A rail transit train track data checking method, device, equipment and medium

Abstract

This invention relates to a method, apparatus, equipment, and medium for verifying track data of rail transit trains. The method includes the following steps: Step A: A diagnostic log recording module receives diagnostic messages from both ends of the train during operation and stores the log records; Step B: An import module imports all log records and map files; Step C: A tooth pitch calculation module calculates the average tooth pitch according to different train numbers and train end numbers; Step D: A tooth pitch verification module verifies the average tooth pitch and generates an accurate tooth pitch; Step E: A data verification module calculates the measured distance, theoretical distance, and distance error between adjacent beacons and generates a detailed measurement report; Step F: A data summarization module summarizes all measurement details and generates a track data verification report. Compared with the prior art, this invention has advantages such as improved data verification efficiency.

Description

Technical Field

[0001] This invention relates to rail transit signal control systems, and more particularly to a method, apparatus, equipment, and medium for verifying rail transit train track data. Background Technology

[0002] Communication-based automatic train control (CBTC) uses a communication network to achieve two-way communication between the train and ground equipment. Its onboard subsystem enables automatic train operation and automatic protection, requiring real-time calculation of the train's position for movement authorization. To ensure safe train operation, thorough safety tests are conducted on the onboard subsystem before the urban rail transit line opens. Among these tests, train track data verification is used to confirm that the equipment defined in the onboard electronic map matches its actual location on the track.

[0003] A search of Chinese patent publication CN107380205A reveals a track data detection vehicle and a track data detection method. Specifically, it discloses using laser displacement sensors to acquire track point data of a grooved rail, and then combining two sets of track point data obtained from two laser displacement sensors to correct errors caused by vehicle tilt, obtaining the final corrected data, making the subsequently obtained track geometric parameter data more accurate. However, this existing patent does not address track data verification testing. Due to the tight schedule and heavy workload of on-board subsystem field testing, how to provide a highly efficient and accurate method for track data verification testing has become a technical problem that needs to be solved. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology by providing a method, apparatus, equipment and medium for verifying track data of rail transit trains. This method can distinguish different vehicles and train end numbers to generate reports, improve the accuracy of calculated data, reduce the time spent on train runs, and improve the efficiency of data verification.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] According to a first aspect of the present invention, a method for verifying track data of rail transit trains is provided, the method comprising the following steps:

[0007] Step A: The diagnostic log recording module receives diagnostic messages from both ends of the train and stores the log records during train operation;

[0008] Step B: Import the module to import all log records and map files;

[0009] Step C: The tooth pitch calculation module calculates the average tooth pitch based on different train car numbers and train end numbers;

[0010] Step D: The tooth pitch verification module verifies the average tooth pitch and generates the accurate tooth pitch;

[0011] Step E: The data verification module calculates the measured distance, theoretical distance, and distance error between adjacent beacons and generates a detailed measurement report;

[0012] Step F: The data aggregation module summarizes all measurement details and generates a track data verification report.

[0013] As a preferred technical solution, this method allows multiple trains to perform tests simultaneously.

[0014] As a preferred technical solution, step A specifically includes:

[0015] The train was run in the field test area, and diagnostic log recording modules were used in the driver's cabs at both ends of the train to connect to the on-board subsystem, receive real-time diagnostic messages from the on-board subsystem, and store them as diagnostic log records.

[0016] As a preferred technical solution, the diagnostic log records include the following information: train number, train terminal number, previous beacon ID, number of teeth of the previous beacon, tooth pitch calibration value, MTIB1 device ID of the most recently calibrated device, MTIB2 device ID of the most recently calibrated device, and calibration status information.

[0017] As a preferred technical solution, step B specifically includes:

[0018] Import all records saved in step A and the vehicle electronic map file. The vehicle electronic map includes the following information: beacon ID, beacon location, adjacent beacons in each direction, and beacon displacement tolerance information.

[0019] As a preferred technical solution, step C specifically includes:

[0020] The tooth pitch calculation module reads all log records, distinguishes them according to different train numbers and train end numbers, obtains the tooth pitch information when the calibration is successful, and calculates the average calibration tooth pitch value corresponding to each train end number.

[0021] As a preferred technical solution, step D specifically involves: for each train number and train end number, the tooth pitch verification module verifies its tooth pitch value to obtain an accurate tooth pitch, which is used for calculating the measured distance in subsequent reports.

[0022] As a preferred technical solution, step E specifically includes:

[0023] The data verification module calculates and generates a detailed measurement report based on the imported log records, the vehicle electronic map file, and the tooth pitch value confirmed by the user in step D.

[0024] As a preferred technical solution, the measurement details report includes the following: Beacon 1 ID, Beacon 2 ID, measured distance, theoretical distance, the difference between the theoretical distance and the measured distance, the allowable error for each beacon, the file name, date and detailed time of the log record.

[0025] As a preferred technical solution, the track data verification report in step F includes the following: Beacon 1 ID, track segment ID to which Beacon 1 belongs, Beacon 2 ID, track segment ID to which Beacon 2 belongs, the number of measurements for this pair of beacons, the actual measured distance, the theoretical distance, the minimum difference between the theoretical distance and the measured distance, the maximum difference between the theoretical distance and the measured distance, the average difference between the theoretical distance and the measured distance, the allowable error of Beacon 1, the allowable error of Beacon 2, and the final test conclusion for each group of beacons.

[0026] According to a second aspect of the present invention, a rail transit train track data verification device is provided, the device comprising:

[0027] The diagnostic log recording module is used to receive diagnostic messages from both ends of the train and store log records during train operation;

[0028] The import module is used to import all log records and map files;

[0029] The tooth pitch calculation module is used to calculate the average tooth pitch based on different train car numbers and train end numbers;

[0030] The tooth pitch verification module is used to verify the average tooth pitch and generate an accurate tooth pitch.

[0031] The data verification module is used to calculate the measured distance, theoretical distance, and distance error between adjacent beacons and generate a detailed measurement report;

[0032] The data aggregation module is used to summarize all measurement details and generate a track data verification report.

[0033] According to a third aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method described thereon.

[0034] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method described thereon.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] 1) After summarizing the log records, this invention calculates the gear pitch separately according to different trains and train end numbers, and uses the corresponding pitch parameters to calculate and summarize the final track data verification report, which can greatly reduce the test execution time and improve work efficiency and the accuracy of report data.

[0037] 2) The human-machine interface of this invention is easy to operate, intuitive to display, and has a low learning cost;

[0038] 3) This invention allows multiple trains to be used for running tests simultaneously, reducing testing time, improving work efficiency, and saving labor costs;

[0039] 4) This invention distinguishes between vehicle and end number for wheel diameter calibration and tooth pitch calculation, resulting in more accurate tooth pitch calculation and improved accuracy of track data verification results. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the interface of the diagnostic log recording module of the present invention;

[0041] Figure 2 This is a schematic diagram of the tooth pitch calculation and confirmation interface of the present invention;

[0042] Figure 3 This is a schematic diagram illustrating the specific process of the orbital data verification method of the present invention;

[0043] Figure 4 This is a schematic diagram of the track data verification device of the present invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] like Figure 3 As shown, this invention provides an effective track data verification method that allows multiple trains to perform tests simultaneously. After summarizing the log records, the gear pitch is calculated separately based on different trains and train end numbers. The final track data verification report is calculated and summarized using the corresponding pitch parameters, which can greatly reduce test execution time, improve work efficiency, and enhance the accuracy of report data. The data verification method specifically includes the following steps:

[0046] Step A: The diagnostic log recording module receives diagnostic messages from both ends of the train and stores the log records during train operation;

[0047] Step B: Import the module to import all log records and map files;

[0048] Step C: The tooth pitch calculation module calculates the average tooth pitch based on different train car numbers and train end numbers;

[0049] Step D: The tooth pitch verification module verifies the average tooth pitch and generates the accurate tooth pitch;

[0050] Step E: The data verification module calculates the measured distance, theoretical distance, and distance error between adjacent beacons and generates a detailed measurement report;

[0051] Step F: The data aggregation module summarizes all measurement details and generates a track data verification report.

[0052] Step A: Run the train in the field test area, and connect the diagnostic log recording module to the onboard subsystem in the driver's cab at both ends of the train to receive real-time diagnostic messages from the onboard subsystem and store them as diagnostic log records. The diagnostic log records include the following variable information: train number, train end number, previous beacon ID, number of teeth of the previous beacon, tooth pitch calibration value, MTIB1 device ID of the most recently calibrated device, MTIB2 device ID of the most recently calibrated device, calibration status, etc.

[0053] Step B: The user uses the human-machine interface to import all the records saved in step A and the vehicle-mounted electronic map file into the program. The vehicle-mounted electronic map includes the following information: beacon ID, beacon location, adjacent beacons in each direction, and beacon displacement tolerance, etc.

[0054] Step C: The tooth pitch calculation module reads all log records, distinguishes them according to different train numbers and train end numbers, obtains the tooth pitch information when the calibration is successful, and calculates the average calibration tooth pitch value corresponding to each train end number.

[0055] Step D: For each train number and train end number, the tooth pitch verification module verifies its tooth pitch value to obtain the accurate tooth pitch, which is used for the calculation of the measured distance in subsequent reports.

[0056] Step E: The data verification module calculates and generates a detailed measurement report based on the imported log records, the vehicle electronic map file, and the tooth pitch value confirmed by the user in step D. The detailed measurement report includes the following: Beacon 1 ID, Beacon 2 ID, measured distance, theoretical distance, the difference between the theoretical distance and the measured distance, the allowable error for each beacon, the file name, date, and detailed time of the log record.

[0057] Step F: The data aggregation module aggregates all measurement details and generates a track data verification report. The track data report includes the following: Beacon 1 ID, track segment ID to which Beacon 1 belongs, Beacon 2 ID, track segment ID to which Beacon 2 belongs, number of measurements for this pair of beacons, actual measured distance, theoretical distance, minimum difference between theoretical and measured distance, maximum difference between theoretical and measured distance, average difference between theoretical and measured distance, allowable error for Beacon 1, allowable error for Beacon 2, and the final test conclusion (pass or fail) for each group of beacons. Specific Implementation

[0059] The rail transit train track data verification method of this invention provides a visual operation interface, allowing users to use flexible configurations for onboard software log recording. An example of the interface display is attached. Figure 1 As shown. The user installs the logging module software on a laptop and connects it to the front panel network port of the vehicle software using an Ethernet cable. After reading the IP address and port provided in the communication configuration, the logging module establishes communication with the vehicle software, receives diagnostic log messages from the vehicle software, and parses the required fields according to the field names, start bytes, field sizes, and other configurations in the configuration file, displaying them on the interface for the user to view. When the number of diagnostic messages accumulates to a certain amount, they are automatically saved as a log file. The variables in the onboard software diagnostic messages include: CC_SSID (train number), CC_Core_ID (train terminal number), ATP.beacon_id (most recent beacon ID), latest_TopLocFrozenCogCounter (cog count when the most recent beacon was read), TRAIN_CALIB.raw_calibration (most recent gear pitch calibration value), TRAIN_CALIB.mtib1_id (most recent calibrated MTIB1 ID), TRAIN_CALIB.mtib2_id (most recent calibrated MTIB2 ID), TRAIN_CALIB.state (most recent calibration status), TRAIN_CALIB.calibration (average calibration value of two consecutive gears), and top_loc_valid_num (number of beacon Top Locs).

[0060] After the test train has completed its test run through the test area, the user saves and summarizes the log records stored in the log recording module, and then imports them into the software using the visual interface of the track verification module. Simultaneously, the onboard electronic map file should be imported for subsequent calculations.

[0061] The tooth pitch calculation module reads the log file, calculates and parses the data based on the starting byte and field length of each field in the configuration file, traverses the log records, calculates for each end of each vehicle, obtains records with a valid calibration status of SUCCESSED, takes the average value of TRAIN_CALIB.raw_calibration, and calculates the average tooth pitch.

[0062] The tooth pitch verification module verifies the tooth pitch value for each train car number and train end number to obtain the accurate tooth pitch. This tooth pitch is used for calculating the measured distance in subsequent reports. The calculated accurate tooth pitch is displayed on the interface for easy viewing. An example of the interface display is attached. Figure 2 As shown.

[0063] The data verification module performs calculations based on the imported logs and in-vehicle electronic maps, specifically including the following steps:

[0064] 1) Group the log files according to the train number CC_SSID and the train terminal number CC_Core_ID;

[0065] 2) Traverse all log files on the current train. When ATP.beacon_id changes and latest_TopLocFrozenCogCounter changes simultaneously (assuming the period number of the change is n), it indicates that a valid set of adjacent beacons has been read. Record ATP.beacon_id(n-1) as beacon1_ID and ATP.beacon_id(n) as beacon2_ID. Calculate the measured distance between beacon1 and beacon2 using the following formula:

[0066] MeasuredDistance=InputCalibration×|CogCounter(n)-CogCounter(n-1)|

[0067] InputCalibration is the calculated tooth pitch value corresponding to the train end number, CogCounter(n) refers to the value of the latest_TopLocFrozenCogCounter variable at period n, and CogCounter(n-1) refers to the value of the latest_TopLocFrozenCogCounter variable at period n-1.

[0068] 3) Calculate the theoretical distance between beacon1 and beacon2 in the vehicle-mounted electronic map file from step 2). The vehicle-mounted electronic map uses track blocks and their offsets to describe the position of the beacons. First, calculate the blocks where beacon1 and beacon2 are located and the block links between them. Then, calculate the theoretical distance between the two beacons using block.length and absissa.

[0069] 4) Calculate the distance error, which is the difference between the measured distance and the theoretical distance;

[0070] 5) Generate a detailed measurement report file. A sample report is shown in Table 1.

[0071] Table 1

[0072]

[0073] The data aggregation module reads all measurement detail reports and aggregates them, counting the number of times each pair of adjacent beacons appears in the measurement detail reports as the measurement count, and calculates the minimum, maximum, and average values ​​of the difference between the theoretical distance and the measured distance.

[0074] The test result is "pass" when a pair of beacons meets the following criteria:

[0075] MeasureCount≥4

[0076]

[0077] MeasureCount represents the measurement test results for the pair of beacons, AverageDelta represents the average difference between the theoretical and measured distances of the pair of beacons across all measurements, and Beacon1Tolerence and Beacon2Tolerence represent the error tolerances for these two beacons.

[0078] The final generated track data verification summary report is shown in Table 2:

[0079] Table 2

[0080] Beacon 1id 1194 1195 1195 781 Beacon 2id 1195 1196 1194 782 Block 2id 353 353 353 215 Measure count 4 4 4 4 Measured distance 4.865 4.913 4.879 43.3 Theorical distance 4.89 4.89 4.89 43.08 Min delta -0.025 0.002 -0.025 0.22 Max delta -0.025 0.03 0.002 0.22 Average delta -0.025 0.023 -0.011 0.22 Beacon 1Tolerance 0.1 0.1 0.1 0.1 Beacon 2Tolerance 0.1 0.1 0.1 0.1 Conclusion OK OK OK NOK

[0081] The above is an introduction to the method embodiments. The following describes the solution of the present invention further through device embodiments.

[0082] like Figure 4 As shown, a rail transit train track data verification device includes:

[0083] The diagnostic log recording module 100 is used to receive diagnostic messages from both ends of the train and store log records during train operation;

[0084] Import module 200 is used to import all log records and map files;

[0085] The tooth pitch calculation module 300 is used to calculate the average tooth pitch according to different train car numbers and train end numbers;

[0086] Tooth pitch verification module 400 is used to verify the average tooth pitch and generate accurate tooth pitch;

[0087] The data verification module 500 is used to calculate the measured distance, theoretical distance, and distance error between adjacent beacons and generate a detailed measurement report.

[0088] The data aggregation module 600 is used to aggregate all measurement details and generate a track data verification report.

[0089] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0090] The electronic device of this invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0091] Multiple components in the device are connected to the I / O interface, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards (NICs), modems, and wireless transceivers. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0092] The processing unit performs the various methods and processes described above, such as the methods of the present invention. For example, in some embodiments, the methods of the present invention may be implemented as computer software programs tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the methods of the present invention described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute the methods of the present invention by any other suitable means (e.g., by means of firmware).

[0093] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0094] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0095] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0096] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A rail transit train track data checking method, characterized in that, The method includes the following steps: Step A: The diagnostic log recording module receives diagnostic messages from both ends of the train and stores the log records during train operation; Step B: Import the module to import all log records and map files; Step C: The tooth pitch calculation module calculates the average tooth pitch based on different train car numbers and train end numbers; Step D: The tooth pitch verification module verifies the average tooth pitch and generates an accurate tooth pitch; Step E: The data verification module calculates the measured distance, theoretical distance, and distance error between adjacent beacons and generates a detailed measurement report; Step F: The data aggregation module summarizes all measurement details and generates a track data verification report; This method allows for simultaneous testing using multiple trains; The diagnostic log records include the following information: train number, train terminal number, previous beacon ID, number of teeth of the previous beacon, tooth pitch calibration value, MTIB1 device ID of the most recently calibrated device, MTIB2 device ID of the most recently calibrated device, and calibration status information. Step C specifically involves: The tooth pitch calculation module reads all log records, distinguishes them according to different train numbers and train end numbers, obtains the tooth pitch information when the calibration is successful, and calculates the average calibration tooth pitch value corresponding to each train end number. The track data verification report in step F includes the following: Beacon 1 ID, track segment ID to which Beacon 1 belongs, Beacon 2 ID, track segment ID to which Beacon 2 belongs, number of measurements for this pair of beacons, actual measured distance, theoretical distance, minimum difference between theoretical and measured distance, maximum difference between theoretical and measured distance, average difference between theoretical and measured distance, allowable error for Beacon 1, allowable error for Beacon 2, and final test conclusion for each group of beacons.

2. The track data checking method of claim 1, wherein, Step A specifically involves: The train was run in the field test area, and diagnostic log recording modules were used in the driver's cabs at both ends of the train to connect to the on-board subsystem, receive real-time diagnostic messages from the on-board subsystem, and store them as diagnostic log records.

3. The track data checking method of claim 1, wherein, Step B specifically involves: Import all records saved in step A and the vehicle electronic map file. The vehicle electronic map includes the following information: beacon ID, beacon location, adjacent beacons in each direction, and beacon displacement tolerance information.

4. The track data checking method of a rail transit train according to claim 1, characterized in that, Step D specifically involves: for each train number and train end number, the tooth pitch verification module verifies its tooth pitch value to obtain the accurate tooth pitch, which is used for calculating the measured distance in subsequent reports.

5. The method for verifying track data of rail transit trains according to claim 1, characterized in that, Step E specifically involves: The data verification module calculates and generates a detailed measurement report based on the imported log records, the vehicle electronic map file, and the tooth pitch value confirmed by the user in step D.

6. The method for verifying track data of rail transit trains according to claim 5, characterized in that, The measurement details report includes the following: Beacon 1 ID, Beacon 2 ID, measured distance, theoretical distance, difference between theoretical and measured distance, tolerance for each beacon, file name, date, and detailed time of the log record.

7. A rail transit train track data verification device, characterized in that, The device includes: The diagnostic log recording module is used to receive diagnostic messages from both ends of the train and store log records during train operation; The import module is used to import all log records and map files; The tooth pitch calculation module is used to calculate the average tooth pitch based on different train car numbers and train end numbers; The tooth pitch verification module is used to verify the average tooth pitch and generate an accurate tooth pitch. The data verification module is used to calculate the measured distance, theoretical distance, and distance error between adjacent beacons and generate a detailed measurement report; The data aggregation module is used to aggregate all measurement details and generate a track data verification report; The device allows multiple trains to perform tests simultaneously; The diagnostic log records include the following information: train number, train terminal number, previous beacon ID, number of teeth of the previous beacon, tooth pitch calibration value, MTIB1 device ID of the most recently calibrated device, MTIB2 device ID of the most recently calibrated device, and calibration status information. The tooth pitch calculation module reads all log records, distinguishes them according to different train numbers and train end numbers, obtains the tooth pitch information when the calibration is successful, and calculates the average calibration tooth pitch value corresponding to each train end number. The track data verification report includes the following: Beacon 1 ID, track segment ID to which Beacon 1 belongs, Beacon 2 ID, track segment ID to which Beacon 2 belongs, number of measurements for this pair of beacons, actual measured distance, theoretical distance, minimum difference between theoretical and measured distance, maximum difference between theoretical and measured distance, average difference between theoretical and measured distance, allowable error for Beacon 1, allowable error for Beacon 2, and final test conclusion for each pair of beacons.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

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