicles 5 of all railway operators. Then, a pair of a parameter indicating the relationship between the traveling distance and the wear amount and the difference is learned as teacher data. Then, the learning unit 18 corrects the parameters by acquiring new inspection data, inputting the parameter indicating the relationship between the traveling distance and the wear amount into the learned model and obtaining the estimated value of the difference. Alternatively, using a plurality of data sets of the wear amount and the corresponding mileage and the above-mentioned difference as teacher data, machine learning is performed, and when new inspection data is acquired, data of the mileage and the wear amount is acquired. The set may be input into a trained model to obtain an estimate of the difference. Further, not only the distance traveled, but also information obtained from the route state information of the vehicle 5 corresponding to the inspection data, all information such as the state value of the traveling data, and the data set of the above difference are used as the teacher data. Machine learning may be performed.

Embodiment 3.
FIG. 19 is a diagram showing a configuration example of a diagnostic system according to the third embodiment of the present invention. The railway management system of the present embodiment is the same as the railway management system 3 of the first embodiment except that a diagnostic system 1b is provided instead of the diagnostic system 1 of the first embodiment. The terminal device 9, the inspection system 60, the operation management system 41, the wireless device 42, and the vehicle 5 of this embodiment are the same as those of the first embodiment. The same components as those in the first embodiment are designated by the same reference numerals as those in the first embodiment, and redundant description will be omitted. Hereinafter, differences from the first embodiment will be mainly described.

  As shown in FIG. 19, the diagnostic system 1b is the same as the diagnostic system 1 except that a classification unit 19 is added to the diagnostic system 1 of the first embodiment and a data storage unit 13b is provided instead of the data storage unit 13. is there.

  In the present embodiment, the inspection data includes not only the device ID, but also manufacturing information indicating the manufacturer of the device, the model number of the device, the manufacturing date, the lot number, and the like. The manufacturing information includes at least information indicating the manufacturer of the device. For example, FIG. 20 is a diagram showing an example of inspection data according to the present embodiment. The diagnostic system 1b holds these results as grouping information for each manufacturing information in the data storage unit 13b after the processing up to step S3 or the processing up to step S4 shown in FIG. 10 is performed. Since the diagnosis system 1b of the present embodiment can perform analysis based on the information of a large number of vehicles 5, by grouping the analysis results of deterioration and the like for each manufacturing information, the abnormality of the product itself or the abnormality of the lot can be obtained. Etc. can be detected.

  FIG. 21 is a diagram showing an example of the grouping result of this embodiment. FIG. 21 shows the actual value and predicted value of deterioration of each group after grouping by manufacturing information by the classification unit 19. The classification unit 19 stores the actual value and predicted value of deterioration for each group in the data storage unit 13b as grouping information. FIG. 21 shows the actual value and predicted value of the wear amount of the three groups, taking the wear amount of the sliding plate 511 of the pantograph 51 as an example. The wear amount 401 indicates the actual value and the predicted value of the wear amount of the group # 1, the wear amount 402 indicates the actual value and the predicted value of the wear amount of the group # 2, and the wear amount 403 indicates the wear of the group # 3. The actual value and the predicted value of the quantity are shown. The solid line portion is the actual value, and the broken line portion is the predicted value. In the example shown in FIG. 21, the amount of wear of the sliding plates 511 of the lot corresponding to the group # 3 is large. Note that FIG. 21 shows an example in which the predicted value is also displayed, but only the actual value may be displayed. The classification unit 19 may classify the analysis results by the deterioration analysis unit 14 for each device manufacturer, or for each manufacturer and date of manufacture, that is, for each lot.

  In addition, each device is not always mounted in the same vehicle 5 and may be replaced in another vehicle 5 in the middle. For example, even if the mileage of the vehicle 5 is known, the true mileage corresponding to the replaced device cannot be grasped. For this reason, if such transfer information is managed as trace information, the deterioration focusing on the device can be analyzed more accurately. FIG. 22 is a diagram showing an example of the trace information according to the present embodiment. As shown in FIG. 22, the trace information indicates the device ID, the manufacturing information corresponding to the device, and the information indicating which vehicle 5 is installed from when to when. For example, by combining this trace information and the route information described in the first embodiment, the traveling distance corresponding to each device can be calculated. As a result, it is possible to improve the traceability of each device and improve the accuracy of analysis of device deterioration. The trace information may not include the manufacturing information. Even if the classification is not performed based on the manufacturing information, the analysis accuracy and the prediction accuracy can be improved by analyzing and predicting the deterioration for each device.

  In the example described above, the classification unit 19 is added to the diagnostic system 1 of the first embodiment, but the classification unit 19 may be added to the diagnostic system 1a of the second embodiment. In this case, the learning unit 18 may learn the estimation result for each group.

  The configurations shown in the above embodiments show an example of the content of the present invention, and can be combined with other known techniques, and the configurations of the configurations are possible without departing from the gist of the present invention. It is also possible to omit or change parts.

  1, 1a, 1b Diagnostic system, 2 database system, 3 railway management system, 5 vehicles, 6 analysis device, 7 data collection device, 8 measurement system, 9 terminal device, 11, 22, 61 communication unit, 12 data acquisition unit, 13, 13a, 13b data storage unit, 14 deterioration analysis unit, 15 deterioration prediction unit, 16 replacement time estimation unit, 17 display unit, 18 learning unit, 19 classification unit, 21 storage unit, 23 data management unit, 41 operation management system , 42, 541 wireless device, 50-1, 50-2 in-vehicle device, 51 pantograph, 52 wheels, 53 underfloor device, 54 on-board device, 55 trolley wire, 62 measurement data storage unit, 63 analysis unit, 64 analysis result presentation Unit, 65 reflection unit, 66 inspection data generation unit, 511 contact plate, 542 control device.

Claims (22)

A deterioration amount indicating the degree of deterioration of the device corresponding to each of the plurality of dates and times calculated based on measurement data obtained by measuring the state of the device mounted on the railroad vehicle at each of the plurality of dates and times, and A data acquisition unit that acquires operation information including route information indicating the route traveled,
Deterioration using the route information to obtain first information indicating a track record of the running state of the railway vehicle, and analyzing deterioration of the device using the first information and the deterioration amounts at the plurality of dates and times. An analysis section,
A diagnostic system comprising: A deterioration prediction unit that predicts the future deterioration amount of the device using the analysis result by the deterioration analysis unit,
The diagnostic system according to claim 1, further comprising: The analysis result includes a parameter indicating a relationship between the first information and the deterioration amount,
The deterioration prediction unit acquires second information indicating a future traveling state of the railway vehicle using the route information, and predicts a future deterioration amount of the device based on the second information and the parameter. The diagnostic system according to claim 2, wherein: An estimation unit that estimates a time when the device needs to be replaced or adjusted, based on a prediction result by the deterioration prediction unit and a predetermined condition for replacement or adjustment of the device,
The diagnostic system according to claim 2, further comprising: The difference between the predicted value predicted by the deterioration prediction unit and the actual value of the deterioration amount at the date and time corresponding to the predicted value calculated based on the measurement data is calculated, and the deterioration amount at the plurality of dates and times. And a learning unit for learning the difference,
Equipped with
The deterioration prediction unit predicts a future deterioration amount based on the analysis result and an estimated value of the difference obtained by the learning of the learning unit. Diagnostic system described. A classification unit that classifies the analysis result by the deterioration analysis unit for each manufacturer of the device,
The diagnostic system according to any one of claims 1 to 5, further comprising:   7. The diagnostic system according to claim 6, wherein the classification unit further classifies the analysis result by the deterioration analysis unit according to manufacturing date.   The deterioration of the device is analyzed for each device based on the trace information indicating the history of the railway vehicle on which the device is mounted for each device. Diagnostic system described in one.   9. The diagnostic system according to claim 1, wherein the first information includes a travel distance of a railway vehicle equipped with the device.   The diagnostic system according to any one of claims 1 to 9, wherein the first information includes information about a curve of a route traveled by a railway vehicle on which the device is mounted.   The diagnostic system according to any one of claims 1 to 10, wherein the route information includes information indicating a train type.   The diagnostic system according to any one of claims 1 to 11, wherein the route information includes a time zone in which the railway vehicle is in operation. The data acquisition unit is data acquired from the railway vehicle and is data including at least one of a control command in the railway vehicle, a response to the control command, and a state value obtained by measuring the state of the railway vehicle. Get the data,
13. The diagnostic system according to claim 1, wherein the deterioration analysis unit further analyzes deterioration of the device based on the traveling data. The device includes a pantograph contact plate,
The diagnostic system according to any one of claims 1 to 13, wherein the deterioration amount includes an abrasion amount of a pantograph contact plate.   15. The diagnostic system according to claim 1, wherein the device includes a pantograph.   The diagnostic system according to any one of claims 1 to 15, wherein the device includes wheels.   17. The diagnostic system according to claim 1, wherein the device includes a brake.   The diagnostic system according to claim 1, wherein the device includes a motor.   The diagnostic system according to any one of claims 1 to 18, wherein the device includes a vehicle body.   The diagnostic system according to any one of claims 1 to 19, further comprising: a display unit that displays an analysis result by the deterioration analysis unit.   21. The diagnostic system according to claim 20, wherein the display unit is capable of switching between a graph showing the deterioration amount with respect to a date and a graph showing the deterioration amount with respect to the first information. Diagnostic system
A deterioration amount indicating the degree of deterioration of the device corresponding to each of the plurality of dates and times calculated based on measurement data obtained by measuring the state of the device mounted on the railway vehicle at each of the plurality of dates and times, and An acquisition step of acquiring operation information including route information indicating the route traveled,
Deterioration using the route information to obtain first information indicating a track record of the running state of the railway vehicle, and analyzing deterioration of the device using the first information and the deterioration amounts at the plurality of dates and times. Analysis step,
A diagnostic method comprising:

Images