Vehicle door device diagnostic system and vehicle door device diagnostic method

Abstract

To provide a vehicle door device diagnostic system capable of saving power in manual inspection work of a vehicle facility.SOLUTION: A vehicle door device diagnostic system 100 includes a storage unit, operation index generation units 30a, 30b, warning issuing units 40a, 40b, and an abnormality cause estimation unit 70. The storage unit stores management information indicating warning, which shows operation abnormality, a name of a portion which can be a source of the operation abnormality among portions constituting the vehicle door devices, and a failure mode of estimated failure for each operation abnormality of opening / closing operation of vehicle door devices 20a, 20b. The operation index generation unit generates an operation index for smoothness of the opening / closing movement of the vehicle door devices for each opening / closing operation of the vehicle door devices. The warning issuing unit detects a sign of operation abnormality of the vehicle door devices based on the generated operation index and issues warning indicating the detected operation abnormality. The abnormality cause estimation unit identifies the name of a portion corresponding to the operation abnormality indicated by the issued warning and its failure mode from the management information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates generally to computer techniques for diagnosing the condition of vehicle door systems. [Background technology]

[0002] In the past, to ensure that rail transit systems such as railways and monorails operated smoothly, manual inspections were required on a regular basis. Furthermore, if an abnormality was detected in the vehicle equipment as a result of the inspections, manual maintenance such as repairs and maintenance was carried out after the fact. However, both such periodic inspections and after-the-fact maintenance work lacked efficiency and placed a heavy burden on workers.

[0003] Therefore, various technologies have been proposed today that apply Internet of Things (IoT) technology to rail transit vehicle equipment, detecting signs of abnormalities in the vehicle based on data acquired from devices such as sensors, switches, cameras, and microphones installed in various parts of the vehicle, thereby automatically diagnosing the condition of the vehicle equipment (for example, Patent Document 1). By utilizing such technology, it becomes possible to realize so-called Condition Based Maintenance (CBM), replacing the above-mentioned maintenance style of vehicle equipment, in which maintenance work is performed after an abnormality has occurred. Furthermore, it is expected that the inspection of vehicle equipment will also reduce the labor required for manual inspection work and the frequency of inspections. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-162032 Summary of the Invention [Problem to be solved by the invention]

[0005] The diagnostic technology described in Patent Document 1 cannot identify the cause of an abnormality whose sign has been detected, i.e., the part that caused the abnormality or the specific details of the failure or malfunction in that part. Therefore, when the diagnostic technology described in Patent Document 1 is used for the purpose of improving the efficiency of inspection and maintenance of vehicle equipment, after a sign of an abnormality is detected, manual inspection work must be performed to identify the cause of the abnormality whose sign has been detected, which poses a problem in that it is difficult to sufficiently reduce the labor required for manual inspection work or the frequency of inspections. [Means for solving the problem]

[0006] The vehicle door device diagnostic system includes a memory unit, an operation indicator generation unit, a warning issuance unit, and an abnormality cause estimation unit. The memory unit stores, for each operation abnormality, which is a type of abnormality in the opening and closing operation of the vehicle door device, a warning indicating the operation abnormality, the names of one or more parts among multiple parts constituting the vehicle door device that may be the source of the operation abnormality, and a failure mode, which is a type of failure expected for each of the one or more parts. The operation indicator generation unit generates, for each opening and closing operation of the vehicle door device, a performance indicator that is an evaluation index of the smoothness of the opening and closing operation of the vehicle door device. The warning issuance unit detects a sign of the operation abnormality of the vehicle door device based on the generated operation indicator, and, if a sign of the operation abnormality is detected, issues a warning indicating the operation abnormality for which a sign has been detected. The abnormality cause estimation unit performs an abnormality cause estimation process that includes identifying the name and failure mode of the part corresponding to the operational abnormality indicated by the issued warning from the management information, and acquiring all of the identified names and failure modes as the estimated causes of the operational abnormality whose precursors have been detected. [Effects of the Invention]

[0007] According to the present invention, manual inspection work for inspecting vehicle equipment can be reduced, and inspection frequency can be reduced. [Brief explanation of the drawings]

[0008] [Figure 1] 1 shows an example of the configuration of a vehicle door device diagnostic system. [Figure 2] 1 shows an example of the configuration of a door controller. [Figure 3] 1 shows an example of the configuration of a vehicle door device. [Figure 4] 10 shows an example of the configuration of an action indicator generation unit. [Figure 5] 10 shows an example of the configuration of a warning issuing unit. [Figure 6] 10 shows an example of the configuration of a warning history storage unit. [Figure 7] 1 shows an example of the configuration of an abnormality cause estimation unit. [Figure 8] 10 shows another example of the configuration of the abnormality cause database. [Figure 9] 10 shows another example of the configuration of the abnormality cause estimation unit. [Figure 10] 10 shows another example of the configuration of the failure probability database. [Figure 11] 10 shows another example of the configuration of a vehicle door device diagnostic system. [Figure 12] 10 shows another example of the configuration of a vehicle door device diagnostic system. DETAILED DESCRIPTION OF THE INVENTION

[0009] In the following description, an "interface apparatus" may refer to one or more interface devices, which may be at least one of the following: One or more I / O (Input / Output) interface devices. The I / O (Input / Output) interface devices are interface devices for at least one of the I / O device and a remote display computer. The I / O interface device for the display computer may be a communications interface device. The at least one I / O device may be a user interface device, for example, either an input device such as a keyboard and a pointing device, or an output device such as a display device. One or more communication interface devices. The one or more communication interface devices may be one or more homogeneous communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more heterogeneous communication interface devices (e.g., an NIC and an HBA (Host Bus Adapter)).

[0010] In the following description, "memory" refers to one or more memory devices, which are an example of one or more storage devices, and may typically be a primary storage device. At least one memory device in the memory may be a volatile memory device or a non-volatile memory device.

[0011] In the following description, a "persistent storage device" may refer to one or more persistent storage devices, which are an example of one or more storage devices. A persistent storage device may typically be a non-volatile storage device (e.g., an auxiliary storage device), and specifically may be, for example, a hard disk drive (HDD), a solid state drive (SSD), a non-volatile memory express (NVME) drive, or a storage class memory (SCM).

[0012] In the following description, the term "storage device" may refer to at least one of memory and persistent storage device.

[0013] Furthermore, in the following description, a "processor" may refer to one or more processor devices. The at least one processor device may typically be a microprocessor device such as a CPU (Central Processing Unit), but may also be another type of processor device such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may also be a processor core. The at least one processor device may also be a processor device in a broader sense, such as a circuit that is a collection of gate arrays written in a hardware description language that performs some or all of the processing (for example, an FPGA (Field-Programmable Gate Array), a CPLD (Complex Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit)).

[0014] In the following description, functions may be described using the expression "yyy unit." However, the functions may be realized by one or more computer programs executed by a processor, by one or more hardware circuits (e.g., FPGAs or ASICs), or by a combination thereof. When a function is realized by a program executed by a processor, the specified processing is performed using a storage device and / or an interface device, as appropriate, and therefore the function may be considered to be at least a part of the processor. Processing described using a function as the subject may be processing performed by a processor or a device having the processor. A program may be installed from a program source. The program source may be, for example, a computer from which the program is distributed or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0015] In the following description, a process may be described using a "program" as the subject, but the process described using a program as the subject may also be a process performed by a processor or a device having that processor. Two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0016] In the following description, information that provides an output for an input may be described using expressions such as "xxx table," but this information may be a table of any structure, or may be a neural network that generates an output for an input, or a learning model such as a genetic algorithm or random forest. Therefore, the "xxx table" may be referred to as "xxx information." In the following description, the structure of each table is an example, and one table may be divided into two or more tables, or all or part of two or more tables may be one table.

[0017] In the following description, the "vehicle door device diagnostic system" may be a system configured with one or more physical computers, or may be a system (e.g., a cloud computing system) implemented on a group of physical computing resources (e.g., a cloud platform). When the vehicle door device diagnostic system "displays" display information, it may mean displaying the display information on a display device possessed by the computer, or it may mean that the computer transmits the display information to a display computer (in the latter case, the display information is displayed by the display computer).

[0018] FIG. 1 shows an example of the configuration of a vehicle door device diagnostic system.

[0019] Note that each block described below does not represent a hardware configuration, but represents a functional block.

[0020] In this embodiment, the vehicle door device diagnostic system 100 is realized by an on-board device mounted on a rail transit vehicle such as a railway, monorail, LRT (Light Rail Transit), or BRT (Bus Rapid Transit), and diagnoses the state of the opening and closing operation of a plurality of vehicle door devices 20a, 20b,..., 20n (hereinafter, when collectively referred to or when no particular distinction is made, they will be collectively referred to as "vehicle door devices 20" or simply referred to as "door devices 20") provided on the longitudinal sides of each vehicle for the primary purpose of passenger boarding and alighting, and a door controller 10 for controlling the opening and closing operation of the door devices 20, based on signals output from the door devices 20. The on-board device may be mounted on each vehicle, or may be mounted on each train consisting of multiple vehicles.

[0021] Here, the door controller 10 outputs an opening / closing command signal 101 to each of the door devices (20a, 20b), which includes an opening command signal for commanding an opening operation and a closing command signal for commanding a closing operation. Each of the vehicle door devices (20a, 20b) starts the door opening operation when it receives the opening command signal from the door controller 10, and starts the door closing operation when it receives the closing operation signal from the door controller 10.

[0022] On the other hand, each door device (20a, 20b) is provided with a detection mechanism (described in detail later) for detecting the open / closed state of the door. Therefore, each door device (20a, 20b) outputs an open detection signal (201a, 201b) when it detects that the door is fully open, and outputs a close detection signal (202a, 202b) when the door is fully closed.

[0023] The vehicle door device diagnostic system 100 generally includes a storage unit (not shown), an operation indicator generating unit 30, a warning issuing unit 40, and an abnormality cause estimating unit .

[0024] The memory unit is realized by a storage device (not shown) and stores, for each operational abnormality, which is a type of abnormality in the opening / closing operation of the door devices (20a, 20b), a warning indicating the operational abnormality, the names of multiple components constituting the door devices (20a, 20b), such as cylinders, solenoid valves, and pulleys, and management information indicating failure modes, which are types of failures expected for each of the multiple components. The management information may further include failure probabilities, which are the occurrence probabilities for each failure mode. The memory unit stores this information, for example, as an abnormality cause database 7002 and / or a failure probability database 9002, which will be described later.

[0025] The storage unit also includes a warning history storage unit 50 (described in detail below).

[0026] The operation indicator generating unit (30a, 30b) receives the opening / closing command signal 101 issued by the door controller 10, and the opening detection signals (201a, 201b) and the closing detection signals (202a, 202b) issued by the door devices (20a, 20b), and generates operation indicators (301a, 301b), which are evaluation indicators of the smoothness of the opening and closing operations of the door devices (20a, 20b), for each of the opening and closing operations of the vehicle door devices (20a, 20b) based on these signals.

[0027] The warning issuing units (40a, 40b) detect signs of abnormal operation of the door devices 20 (20a, 20b) based on the generated operation indicators (301a, 301b). Specifically, the warning issuing units (40a, 40b) compare each of the operation indicators 301 (301a, 301b) generated by each operation indicator generating unit (30a, 30b) with a reference value, and determine whether or not the indicators indicate normal values.

[0028] When the operation indicator (301a, 301b) generated for one of the opening and closing operations of the door device (20a, 20b) is not within a normal range, the warning issuing unit (40a, 40b) detects a sign of an abnormal operation of the door device (20a, 20b).

[0029] When detecting a sign of an operational abnormality in each of the door devices 20 (20a, 20b), the warning issuing units (40a, 40b) issue a warning (401a, 401b) indicating the operational abnormality for which the sign has been detected.

[0030] The anomaly cause estimation unit 70 executes a process of identifying the name and failure mode of the part corresponding to the operational abnormality indicated by the issued warning from the management information, and a process of acquiring all of the identified names and failure modes as the estimated causes of the operational abnormality whose sign has been detected. These processes executed by the anomaly cause estimation unit 70 are referred to as an anomaly cause estimation process (described in detail later).

[0031] That is, by being provided with the above-described configuration, the vehicle door device diagnostic system 100 can detect signs of operational abnormalities along with the type of abnormality for each of the door devices 20 (20a, 20b). This makes it possible to realize so-called condition-based maintenance, in which, instead of performing maintenance work after an abnormality has occurred in a door device 20, a door device 20 in which a sign of an operational abnormality has been detected is manually inspected in detail for only the type of abnormality for which the sign has been detected, and maintenance work is performed appropriately as necessary. As a result, it is possible to reduce the labor required for manual inspection work and the frequency of inspections.

[0032] The anomaly cause estimation unit 70 also executes a process of calculating an evaluation value called a posterior probability, which is a relative evaluation of the failure probability for all assumed failure modes. This process executed by the anomaly cause estimation unit 70 is referred to as a posterior probability calculation process (described in detail later).

[0033] Furthermore, the vehicle door device diagnostic system 100 includes a warning history storage unit 50 and a disturbance removal unit 60.

[0034] The warning history storage unit 50 particularly stores the history of warnings (401a, 401b) issued by the warning issuing units (40a, 40b) for each opening and closing operation of each of the door devices 20 (20a, 20b). The warning history storage unit 50 is included in the storage unit.

[0035] Furthermore, the disturbance removal unit 60 performs processing to remove elements that become disturbances to the abnormality cause estimation processing prior to the execution of the abnormality cause estimation processing by the abnormality cause estimation unit 70. This allows the vehicle door device diagnostic system 100 to accurately execute the abnormality cause estimation processing by the abnormality cause estimation unit 70. Note that an example of an element that becomes a disturbance when the abnormality cause estimation processing is executed is an increase in sliding resistance during the opening and closing operation of the door device 20 caused by a passenger leaning against the door device 20.

[0036] FIG. 2 shows an example of the configuration of the door controller 10.

[0037] The door controller 10 of this embodiment is generally a self-holding circuit realized by two mechanical contacts (2001, 2002) and a relay 2003. The door controller 10 outputs an open / close command signal 101 indicating the presence or absence of a voltage applied to the circuit, which changes depending on the operation result of the two mechanical contacts (2001, 2002).

[0038] When door-open switch 2001, which is a contact for self-holding, is input while door-close switch 2002, which is a contact for releasing self-holding, is in a released state, the self-holding circuit is energized, and relay 2003 is excited, thereby maintaining the energized state of the circuit. In this state, when door-close switch 2002 is further energized, relay 2003 is deenergized, and the self-holding circuit that had maintained the energized state is opened.

[0039] As a result, the door controller 10 outputs an opening / closing command signal 101, which indicates an open command when the self-holding circuit is energized and a close command when the self-holding circuit is not energized, depending on the operation states of the door open switch 2001 and the door close switch 2002. The issuance of an open command is initiated by the rising edge of the opening / closing command signal 101 due to the application of the self-holding circuit. The issuance of a close command is initiated by the falling edge of the opening / closing command signal 101 due to the release of the self-holding circuit. In other words, the door open switch 2001 is input to the door device 20. Open The door close switch 2002 prompts the door device 20 to start the closing operation by inputting an input.

[0040] FIG. 3 shows an example of the hardware configuration of the door device 20.

[0041] The door device 20 of this embodiment is a sliding pneumatic door device provided on the side of each vehicle, and generally includes as its components two vehicle side doors (hereinafter simply referred to as "doors") 3001 that open and close in the left-right direction along rails 3002, the rails 3002 that regulate the movement of the doors 3001, and a drive mechanism consisting of a belt 3003, a pulley 3004, a rod 3005, a cylinder 3006, an electromagnetic valve 3007, and an air reservoir 3008.

[0042] The door device 20 opens and closes the door 3001 by operating the drive mechanism in response to the opening / closing command signal 101 issued by the door controller 10.

[0043] Cylinder 3006, a component of the drive mechanism, has two sealed spaces inside it that are separated by a movable partition (not shown). This partition changes its position in the axial direction of cylinder 3006 depending on which sealed space in cylinder 3006 the compressed air discharged from air reservoir 3008 flows into. The flow path for compressed air from air reservoir 3008 into cylinder 3006 is a three-way branch, and at the branching point is located solenoid valve 3007 for determining which of the two sealed spaces the compressed air will flow into.

[0044] One end of a rod 3005 is connected to approximately the center of the side end face of the partition wall, and is arranged along the cylindrical axis of the cylinder 3006 in order to transmit kinetic energy generated by changes in its position to the belt 3003. The other end of the rod 3005 is connected to a part of a circular belt 3003 stretched between two pulleys 3004 arranged so that their rotation axes are parallel.

[0045] In the door device 20, when the solenoid valve 3007 switches the flow path of compressed air in response to the opening / closing command signal 101 issued by the door controller 10, the kinetic energy generated by the change in the position of the partition part of the cylinder 3006 in the cylindrical axial direction is transmitted to the door 3001 via the rod 3005 and the belt 3003, and the door 3001 moves along the rail 3002 via the door roller 3009, thereby opening and closing the door.

[0046] In addition, the door device 20 is provided with the aforementioned detection mechanism for detecting the open / closed state of the door 3001, which is provided at predetermined positions with an open detection switch 3010 that detects the fully open state of the door 3001 when pressed down by the tip of the abutting rod 3005, and a closed detection switch 3011 that detects the fully closed state of the door 3001 when pressed down by the tip of the abutting rod 3005.

[0047] When the open detection switch 3010 detects that the door 3001 is in a fully open state, i.e., that the opening operation of the door device 20 has been completed, it outputs an open detection signal 201 that indicates the completion of the opening operation of the door device 20. When the close detection switch 3011 detects that the door 3001 is in a fully closed state, i.e., that the closing operation of the door device 20 has been completed, it outputs a close detection signal 202 that indicates the completion of the closing operation of the door device 20.

[0048] In this embodiment, the door device 20 has been described as a sliding door device that swings left and right and has two doors 3001, but the number of doors, the opening and closing direction, the drive system, etc. may be changed as appropriate. For example, the door device may be a single-wing door device that has one door 3001. The door device may also be a so-called folding door device in which the door folds inward toward the vehicle when fully open. Furthermore, the door device may not be a pneumatic door device that drives the door by injecting compressed air into a cylinder, but may be an electric door device that drives the door by rotating a motor.

[0049] FIG. 4 shows an example of the action indicator generating unit.

[0050] The action indicator generating unit 30 sequentially executes the following processes based on the opening / closing command signal 101 received from the door controller 10, the opening detection signal 201 received from the opening detection switch 3010, and the closing detection signal 202 received from the closing detection switch 3011, to generate an action indicator that is an evaluation index for the smoothness of the opening / closing action of the door device 20. This process is referred to as action indicator generating process.

[0051] When the action indicator generating unit 30 detects a rising edge of the open / close command signal 101 issued by the door controller 10, it first performs a rising edge detection process 4001a to output the most recent rising edge detection time, and obtains an open command time 4003 indicating the time when the open command was issued.

[0052] On the other hand, when the action indicator generating unit 30 detects a falling edge of the open / close command signal 101 issued by the door controller 10, it performs a falling edge detection process 4002a to output the most recent falling edge detection time, and obtains a close command time 4004 that indicates the time when the close command was issued.

[0053] Furthermore, the action indicator generation unit 30 performs a rising detection process 4001b and a falling detection process 4002b on the open detection signal 201 received from the open detection switch 3010. As a result of the rising detection process 4001b, an opening operation completion time 4005 indicating the completion time of the opening operation of the door device 20 is acquired. Furthermore, as a result of the falling detection process 4002b, a closing operation start time 4006 indicating the start of the closing operation of the door device 20 is acquired.

[0054] Similarly, the action indicator generation unit 30 also performs rising detection processing 4001c and falling detection processing 4002c on the close detection signal 202 received from the close detection switch 3011. As a result of the rising detection processing 4001c, a closing operation completion time 4007 indicating the completion of the closing operation of the door device 20 is acquired. Furthermore, as a result of the falling detection processing 4002c, an opening operation start time 4008 indicating the start time of the opening operation of the door device 20 is acquired.

[0055] Next, the action indicator generating unit 30 obtains the difference between the opening operation start time 4008 and the opening operation completion time 4005, and calculates the opening operation time 4009 that indicates the time required for the door device 20 to complete the opening operation from the start to the completion.

[0056] Furthermore, the action indicator generating unit 30 obtains the difference between the close command time 4004 and the closing operation start time 4006, and calculates the closing operation dead time 4010 that indicates the lost time occurring from the start to the completion of the closing operation of the door device 20.

[0057] Furthermore, the action indicator generating unit 30 obtains the difference between the closing operation start time 4006 and the closing operation completion time 4007, and calculates the closing operation time 4011 that indicates the time required for the door device 20 to complete the closing operation from the start to the completion.

[0058] Similarly, the action indicator generating unit 30 obtains the difference between the opening command time 4003 and the opening operation start time 4008, and calculates the opening operation dead time 4012 that indicates the lost time occurring from the start to the completion of the opening operation of the door device 20.

[0059] Thereafter, the action indicator generation unit 30 performs a multiplexing process on the calculated opening operation time 4009, closing operation dead time 4010, closing operation time 4011, and opening operation dead time 4012 using the multiplexer 4013, and outputs the result as the action indicator 301.

[0060] The door device 20 may include a door cock (not shown) that is a mechanism for manually opening and closing the door 3001. In this case, the action indicator generating unit 30 may execute the action indicator generating process using a signal received from the door cock.

[0061] That is, the action indicator generation unit 30 generates the action indicator 301 based on signals received from at least one of the door open switch that issues an open command to prompt the door device 20 to start a closing operation, the door close switch that issues a close command to prompt the door device 20 to start a closing operation, the open detection switch that detects the completion of the opening operation of the door device 20, the close detection switch that detects the completion of the closing operation of the door device 20, and the door cock that is a mechanism for manually opening and closing the door device 20. This makes it possible to accurately detect both the start and completion of the opening operation and the start and completion of the closing operation of the door device 20. As a result, it is possible to reliably detect any signs of abnormality in the opening and closing operation of the door device 20 without overlooking them, thereby saving on manual inspection work and reducing the frequency of inspections.

[0062] Furthermore, the operation indicator 301 generated by the operation indicator generation process includes one of the following: an opening operation time representing the time required for the door device 20 to complete an opening operation; a closing operation time representing the time required for the door device 20 to complete a closing operation; an opening operation wasted time representing the lost time occurring from the start of the opening operation of the door device 20 to the completion; and a closing operation wasted time representing the lost time occurring from the start of the closing operation of the door device 20 to the completion. The opening operation time and the closing operation time can be accurately calculated using the above-described method without the need for additional sensors. Furthermore, the opening operation wasted time and the closing operation wasted time can also be accurately calculated using the above-described method. If these wasted times occur during the opening and closing operations of the door device 20, there is a high possibility that a malfunction has occurred in one of the components of the door device 20. Therefore, by using these operation indicators to evaluate the smoothness of the opening and closing operations of the door device 20, any signs of abnormalities in the opening and closing operations of the door device 20 can be reliably detected without overlooking them, thereby reducing the amount of manual inspection work and the frequency of inspections.

[0063] FIG. 5 shows an example of the warning issuing unit.

[0064] The warning issuing unit 40 receives the action indicators 301 from the action indicator generating unit 30, sequentially executes the following processes, and generates a warning 401 according to the results of the processes. When the warning issuing unit 40 generates a warning 401, it issues the warning 401. This process is called warning issuing processing.

[0065] The warning issuing unit 40 first performs a decoding process on the multiplexed action indicators 301 using the decoding device 5001, and obtains the indices of the opening operation time 4009, the closing operation wasted time 4010, the closing operation time 4011, and the opening operation wasted time 4012 included in the action indicators 301.

[0066] Next, the warning issuing unit 40 inputs the acquired indicators of the opening operation time 4009, the closing operation wasted time 4010, the closing operation time 4011 and the opening operation wasted time 4012 into the determiners (5002a to 5002d), respectively, and determines whether or not each of these indicators (4009 to 4012) is a normal value relative to a predefined threshold value 5003.

[0067] Each of these indicators (4009 to 4012) is determined to be a normal value when it is less than the threshold value 5003. In this case, it is estimated that the operation of the door device 20 is normal (G).

[0068] On the other hand, each of these indicators (4009 to 4012) is determined to be an abnormal value when it is equal to or greater than the threshold value 5003. In this case, it is presumed that a sign of abnormality (Y) has appeared as an abnormal value in the operation of the door device 20.

[0069] Therefore, when the input opening operation time 4009 is an abnormal value, the determiner 5002a generates an opening operation delay warning 5004.

[0070] If the input closing operation dead time 4010 is an abnormal value, the determiner 5002b generates a closing dead time warning 5005.

[0071] The determiner 5002c generates a closing operation delay warning 5006 when the input closing operation time 4011 is an abnormal value.

[0072] If the inputted opening operation dead time 4012 is an abnormal value, the determiner 5002d generates an opening dead time warning 5007.

[0073] Thereafter, the warning issuing unit 40 performs multiplexing processing using the multiplexing device 5008 on the opening operation delay warning 5004, closing wasted time warning 5005, closing operation delay warning 5006 and opening wasted time warning 5007 output by the determiner 5002, and issues it as a single warning 401.

[0074] In this embodiment, the determiners (5002a to 5002d) use one corresponding threshold value 5003 for each of the indicators of the opening operation time 4009, the closing operation wasted time 4010, the closing operation time 4011, and the opening operation wasted time 4012 to determine whether each of the indicators (4009 to 4012) is a normal value. However, the number of threshold values ​​used by the determiners and specific numerical values ​​may be changed as appropriate. For example, the warning issuing unit 40 may determine each of the indicators (4009 to 4012) using two different threshold values, thereby estimating that the opening and closing operation of the door device 20 is actually abnormal in addition to being normal (G) or showing a sign of abnormality (Y).

[0075] In addition, in this embodiment, the warning issuing unit 40 generates and issues the warning 401 every time the door device 20 performs an opening or closing operation, but the trigger and timing for issuing the warning 401 may be changed as appropriate. For example, the warning issuing unit 40 may issue the warning 401 when the details of the warning 401 change, that is, when the value of any of the opening operation delay warning 5004, the closing wasted time warning 5005, the closing operation delay warning 5006, and the opening wasted time warning 5007 included in the warning 401 is updated.

[0076] Furthermore, in the present embodiment, the action indicator generation unit 30 and the warning issuance unit 40 are each provided with a multiplexing device (4013, 5008), and the action indicator 301 generated by the action indicator generation unit 30 and the warning 401 issued by the warning issuance unit 40 have both been subjected to multiplexing processing. However, it goes without saying that the opening operation time 4009, the closing operation wasted time 4010, the closing operation time 4011, and the opening operation wasted time 4012, which are components of the action indicator 301, and the opening operation delay warning 5004, the closing wasted time warning 5005, the closing operation delay warning 5006, and the opening wasted time warning 5007, which are components of the warning 401, may be output individually without being subjected to multiplexing processing.

[0077] The vehicle door device diagnostic system 100 of this embodiment also includes a warning history storage unit 50 that receives the warning 401 issued by the warning issuing unit 40 each time and stores the issuance history of the warning 401.

[0078] FIG. 6 shows an example of the structure of the warning history table stored in the warning history storage unit 50. As shown in FIG.

[0079] The warning history table 600 is a table for managing the content of each warning 401 issued by the warning issuing unit 40. The warning history table 600 has a record for each warning. The record indicates the date and time when the warning 401 was issued, and whether or not the warning 401 includes an opening operation delay warning 5004, a closing dead time warning 5005, a closing operation delay warning 5006, and an opening dead time warning 5007.

[0080] For example, if any of the values ​​of the opening operation time 4009 corresponding to the opening operation delay warning 5004, the closing operation dead time 4010 corresponding to the closing operation dead time warning 5005, the closing operation time 4011 corresponding to the closing operation delay warning 5006, and the opening operation dead time 4012 corresponding to the opening operation dead time warning 5007 is a normal value, then the warning 401 issued by the warning issuing unit 40 will not generate or include any warnings among the opening operation delay warning 5004, the closing dead time warning 5005, the closing operation delay warning 5006, and the opening dead time warning 5007 whose corresponding indicators indicate normal values. In this case, for any of the opening operation delay warning 5004, the closing dead time warning 5005, the closing operation delay warning 5006, and the opening dead time warning 5007 that were not included in the warning 401, a letter "G," which means normal, is recorded in the corresponding field of the warning history table 600.

[0081] On the other hand, for those of the opening operation delay warning 5004, closing dead time warning 5005, closing operation delay warning 5006, and opening dead time warning 5007 that were included in warning 401, a "Y" is recorded in the corresponding field of the warning history table 600, which means that the corresponding indicator shows signs of an operational abnormality.

[0082] 6 , the warning history table 600 records, for each record, the issuance date and time of the warning 401 and the values ​​of the various components of the warning 401 in association with each other, thereby roughly representing the content of each warning. According to the example shown in FIG. 6 , the warning history table 600 records that, for a warning issued at "February 2, 2020, 10:00:01," the value of the opening operation time 4009 corresponding to the opening operation delay warning 5004 was an abnormal value (Y), and that the values ​​of the closing operation dead time 4010 corresponding to the closing operation delay warning 5005, the closing operation time 4011 corresponding to the closing operation delay warning 5006, and the opening operation dead time 4012 corresponding to the opening operation dead time warning 5007 were all normal values ​​(G). This means that the warning 401 includes the opening operation delay warning 5004, but does not include the closing operation dead time warning 5005, the closing operation delay warning 5006, or the opening dead time warning 5007.

[0083] In the present embodiment, the warning history storage unit 50 has been described as storing the issuance history of the warning 401 each time, but the manner in which the issuance history of the warning 401 is recorded may be changed as appropriate. For example, when the value of any one of the opening operation delay warning 5004, the closing dead time warning 5005, the closing operation delay warning 5006, and the opening dead time warning 5007 included in the warning 401 is updated, the warning history storage unit may record the history of the warning 401 together with the time.

[0084] The vehicle door device diagnostic system 100 of this embodiment is provided with the warning history storage unit 50, and is thereby able to store a history of the warnings 401. Therefore, in addition to sequentially analyzing the warnings 401 issued by the warning issuing unit 40, the vehicle door device diagnostic system 100 can also store a history of multiple warnings 401 issued by the warning issuing unit 40 and analyze them collectively later.

[0085] As a result, the vehicle door device diagnostic system 100 of this embodiment can minimize the influence of external disturbances when analyzing the warnings 401, for example, by analyzing the history of all warnings 401 issued while a train is traveling through an entire operating section after the train has arrived at its terminal, or by analyzing the history of all warnings 401 for one day after the train has been sent out (details will be described later).

[0086] FIG. 7 shows an example of the abnormality cause estimation unit 70.

[0087] The abnormality cause estimation unit 70 refers to the warning history storage unit 50, and acquires a warning 601 from the warnings 401 stored in the warning history storage unit 50, in which any one of the values ​​of the opening operation time 4009 corresponding to the opening operation delay warning 5004, the closing operation wasted time 4010 corresponding to the closing wasted time warning 5005, the closing operation time 4011 corresponding to the closing operation delay warning 5006, and the opening operation wasted time 4012 corresponding to the opening wasted time warning 5007 has an abnormal value, and executes an abnormality cause estimation process 7001 to estimate the cause (hereinafter referred to as the "abnormal cause") 7003 that has caused the warning 601 to indicate a sign of an abnormality in the operation of the door device 20.

[0088] In the following description, the warning 601 acquired by the abnormality cause estimation unit 70 from the warning history storage unit 50 will be referred to as a cause estimation warning 601.

[0089] In the following explanation, the abnormality cause 7003 includes the following items. A component that is estimated to be the faulty part among the above-mentioned components of the door device 20 (hereinafter referred to as the "presumed faulty part"). -Failure mode of the suspected failure area.

[0090] The abnormality cause estimation unit 70 refers to an abnormality cause database 7002 stored in a storage unit (not shown), executes an abnormality cause estimation process 7001 for the cause estimation warning 601, and estimates an abnormality cause 7003. Thereafter, the abnormality cause estimation unit 70 causes the interface device 7004 to display the estimated abnormality cause 7003 as in a display example 7005 shown in FIG.

[0091] The anomaly cause database 7002 is a definition collection that predefines the correspondence between various combinations (hereinafter simply referred to as "alarm combinations") of the values ​​of the opening operation time 4009 corresponding to the opening operation delay warning 5004, the closing operation dead time 4010 corresponding to the closing dead time warning 5005, the closing operation time 4011 corresponding to the closing operation delay warning 5006, and the opening operation dead time 4012 corresponding to the opening dead time warning 5007, all of which are included in the cause estimation warning 601, and the failure location (hereinafter referred to as "presumed failure location") that is presumed for each combination of warnings based on the causal relationship between a failure and its effect in known analysis methods such as Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA), which are mainly used in the design of the door device 20. In this embodiment, the anomaly cause database 7002 is stored as a table 700 having a record for each combination of warnings. The record represents the combination of warnings and the presumed failure location for that combination of warnings. 7, the estimated faulty parts for the warning combination "A" in which the closing operation dead time 4010 corresponding to the closing dead time warning 5005 and the opening operation dead time 4012 corresponding to the opening dead time warning 5007 are abnormal values ​​are the belt 3003, the pulley 3004, and the cylinder 3006.

[0092] Furthermore, as shown in the display example 7005 of FIG. 7, when the cause estimation warning 601 has a warning combination of "A", the interface device 7004 displays that "belt 3003", "pulley 3004", and "cylinder 3006" are the estimated fault parts of the door device 20 corresponding to the cause estimation warning 601.

[0093] This makes it possible to efficiently and accurately extract a suspected faulty part from the many parts that make up the door device and display it on the interface device 7004. As a result, manual inspection work on the door device 20 can be performed efficiently and reliably, thereby saving labor and reducing the frequency of inspections.

[0094] In the present embodiment, the anomaly cause database 7002 has been described as being stored in the storage unit as the table 700. However, the storage mode (format) of the anomaly cause database 7002 in the storage unit may be changed as appropriate. For example, as shown in Fig. 8, the anomaly cause database 7002 may be stored in the storage unit as an anomaly cause graph 800 that represents, in a tree structure, the causal relationships between the failure location and failure mode and the warnings indicating operational anomalies.

[0095] 8 has a node for each attribute, "P" representing the fault location, "M" representing the failure mode, "E" representing the effect, and "A" representing the combination of warnings. The nodes are connected in advance by links representing the causal relationships between the attributes based on the analysis methods such as the FMEA and FTA described above.

[0096] In this case, when executing the anomaly cause estimation process 7001, the anomaly cause estimation unit 70 traces back the links representing the causal relationships between preset attributes, and searches from the node representing the warning combination A to the node representing the failure location P and the node representing the failure mode M, thereby being able to estimate the anomaly cause 7003.

[0097] In the present embodiment, the anomaly cause estimation unit 70 acquires the cause estimation warning 601 from the warning history storage unit 50 and executes the anomaly cause estimation process 7001. However, the route by which the warning is acquired may be changed as appropriate. For example, the anomaly cause estimation unit 70 may directly receive the warning 401 issued by the warning issuing unit 40 and execute the anomaly cause estimation process 7001.

[0098] In addition, when executing the abnormality cause estimation process 7001 for the cause estimation warning 601, the abnormality cause estimation unit 70 can also estimate the abnormality cause 7003 by referring to a failure probability database 9002 stored in a memory unit (not shown), as shown in FIG. 9.

[0099] The failure probability database 9002 is a collection of definitions that predefines the correspondence between a presumed failure part, a failure mode, and the probability of occurrence of the failure mode (hereinafter also referred to as "failure probability") for each type of warning combination. The failure probability is predefined based on analysis methods such as the above-mentioned FMEA and FTA. In this embodiment, the failure probability database 9002 is provided for each warning combination and is stored as a table 900 having a record for each presumed failure part. The record represents a presumed failure part, a failure mode corresponding to the presumed failure part, and the probability of occurrence of the failure mode. In other words, the failure probability database 9002 records, for each record, a presumed failure part, a failure mode corresponding to the presumed failure part, and a failure probability associated with the presumed failure part. 9, when the cause estimation warning 601 has a combination of warnings designated as "A," the estimated failure parts are the door open switch 2001, cylinder 3006, solenoid valve 3007, pulley 3004, belt 3003, open detection switch 3010, and close detection switch 3011. Of these, for example, two failure modes, "air leakage" and "sticking," are assumed for the "solenoid valve 3007," and the occurrence probabilities of these two failure modes are both the same, "0.00×10 -8 "

[0100] Furthermore, the anomaly cause estimation unit 70 executes a process to calculate an evaluation value called a posteriori probability, which relatively evaluates the failure probability for all failure modes assumed for the estimated failure part. The process executed by the anomaly cause estimation unit 70 is referred to as a posteriori probability calculation process. According to the example shown in FIG. 9, the occurrence probabilities of the two assumed failure modes in the above case where the estimated failure part is "solenoid valve 3007" are both "0.00×10 -8In this case, the posterior probability for evaluating the probability of occurrence of "air leakage" is 50%, and the posterior probability for evaluating the probability of occurrence of "sticking" is also 50%. In other words, the posterior probability can be found by calculating the ratio of the failure probability of a failure mode to the total failure probability of all failure modes that correspond to the estimated failure part in the failure probability database 9002.

[0101] Furthermore, the anomaly cause estimation unit 70 can, for example, calculate the posterior probability for all possible failure modes for each combination of warnings, and based on the level of the posterior probability, relatively evaluate the possibility that the estimated failure mode is actually the cause of the anomaly.

[0102] Therefore, as in the display example 9005 shown in FIG. 9, when the cause estimation warning 601 has a combination of warnings "A," the interface device 7004 displays the combinations of "deterioration" of "pulley 3004," "deterioration" of "belt 3003," and "air leak" of "cylinder 3006," as well as the presumed failure parts and failure modes that are presumed to be the cause of the abnormality, in descending order of posterior probability, i.e., in descending order of the likelihood that they are actually the cause of the abnormality.

[0103] As a result, when manual inspection is performed on a door device 20 in which signs of an abnormality have been detected in the opening and closing operation, the inspection can be performed efficiently by checking the combinations of suspected faulty parts and fault modes displayed on the interface device in the order in which they are displayed.

[0104] In the present embodiment, the failure probability database 9002 has been described as being stored in the storage unit as the table 900. However, the storage format of the failure probability database 9002 may be changed as appropriate. For example, the failure probability database 9002 may be stored in the storage unit as a failure probability graph 1000, which represents the causal relationship between failures and warnings in a tree structure, as shown in FIG.

[0105] The failure probability graph 1000 illustrated in FIG. 10 is a Bayesian network, and has nodes for each attribute: "P" representing a failure location, "M" representing a failure mode, "E" representing an effect, and "A" representing a combination of warnings. The nodes are connected in advance by links representing the causal relationships between the attributes based on the analysis methods such as the FMEA and FTA described above. Furthermore, each link connecting the node representing the failure location P with the node representing the failure mode M is assigned in advance the failure probability of the corresponding failure mode M as an evaluation value based on the FMEA or FTA described above. In other words, in the failure probability graph 1000, as illustrated in FIG. 10, the causal relationships between the attributes are defined in advance as a probability chain.

[0106] In the example of Figure 10, the link connecting the node representing failure mode M and the node representing effect E, and the link connecting the node representing effect E and the node representing warning combination A are each assigned an occurrence probability evaluation value of "1.00" representing 100%, but the occurrence probability evaluation value assigned in advance to these links in order to define the probabilistic dependency between nodes does not have to be "1.00" and can be changed as appropriate.

[0107] In this case, when executing the anomaly cause estimation process 7001, the anomaly cause estimation unit 70 traces back the links representing the causal relationships between preset attributes, and searches from the node representing the warning combination A to the node representing the failure location P and the node representing the failure mode M, thereby calculating the posterior probability and being able to estimate the anomaly cause 7003 in descending order of probability.

[0108] In the present embodiment, the anomaly cause estimation unit 70 has been described as executing the anomaly cause estimation process 7001 based on information stored in the anomaly cause database 7002 or information stored in the failure probability database 9002. However, the database that the anomaly cause estimation unit 70 refers to when executing the anomaly cause estimation process 7001 does not have to be either the anomaly cause database 7002 or the failure probability database 9002. For example, the anomaly cause estimation unit 70 may execute the anomaly cause estimation process 7001 based on information stored in the anomaly cause database 7002 and information stored in the failure probability database 9002.

[0109] In this way, the anomaly cause estimation unit 70 executes the anomaly cause estimation process 7001 based on the information stored in the anomaly cause database 7002 and / or the information stored in the failure probability database 9002. The information stored in the anomaly cause database 7002 and the information stored in the failure probability database 9002, i.e., the information such as the combination of warnings, the estimated failure location, the failure mode, and the failure probability, is, as described above, information that is defined in advance based on analysis methods such as FMEA and FTA that are used mainly in the design stage of the door device 20. If this information is collected after the door device 20 has started operating and the anomaly cause database 7002 and the failure probability database 9002 are constructed, it would take a long time to construct a database that can accurately execute the anomaly cause estimation process 7001, even if actual measurement data obtained from a plurality of door devices 20 is accumulated. However, the abnormality cause database 7002 and / or the failure probability database 9002, which are referred to by the abnormality cause estimation unit 70 when executing the abnormality cause estimation process 7001, are implemented as databases in which a stochastic process model is constructed based on known analysis methods such as FMEA and FTA that were actually used in the design stage of the door device 20, in other words, before the door device 20 started to be put into operation. Therefore, the vehicle door device diagnostic system 100 of this embodiment can accurately execute the abnormality cause estimation process 7001 immediately after the door device 20 starts to be put into operation.

[0110] Furthermore, known analytical methods such as FMEA and FTA used in constructing the anomaly cause database 7002 and the failure probability database 9002 of this embodiment are based on extensive past knowledge regarding the design, manufacture, and operation of various door devices. Therefore, the anomaly cause database 7002 and the failure probability database 9002 comprehensively cover all failure locations and failure modes that could be assumed when the door device 20 was designed. Furthermore, the predicted values ​​of failure probabilities for each failure mode defined in the failure probability database 9002 are based on a vast amount of data and are extremely accurate. Therefore, the vehicle door device diagnostic system 100 of this embodiment can accurately estimate failure locations and failure modes without omission as a result of the anomaly cause estimation process 7001. As a result, manual inspection work can be reduced, and inspection frequency can be reduced.

[0111] As described above, the vehicle door device diagnostic system 100 of this embodiment includes the warning history storage unit 50. Therefore, the abnormality cause estimation unit 70 can acquire multiple warnings stored in the warning history storage unit 50 after the fact, all at once, and execute the abnormality cause estimation process 7001 all at once.

[0112] As described above, the vehicle door device diagnostic system 100 of this embodiment includes the disturbance elimination unit 60 that, prior to the execution of the abnormality cause estimation process 7001 by the abnormality cause estimation unit 70, executes a process to eliminate elements that become disturbances to the abnormality cause estimation process 7001. This process executed by the disturbance elimination unit 60 is referred to as the disturbance elimination process.

[0113] In this case, the disturbance removal unit 60 executes the disturbance removal process by acquiring the warning history from the warning history storage unit 50. The abnormality cause estimation unit 70 acquires the warning from which the disturbance has been removed by the disturbance removal process from the disturbance removal unit 60, and executes the abnormality cause estimation process 7001.

[0114] As a result, the vehicle door device diagnostic system 100 of this embodiment can minimize the influence of disturbances when executing the abnormality cause estimation process 7001, and can therefore execute the abnormality cause estimation process 7001 with high accuracy.

[0115] As described above, an example of a factor that may become a disturbance when the abnormality cause estimation process is performed is an increase in sliding resistance during the opening and closing operation of the door device 20, which is caused by a passenger leaning on the door device 20. Therefore, the disturbance removal process may be, for example, a process in which the disturbance removal unit 60 selects only the warnings with the shortest opening operation time and closing operation time in the corresponding operation indicator from the warning history acquired from the warning history storage unit 50, that is, the warnings with the smallest influence of a passenger leaning on the door device 20. Furthermore, the disturbance removal process may be, for example, a process in which the disturbance removal unit 60 removes warnings with opening operation time and closing operation time longer than a predetermined time.

[0116] As a result, the vehicle door device diagnostic system 100 of this embodiment can minimize the influence of disturbances caused by passengers leaning against the door device 20, and can therefore accurately execute the abnormality cause estimation process 7001.

[0117] In addition, the disturbance removal process may be a process in which the history of warnings for a predetermined period is obtained from the warning history storage unit 50, and for each warning, the disturbance removal unit 60 selects a representative value by statistical processing such as majority voting and outputs the cause estimation warning 601.

[0118] The disturbance elimination unit 60 may also acquire various information from outside the vehicle door device diagnostic system 100 and perform the disturbance elimination process.

[0119] Fig. 11 shows an example of the configuration of a vehicle door device diagnostic system 1100 when the disturbance elimination unit 60 acquires various information from outside the system. In the vehicle door device diagnostic system 1100 illustrated in Fig. 11, the disturbance elimination unit 60 acquires operation status record information 1101, which is a record of the train operation status, from a vehicle information control device 110, which is a vehicle information control device installed outside the system 1100, and performs disturbance elimination processing.

[0120] The operation status record information 1101 may be, for example, information indicating the occupancy rate of a vehicle between stations. In this case, the disturbance removal process may be a process in which the disturbance removal unit 60 removes, from the warning history acquired from the warning history storage unit 50, warnings issued between stations where the vehicle's occupancy rate exceeds a predetermined value.

[0121] As a result, the vehicle door device diagnostic system 1100 can minimize the influence of disturbances caused by passengers leaning against the door device 20, and can therefore accurately execute the abnormality cause estimation process 7001.

[0122] Furthermore, the operation status record information 1101 may be, for example, door entrapment detection information indicating that a passenger is entrapped in the door device 20. In this case, the disturbance removal process may be a process in which the disturbance removal unit 60 removes, from the warning history obtained from the warning history storage unit 50, a warning that corresponds to the opening / closing operation for which door entrapment detection information is obtained from the vehicle information control device 110. As a result, the vehicle door device diagnostic system 1100 can remove a warning that is erroneously issued when a passenger is entrapped in the door device 20 and eliminate the influence of a disturbance caused by a passenger being entrapped in the door device 20, thereby enabling the abnormality cause estimation process 7001 to be executed with high accuracy.

[0123] In the present embodiment, the vehicle door device diagnostic system 100 has been described as having the warning history storage unit 50 store a history of multiple warnings. However, the specific processing flow of various signals prior to the execution of the abnormality cause estimation process 7001 can be changed as appropriate. For example, the vehicle door device diagnostic system 1200 illustrated in FIG. 12 does not include the warning history storage unit 50, but instead includes an action indicator history storage unit 1250 that stores a history of action indicators 1201. In this case, the warning issuing unit 1240 acquires multiple action indicators 1201 collectively from the action indicator history storage unit 1250 and issues a warning 401.

[0124] As a result, for example, the warning issuing unit 1240 can use the statistical value of the history of the operation indicators 1201 of the plurality of door devices 20 stored in the operation indicator history storage unit 1250 as the threshold value 5003 used by the determiner 5002. As a result, the warning issuing unit 1240 can assign the threshold value 5003 by learning during the operation of the train, without having to define it in advance.

[0125] Although one embodiment has been described above, this is merely an example for explaining the present invention, and the scope of the present invention is not limited to this embodiment. The present invention can be implemented in various other forms. [Explanation of symbols]

[0126] 100, 1100, 1200: Vehicle door device diagnostic system

Claims

1. a storage unit that stores management information indicating, for each operational abnormality that is a type of abnormality in the opening / closing operation of the vehicle door device, a warning indicating the operational abnormality, the names of one or more parts that may be the source of the operational abnormality among a plurality of parts constituting the vehicle door device, and failure modes that are types of failures that are expected for each of the one or more parts; an action indicator generating unit that generates an action indicator, which is an evaluation index of smoothness of an opening / closing action of a vehicle door device, for each of opening and closing actions of the vehicle door device; a warning issuing unit that detects a sign of an operational abnormality in the vehicle door device based on the generated operation indicator, and when a sign of an operational abnormality is detected, issues a warning indicating the operational abnormality for which the sign is detected; an abnormality cause estimation unit that executes an abnormality cause estimation process including identifying, from the management information, the name and failure mode of a part corresponding to the operational abnormality indicated by the issued warning, and acquiring all of the identified names and failure modes of the parts as estimated causes of the operational abnormality whose sign has been detected; Equipped with the management information further includes a failure probability, which is an occurrence probability for each failure mode; The abnormality cause estimation unit If, in the management information, the operational abnormality indicated by the issued warning is associated with a plurality of failure modes that may be the cause of the operational abnormality, the names of all parts associated with the operational abnormality, the failure modes of the parts, and the failure probabilities of the failure modes are acquired, and a posterior probability calculation process is further executed to calculate, for each failure mode, a posterior probability that is a relative value of the failure probability of the failure mode to the sum of the failure probabilities of all failure modes associated with the operational abnormality indicated by the issued warning. Vehicle door device diagnostic system.

2. The abnormality cause estimation unit Based on the magnitude of the calculated posterior probability, the names of all parts acquired by the posterior probability calculation process and the likelihood that the failure modes of the parts are the cause of the operational abnormality for which the sign was detected are evaluated. The vehicle door device diagnostic system according to claim 1 .

3. the storage unit stores the management information as a stochastic process model in which a causal relationship between the failure mode and the operational abnormality is expressed in a tree structure; The abnormality cause estimation unit executes a posterior probability calculation process based on the stochastic process model. The vehicle door device diagnostic system according to claim 2 .

4. the failure modes and failure probabilities included in the management information are failure modes and failure probabilities of the failure modes listed for each part in a design stage of the vehicle door device, The abnormality cause estimation unit executes a posterior probability calculation process based on the failure probability of the failure mode included in the management information. The vehicle door device diagnostic system according to claim 2 .

5. The anomaly cause estimation unit displays the names of all acquired parts and the failure modes of the parts in descending order of posterior probability. The vehicle door device diagnostic system according to claim 2 .

6. the storage unit includes a warning history storage unit that stores a history of warnings issued by the warning issuing unit, The abnormality cause estimation unit executes an abnormality cause estimation process for the warning whose history is stored in the warning history storage unit. The vehicle door device diagnostic system according to claim 1 .

7. a disturbance removal unit that acquires a history of warnings stored in the warning history storage unit and performs a disturbance removal process to remove disturbances in the abnormality cause estimation process, The abnormality cause estimation unit receives the warning from the disturbance elimination unit after the disturbance has been eliminated and executes the abnormality cause estimation process.

7. The vehicle door device diagnostic system according to claim 6.

8. The performance indicator is an opening operation time representing the time required for the vehicle door device to start and complete an opening operation; a closing operation time representing the time required for the vehicle door device to complete a closing operation from the start; an opening operation wasted time representing a loss of time occurring from the start to the completion of an opening operation of the vehicle door device; a closing operation dead time representing a loss time occurring from the start to the completion of the closing operation of the vehicle door device; 2. The vehicle door device diagnostic system according to claim 1, further comprising:

9. The disturbance removal process includes: The disturbance removal unit selects only the warnings from the warning history acquired from the warning history storage unit, which have the shortest opening operation time, which indicates the time required for the vehicle door device to open from the start to the completion of the opening operation, and the shortest closing operation time, which indicates the time required for the vehicle door device to close from the start to the completion of the closing operation, in the corresponding operation indicators. The vehicle door device diagnostic system according to claim 7.

10. the disturbance removal unit acquires information representing a vehicle occupancy rate, The disturbance removal process includes: The disturbance elimination unit removes warnings issued under conditions where the occupancy rate exceeds a predetermined value from the warning history acquired from the warning history storage unit. The vehicle door device diagnostic system according to claim 7.

11. The action indicator generation unit a door open switch that issues an open command to the vehicle door device to prompt the vehicle door device to start an opening operation; a door close switch that issues a close command to the vehicle door device to prompt the vehicle door device to start a closing operation; an opening detection switch that detects completion of an opening operation of the vehicle door device; a closing detection switch that detects completion of a closing operation of the vehicle door device; a door cock which is a mechanism for manually opening and closing the vehicle door device; 2. The vehicle door device diagnostic system according to claim 1, wherein the operation indicator is generated based on a signal received from at least one of:

12. a computer stores management information for each operational abnormality, which is a type of abnormality in the opening and closing operation of the vehicle door device, indicating a warning indicating the operational abnormality, the names of one or more parts that may be the source of the operational abnormality among a plurality of parts constituting the vehicle door device, and failure modes that are types of failures that are expected for each of the one or more parts; generating an operation index, which is an evaluation index of the smoothness of the opening and closing operation of the vehicle door device, for each of the opening and closing operations of the vehicle door device by a computer; a computer detects a sign of an operational abnormality in the vehicle door device based on the generated operational indicator; If a sign of abnormal operation is detected, a computer issues a warning indicating the abnormal operation for which the sign is detected; executes, by a computer, an abnormality cause estimation process including identifying, from the management information, the name and failure mode of a part corresponding to the operational abnormality indicated by the issued warning, and acquiring all of the identified names and failure modes as estimated causes of the operational abnormality whose sign has been detected; the management information further includes a failure probability, which is an occurrence probability for each failure mode; The abnormality cause estimation process includes: If, in the management information, the operational abnormality indicated by the issued warning is associated with a plurality of failure modes that may be the cause of the operational abnormality, the names of all parts associated with the operational abnormality, the failure modes of the parts, and the failure probabilities of the failure modes are acquired, and a posterior probability calculation process is further executed to calculate, for each failure mode, a posterior probability that is a relative value of the failure probability of the failure mode to the sum of the failure probabilities of all failure modes associated with the operational abnormality indicated by the issued warning. A vehicle door device diagnostic method.

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