Method for automatically checking messages and pictures of rail wagon and providing cluster identification

Abstract

The invention discloses a method for automatically checking railway wagon messages and pictures and providing cluster identification. The method comprises the following steps: monitoring railway wagon passing messages written into a disk; wherein the magnetic disk is a magnetic disk, used for storing railway wagon passing messages, of the detection station; when the wagon passing message is written in, analyzing the wagon passing message to obtain a wagon passing state; when the vehicle passing state is that vehicle passing is completed, the number of vehicle passing pictures in a disk predetermined directory is collected and compared with the number of predetermined vehicle passing pictures; determining the passing state of the railway wagon according to the comparison result; according to the method and the device, the passing state is determined by simultaneously utilizing the passing message and the passing picture of the railway wagon, so that the obtained process state is more accurate, the real-time performance of determining the passing state can be improved by monitoring the passing message of the railway wagon in the magnetic disk in real time, and the accuracy of determining the passing state is improved. And a railway wagon passing message and a railway wagon passing picture are provided for an image identification cluster of the railway wagon fault image detection system in time.

Description

Technical Field

[0001] The invention belongs to the technical field of railway freight car fault cluster identification, and in particular relates to a method for automatically verifying railway freight car messages and pictures and providing cluster identification. Background Art

[0002] In the railway freight car fault image detection system, the important parts of the railway freight car are photographed by a linear array scanning camera located next to the railway track. The photographed pictures are transmitted to the detection station, which processes and stores the pictures and finally provides them to the back-end equipment for post-recognition processing to complete the safety inspection of the important parts of the railway freight car.

[0003] During the file and image transmission process between the detection station and the back-end equipment, it is usually necessary to confirm that the railway truck process is completed before transmitting to the back-end equipment. However, in actual applications, it is often difficult for the detection station to accurately and real-time determine the status of the railway truck process, thereby reducing the operating efficiency and accuracy of the railway truck fault image detection system. Summary of the invention

[0004] The purpose of the present invention is to provide a method for automatically verifying railway freight car messages and pictures and providing cluster recognition, so as to obtain the process status of railway freight cars in a timely and accurate manner, thereby improving the operating efficiency and accuracy of the railway freight car fault image detection system.

[0005] The present invention adopts the following technical solution: a method for automatically checking railway freight car messages and pictures and providing cluster identification, comprising the following steps:

[0006] Monitor the railway freight train passing message written to the disk; wherein the disk is a disk used by the detection station to store the railway freight train passing message;

[0007] When a railway freight train passing message is written, the railway freight train passing message is parsed to obtain the passing status;

[0008] When the vehicle passing status is completed, the number of vehicle passing pictures in the predetermined directory on the disk is collected and compared with the predetermined number of vehicle passing pictures;

[0009] The passing status of railway freight cars is determined based on the comparison results.

[0010] Furthermore, the comparison with the number of predetermined vehicle passing pictures includes:

[0011] Compare the number of passing vehicle pictures with the scheduled number of passing vehicle pictures according to the work station code.

[0012] Further, determining the passing status of the railway freight car according to the comparison result includes:

[0013] When the number of passing pictures reaches the predetermined number of passing pictures, the railway freight car passing message and passing pictures are stored, and the railway freight car passing status is updated to passing completed.

[0014] Further, determining the passing status of the railway freight car according to the comparison result includes:

[0015] When the number of passing pictures corresponding to the workstation codes is equal to the predetermined number of passing pictures, the passing status of the railway freight car is determined to be completed.

[0016] Furthermore, it also includes:

[0017] When the number of passing pictures corresponding to any workstation code is less than the predetermined number of passing pictures, the passing status of the railway freight car is determined to be not completed.

[0018] Furthermore, parsing the railway freight car passing message to obtain the passing status includes:

[0019] Parsing railway freight car passing messages;

[0020] The receiving status in the train message content in the railway freight car passing message is used as the passing status.

[0021] Furthermore, parsing the railway freight car passing message to obtain the passing status includes:

[0022] Parsing railway freight car passing messages;

[0023] Query the number of vehicles and vehicle messages in the train message content of the railway freight car passing message;

[0024] The vehicle passing status is determined based on the number of vehicles and the number of vehicle messages.

[0025] Further, updating the railway freight car passing status to passing completed also includes:

[0026] Provide railway freight car fault image detection system's image recognition cluster with railway freight car passing messages and pictures.

[0027] Furthermore, providing railway freight car passing messages and passing pictures to the image recognition cluster of the railway freight car fault image detection system includes:

[0028] Provide railway freight car passing messages to the image recognition cluster through a secure encryption interface;

[0029] Provide passing car pictures to the image recognition cluster through Nginx reverse proxy.

[0030] Another technical solution of the present invention: a device for automatically verifying railway freight car messages and pictures and providing cluster identification, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the above method is implemented when the processor executes the computer program.

[0031] The beneficial effects of the present invention are as follows: the present invention simultaneously utilizes railway freight car passing messages and passing pictures to determine the passing status, which can make the obtained process status more accurate, and by real-time monitoring of railway freight car passing messages in the disk, the real-time performance of the passing status determination can be improved, and the railway freight car passing messages and passing pictures can be provided to the image recognition cluster of the railway freight car fault image detection system in a timely manner, thereby improving the operating efficiency and accuracy of the railway freight car fault image detection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of a method for automatically checking railway freight car messages and pictures and providing cluster identification in an embodiment of the present invention;

[0033] Figure 2 The present invention is a schematic diagram of the structure of a device for automatically verifying railway freight car messages and pictures and providing cluster identification in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] At present, the existing technology uses multi-threaded reading of FTP server files to obtain railway freight car passing messages and pictures. The disadvantage of this problem is that when the reading of picture files is interrupted or timed out, all picture files need to be re-read and historical files need to be deleted.

[0036] In addition, the shortcomings of FTP in data transmission may not only be security, but also many other aspects, including data reliability, accuracy, ease of operation, etc., as follows: security vulnerabilities, FTP client ID and password are transmitted in plain text, FTP can be used for DOS attacks or become a network vulnerability, FTP Client is very common and free, which provides convenience for hackers, FTP transmission is easy to be intercepted and stolen, and even SFTP is difficult to cope with today's network threats. The average failure rate of FTP is 6% and the fragile reliability puts technicians in firefighting mode at any time. First come first served, lack of priority control mechanism and strategy. Poor transmission performance, sometimes the sent data will never reach the destination. Unable to immediately notify and handle transmission anomalies, until the business fails, the problem is not discovered, or even learned from the customer. Difficult to operate and maintain, account issuance and recovery, temporary permission adjustment. Forced to manage more and more server nodes. Custom scripts and integration will only bring more failure points and ultimately waste valuable development resources.

[0037] The present invention monitors the dynamic addition, modification and deletion of disk directory files through a third-party component; caches the equipment information message, train data message and train vehicle picture file that meet the train inspection requirements; performs algorithm verification on the train passing data and picture data; verifies whether they are complete through the picture rules of each workstation; and provides cluster AI recognition through load balancing nginx and interface methods.

[0038] The present invention discloses a method for automatically verifying railway freight car messages and pictures and providing cluster identification, comprising the following steps: S110, monitoring railway freight car passing messages written into a disk; wherein the disk is a disk used by a detection station to store railway freight car passing messages; S120, when a railway freight car passing message is written, parsing the railway freight car passing message to obtain a passing status; S130, when the passing status is passing completion, collecting the number of passing pictures in a predetermined directory on the disk, and comparing them with the predetermined number of passing pictures; S140, determining the passing status of the railway freight car according to the comparison result.

[0039] The present invention simultaneously utilizes railway freight car passing messages and passing pictures to determine the passing status, which can make the obtained process status more accurate, and by real-time monitoring of railway freight car passing messages in the disk, the real-time performance of the passing status determination can be improved, and the railway freight car passing messages and passing pictures can be provided to the image recognition cluster of the railway freight car fault image detection system in a timely manner, thereby improving the operating efficiency and accuracy of the railway freight car fault image detection system.

[0040] In one embodiment, the present invention uses JNotify to monitor the file directory of the disk detection station, writes files to the disk by monitoring, and reads the disk files for analysis.

[0041] When multiple detection stations and multiple trains pass at the same time, this method supports concurrent processing and parsing of file contents, and also supports random order transmission and parsing of single train passing messages; moreover, when multiple train messages are concurrently written to disk at the same time, the train vehicle data in the message is guaranteed to be written to the database normally. It also supports real-time parsing of passing messages, high concurrent writing, and high-timeliness provision of image data.

[0042] When doing data access or file parsing, it is often necessary to monitor and parse the image files in the directory of the specified detection station. When monitoring files, the usual practice is to obtain the files in the directory by periodically polling the directory, and this method will have a delay. Therefore, the present invention uses JNotify to provide a Java version of the solution, and references the Notify mechanism. The file information that this mechanism can monitor includes: folder / file creation, folder / file deletion, folder / file modification, folder / file renaming, etc.

[0043] Because Jnotify is developed in C language, you need to add jnotify_64bit.dll (64-bit) (Windows) or libjnotify.so (linux) dynamic library to the system. Add jnotify_64bit.dll (64-bit) to C:\Windows\System32. Add libjnotify.so to the / lib64 directory.

[0044] At the same time, write a class that inherits JNotifyAdapter. Rewrite the method to set the listening folder, add the events to be listened, whether to listen to the subfolder, and add the method to start the monitoring program.

[0045] Regarding the message parsing method, you can use the Scanner class, BufferReader class, FileInputStream class, or FileChannel class.

[0046] In the embodiment of the present invention, the railway freight car passing message is named: LC_passing sequence number_passing time_data batch number_version number.data. The specific content of the message is as follows:

[0047] LC, train number, passing time, driving direction, number of vehicles (total number of vehicles in the train), number of locomotives, number of freight vehicles, number of passenger vehicles, average speed, maximum speed, minimum speed, marshaling type, and receiving status;

[0048] CL, train number, passing time, passing sequence, vehicle number, vehicle type, vehicle model, manufacturer, manufacturing date, change length, vehicle assignment, wheelbase, number of middle part images, number of bottom images of vehicle end connection, number of bottom images of foreground bogie, number of middle part images of vehicle frame, number of bottom images of back bogie, number of side images of vehicle end connection, number of side images of foreground bogie, number of middle part images of vehicle side, number of side images of back bogie, number of vehicle axles, end position, image positioning information, number of images captured by single-channel camera on the side, number of images captured by single-channel camera on the bottom, number of images captured by single-channel camera on the middle side, number of images captured by single-channel camera on the side for regular inspection, number of images captured by single-channel camera on the side line scan, number of images captured by single-channel camera on the bottom line scan.

[0049] Among them, the messages starting with LC are train messages, and the messages starting with CL are vehicle messages.

[0050] In one embodiment, parsing a railway freight car passing message to obtain a passing status includes: parsing the railway freight car passing message; using the receiving status in the train message content in the railway freight car passing message as the passing status. The receiving status can be a character code, such as 0 indicating that the passing is not completed, and 1 indicating that the passing is completed. For another example, the receiving status can also be 021, 038, etc., indicating the number of vehicles that have passed the train.

[0051] That is to say, the present invention directly extracts the train receiving status in the above train message as the train passing status of the message. This method only needs to query and does not require calculation, which can save time and improve efficiency.

[0052] In another embodiment, parsing a railway freight car passing message to obtain a passing status includes: parsing the railway freight car passing message; querying the number of vehicles and the number of vehicle messages in the train message content in the railway freight car passing message; and determining the passing status according to the number of vehicles and the number of vehicle messages.

[0053] Specifically, the train message contains the number of vehicles, which refers to the number of carriages in a railway freight train. Therefore, the total number of vehicles in the train can be determined through the content of the message. At the same time, the number of vehicle messages is queried, and finally the number of vehicles and the number of corresponding vehicle messages are compared to obtain the passing status. For example, if the number of vehicles is 50 and the number of vehicle messages received is also 50, it means that the passing is completed. If the number of vehicle messages received is 48, it means that the passing is not completed.

[0054] Of course, each method of obtaining the vehicle passing status has its own advantages and disadvantages. You can choose one or both methods according to the application scenario requirements.

[0055] In the present invention, in addition to obtaining the passing status by parsing the railway freight car passing message, the number of passing pictures is verified to increase the accuracy of judging the passing status.

[0056] In an embodiment of the present invention, comparing with the predetermined number of passing vehicle images includes: comparing the number of passing vehicle images with the predetermined number of passing vehicle images according to the workstation code. When the number of passing vehicle images reaches the predetermined number of passing vehicle images, the passing is considered completed, the railway freight car passing message and the passing vehicle images are stored, and the railway freight car passing status is updated to the passing completed. When the number of passing vehicle images does not reach the predetermined number of passing vehicle images, it is considered that the passing is not completed.

[0057] More specifically: when the number of passing pictures corresponding to each workstation code is equal to the predetermined number of passing pictures, the railway freight car passing status is determined to be completed. When the number of passing pictures corresponding to any workstation code is less than the predetermined number of passing pictures, the railway freight car passing status is determined to be incomplete.

[0058] In other words, the total number of vehicle passing pictures can be compared with the total number of scheduled vehicle passing pictures. When more precision is required, the vehicle passing is considered completed only when the number of pictures coded at each workstation meets the requirement.

[0059] In the embodiment of the present invention, the naming rule of the file directory is: vehicle passing time (year, month, day)\vehicle passing time (hour, minute, second)_vehicle passing sequence number, such as 20230228\120301_3\, which means the railway freight car folder with vehicle sequence number 3 at 12:03:01 on February 28, 2023. The naming format of each picture can be: vehicle passing sequence_station code_picture code.jpg.

[0060] The vehicle serial number indicates the serial number of vehicles that have passed the detection station since midnight on the same day, such as 101, variable length, up to 4 digits. The vehicle passing time is expressed as YYYYMMDDHH24MISS, with a fixed length of 14 digits. The vehicle sequence indicates the number of the vehicle, such as 1, 2, 3, etc., variable length, up to 3 digits. The station code is usually from 1 to 8 to represent different viewing stations (carriage parts), see Table 1 below for details. The picture code indicates the picture number of each position of each station, starting from 0, and increasing from left to right in each screen "nine-square grid", and when a row is filled, it will change to another row to continue numbering.

[0061] Table 1

[0062]

[0063]

[0064] More specifically, for example, 20230228\120101_1\1_5_2.jpg means the 1_5_2.jpg picture in the 20230228\120101_1 file directory, which means a picture in the directory with vehicle serial number 1 at 12:01:01 on February 28, 2023. This picture is the second picture of vehicle No. 1 and work station code 5 (indicating the side of the bus).

[0065] For example, 20230228\120101_21\2_3_24.jpg means the 2_3_24.jpg picture in the 20230228\120101_21 file directory, which means a picture in the directory with vehicle serial number 21 at 12:01:01 on February 28, 2023. The picture is the 24th picture of vehicle No. 2 and work station code 3 (indicating the middle part of the bottom).

[0066] It should be noted that the size of each picture in the workstation map is uniformly 1400 pixels in width and 1024 pixels in height. The horizontal direction of the picture is the driving direction, and the train is photographed moving from the right side of the display to the left side. Among them, the left side is the left hand side of the driver's seat facing the driving direction, and the right side is the right hand side of the driver's seat facing the driving direction. The side image is the same as the bottom image. The image should be mirrored according to the movement from the right to the left.

[0067] In the present invention, a switch can be used to control whether to perform image verification, which can be specifically set in the configuration file. When the image verification switch is turned off (i.e., after parsing the railway freight car passing message to obtain the passing status, when the passing status is completed, directly update the process status without performing subsequent steps), the program will run more efficiently and can provide train data to the intelligent recognition cluster more quickly.

[0068] In this embodiment, the rules for setting the number of pictures reserved for each workstation are explained.

[0069] 1. The number of pictures of the side frame (i.e. bogie) station is as follows:

[0070] Calculation formula: (number of images of the side line scanning camera single channel - number of images of the middle side single channel camera) * 2 = (12-6) * 2 = 12 images.

[0071] Such as #_1_0.jpg, #_1_1.jpg, #_1_2.jpg, #_1_3.jpg, #_1_4.jpg, #_1_5.jpg, component name: front side frame, component id 00.

[0072] #_1_6.jpg, #_1_7.jpg, #_1_8.jpg, #_1_9.jpg, #_1_10.jpg, #_1_11.jpg, component name: backstage side frame component id 01. Among them, # represents the vehicle number.

[0073] 2. The total number of pictures of brake beam workstations is 12.

[0074] #_2_0.jpg~#_2_11.jpg, the three rows and two columns of this workstation form a component, which is divided into the front brake beam, component id 02, and the back brake beam, component id 03.

[0075] 3. Total number of pictures of the middle part (i.e. the middle part of the bottom):

[0076] Calculation formula: number of middle images*3=6*3=18.

[0077] #_3_0.jpg~#_3_17.jpg, the three rows and three columns of this station form a component, and the 18 pictures are divided into middle part 1, middle part 2, middle part 3 and other parts in the middle part (if any), the ids are: 08, 09, 06, 24,

[0078] There is a special case in the middle part. The number of images in the middle part = 6, three rows and three columns, which equals 7. The last column may be discontinuous or continuous.

[0079] 4. The total number of pictures of the hook and buffer station is 9.

[0080] The image sequence is: #_4_0.jpg~#_4_8.jpg, component id 04.

[0081] The total number of pictures of the inter-hook difference workstations is 2.

[0082] The image sequence is: #_4_9.jpg, #_4_10.jpg component id 10.

[0083] In addition, it should be noted that the following two parts are added to the tail car: the total number of pictures of the tail hook and buffer station is 6. The picture sequence is: #_4_11.jpg~#_4_16.jpg, part id 14; the total number of pictures of the tail hook difference station is 2. The picture sequence is: #_4_17.jpg, #_4_18.jpg, part id 15.

[0084] 7. Total number of side and middle workstation pictures:

[0085] Calculation formula: number of middle images*2=6*2=12.

[0086] #_7_0.jpg, #_7_1.jpg, #_7_2.jpg, #_7_3.jpg, #_7_4.jpg, #_7_5.jpg, #_7_6.jpg, #_7_7.jpg, #_7_8.jpg, #_7_9.jpg, #_7_10.jpg, #_7_11.jpg, the two rows and three columns (2*3) of this workstation are a component, which are divided into middle part side 1, middle part side 2 and middle part side 3 and other (if any) components of the middle part side, the ids are: 30, 31, 32, 33 respectively.

[0087] 8. Total number of pictures of the side workstations of the vehicle body:

[0088] Calculation formula: Number of images of a single-channel camera for side inspection*2=12*2=24.

[0089] The sequence of the figures is: #_8_0.jpg~#_8_23.jpg. The two rows and three columns of this workstation constitute a component, which are divided into body side 1, body side 2, body side 3 and other body sides (if any). The component IDs are: 26, 27, 28, 29 respectively.

[0090] In one embodiment, after updating the railway freight car passing status to passing completed, the method further includes: providing a railway freight car passing message and a passing picture to an image recognition cluster of a railway freight car fault image detection system.

[0091] Specifically, railway freight train passing messages are provided to the image recognition cluster through a secure encryption interface; and passing train pictures are provided to the image recognition cluster through the Nginx reverse proxy.

[0092] In the security encryption interface of this embodiment, a username and password are first generated for the image recognition cluster, and the values ​​are sent to the image recognition cluster. At the same time, a token with a time code is issued for a period of time. When the image recognition cluster needs to obtain a railway freight car passing message, the username, password and time code are verified, and data is provided to it only when the verification is passed. In addition, the Nginx reverse proxy method can directly obtain the stored pictures, which improves the picture transmission rate.

[0093] In summary, the present invention realizes the monitoring of concurrent message and picture data of multiple detection stations of TFDS, with high real-time performance. It ensures that train messages and pictures can be detected in real time. At the same time, the number of pictures is checked to see if they are complete based on the verification of TFDS truck passing message data; the number of components is detected through train message parameters. The train passing data query interface is provided through encrypted token, and the Nginx reverse proxy provides the picture data access address.

[0094] The six detection stations in the current application example monitor disk file writing in real time 24 / 7, which has greatly improved the file reading time compared with the previous FTP technology performance. At the same time, the detection station can provide the passing data and image data to the task management center system about 2 to 3 minutes after a train passes.

[0095] The present invention also discloses a device for automatically checking railway freight car messages and images and providing cluster identification, including a memory 310, a processor 320, and a computer program 330 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 330, the above method is implemented.

[0096] The present invention also discloses an embodiment that provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0097] The present invention also provides a computer program product. When the computer program product runs on a data storage device, the data storage device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0098] If the integrated unit module is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to a storage device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electrical carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0099] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0100] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0101] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0102] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Claims

1. A method for automatically checking railway freight car messages and pictures and providing cluster identification, characterized in that: The following steps are involved: Monitoring railway freight train passing messages written to a disk; wherein the disk is a disk used by the detection station to store railway freight train passing messages; When a railway freight train passing message is written, the railway freight train passing message is parsed to obtain the passing status; When the vehicle passing status is vehicle passing completion, the number of vehicle passing pictures in the predetermined directory of the disk is collected and compared with the predetermined number of vehicle passing pictures; The passing status of railway freight cars is determined based on the comparison results.

2. A method for automatically checking and providing cluster identification for railway freight car messages and pictures as claimed in claim 1, characterized in that: Comparison with the number of scheduled vehicle images includes: The number of vehicle passing pictures is compared with the predetermined number of vehicle passing pictures according to the work station code.

3. A method for automatically checking and providing cluster identification for railway freight car messages and pictures as claimed in claim 2, characterized in that: The railway freight car passing status is determined based on the comparison results, including: When the number of passing pictures reaches a predetermined number of passing pictures, the railway freight car passing message and passing pictures are stored, and the railway freight car passing status is updated to passing completed.

4. A method for automatically checking and providing cluster identification for railway freight car messages and pictures as claimed in claim 3, characterized in that: The railway freight car passing status is determined based on the comparison results, including: When the number of passing pictures corresponding to the workstation codes is equal to the predetermined number of passing pictures, it is determined that the passing status of the railway freight car is completed.

5. A method for automatically checking and providing cluster identification for railway freight car messages and pictures as claimed in claim 4, characterized in that: Also includes: When the number of passing pictures corresponding to any of the workstation codes is less than the predetermined number of passing pictures, it is determined that the passing status of the railway freight car is not completed.

6. A method for automatically checking railway freight car messages and pictures and providing cluster identification as claimed in any one of claims 2 to 5, characterized in that: Parsing the railway freight car passing message to obtain the passing status includes: Parsing the railway freight car passing message; The train receiving status in the train message content in the railway freight train passing message is used as the train passing status.

7. A method for automatically checking railway freight car messages and pictures and providing cluster identification as claimed in any one of claims 2 to 5, characterized in that: Parsing the railway freight car passing message to obtain the passing status includes: Parsing the railway freight car passing message; Querying the number of vehicles and the number of vehicle messages in the train message content in the railway freight car passing message; The vehicle passing status is determined according to the number of vehicles and the number of vehicle messages.

8. A method for automatically checking railway freight car messages and pictures and providing cluster identification as claimed in any one of claims 2 to 5, characterized in that: After updating the railway freight car passing status to passing completed, it also includes: The railway freight car passing message and passing picture are provided to the image recognition cluster of the railway freight car fault image detection system.

9. A method for automatically checking railway freight car messages and pictures and providing cluster identification as claimed in claim 8, characterized in that: Providing the railway freight car passing message and passing picture to the image recognition cluster of the railway freight car fault image detection system includes: Providing the railway freight car passing message to the image recognition cluster through a secure encryption interface; The image recognition cluster is provided with the passing vehicle picture by means of Nginx reverse proxy.

10. A device for automatically checking railway freight car messages and pictures and providing cluster identification, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

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