Urban rail intelligent operation and maintenance management method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of rail transit, and particularly discloses an urban rail intelligent operation and maintenance management method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining target alarm information of any subsystem monitored by an urban rail intelligent operation and maintenance system, and judging whether the target alarm information has a matched target fault model or not; and if the target alarm information has the matched target fault model, calling the target fault model to analyze the target alarm information to obtain a target diagnosis result. According to the invention, real-time automatic diagnosis of faults in the intelligent operation and maintenance process of the urban rail can be realized, and the efficiency of intelligent operation and maintenance management of the urban rail is improved while the labor cost is reduced.

Description

Background Art

[0002] The urban rail intelligent operation and maintenance system consists of various subsystems such as automatic train monitoring (ATS), vehicle-mounted controller (VOBC), zone controller (ZC), and computer interlocking (CI). The urban rail intelligent operation and maintenance system is an important system for realizing the modern operation and command of rail transit. As the intelligent brain of rail transit, it is a strong guarantee for the safe and efficient operation of trains. With the evolution of the urban rail intelligent operation and maintenance system, a large number of lines are currently built in accordance with GoA4 level. Urban rail transit continues to develop in the direction of automation and intelligence. Of course, the importance of its stable operation is constantly highlighted. How to ensure the reliable operation of equipment on track and quickly and promptly handle faults and restore operations has become a key issue.

[0003] The traditional maintenance method of urban rail intelligent operation and maintenance system mainly relies on the work experience of engineering and technical personnel. On the one hand, the process of carrying out regular maintenance work is somewhat blind, and it is impossible to quickly and effectively locate faulty equipment. Large-scale equipment maintenance will waste a lot of manpower, material and financial resources, and consume a lot of time costs; on the other hand, when a fault occurs suddenly, from receiving the report to on-site investigation, to formulating emergency plans and implementing equipment maintenance, it will consume a lot of time, which will inevitably affect the normal operation of the line.

[0004] Therefore, it is urgent to provide a technical solution to solve the above problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method, device, electronic equipment and storage medium for intelligent operation and maintenance management of urban rail.

[0006] In a first aspect, the present invention provides an urban rail intelligent operation and maintenance management method, the technical solution of the method is as follows:

[0007] Obtain target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information;

[0008] If there is a matching target fault model for the target alarm information, the target fault model is called to analyze the target alarm information to obtain a target diagnosis result.

[0009] The beneficial effects of the urban rail intelligent operation and maintenance management method of the present invention are as follows:

[0010] The method of the present invention can realize real-time automatic diagnosis of faults in the process of urban rail intelligent operation and maintenance, thereby reducing labor costs and improving the efficiency of urban rail intelligent operation and maintenance management.

[0011] On the basis of the above scheme, the urban rail intelligent operation and maintenance management method of the present invention can also be improved as follows.

[0012] In an optional manner, the step of obtaining target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system includes:

[0013] The target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system is obtained from the kafka database.

[0014] In an optional manner, the step of determining whether the target alarm information has a matching target fault model includes:

[0015] Based on the mapping relationship between the alarm information and the fault model, determining whether the target alarm information has a corresponding fault model, and obtaining a first determination result;

[0016] If the first judgment result is yes, then judging whether the duration of the target alarm information reaches a threshold value, and obtaining a second judgment result;

[0017] If the second judgment result is yes, it is determined that the target alarm information has a matching target fault model.

[0018] In an optional manner, the step of determining whether the target alarm information has a matching target fault model further includes:

[0019] If the first judgment result is no, determining that the target alarm information does not have a matching target fault model;

[0020] If the second judgment result is no, the preset time interval is used to re-judge whether the duration of the target alarm information reaches the threshold; until the duration is reached, it is determined that the target alarm information has a matching target fault model, or, when the duration is not reached, the target alarm information is invalid, and it is determined that the target alarm information does not have a matching target fault model.

[0021] In an optional manner, the step of calling the target fault model to analyze the target alarm information to obtain a target diagnosis result includes:

[0022] The alarm information and equipment status information of the subsystem of the urban rail intelligent operation and maintenance system corresponding to the target alarm information are obtained from the Elasticsearch database, and the model code of the target fault model is combined for analysis and calculation to obtain the target diagnosis result.

[0023] In an optional manner, the method further includes:

[0024] The target diagnosis result is stored in the Elasticsearch database, so that the urban rail intelligent operation and maintenance system obtains the target diagnosis result from the Elasticsearch database and outputs it for display.

[0025] In a second aspect, the present invention provides an urban rail intelligent operation and maintenance management device, the technical solution of the device is as follows:

[0026] Includes: processing module and operation module;

[0027] The processing module is used to: obtain target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information;

[0028] The operation module is used for: if there is a matching target fault model for the target alarm information, calling the target fault model to analyze the target alarm information to obtain a target diagnosis result.

[0029] The beneficial effects of the urban rail intelligent operation and maintenance management device of the present invention are as follows:

[0030] The device of the present invention can realize real-time automatic diagnosis of faults in the process of urban rail intelligent operation and maintenance, thereby reducing labor costs and improving the efficiency of urban rail intelligent operation and maintenance management.

[0031] On the basis of the above scheme, the urban rail intelligent operation and maintenance management device of the present invention can also be improved as follows.

[0032] In an optional manner, the processing module is specifically used to:

[0033] The target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system is obtained from the kafka database.

[0034] In a third aspect, a technical solution of an electronic device of the present invention is as follows:

[0035] The method comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps of the urban rail intelligent operation and maintenance management method of the present invention are implemented.

[0036] In a fourth aspect, the present invention provides a computer-readable storage medium having the following technical solution:

[0037] Instructions are stored in the computer-readable storage medium. When the computer-readable storage medium reads the instructions, the computer-readable storage medium executes the steps of the urban rail intelligent operation and maintenance management method of the present invention.

[0038] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0040] Figure 1 A schematic diagram of a flow chart of a first embodiment of an urban rail intelligent operation and maintenance management method of the present invention;

[0041] Figure 2 This is the basic architecture diagram of the management platform system;

[0042] Figure 3 It is a schematic diagram of the configuration file of the fault model;

[0043] Figure 4 This is a schematic diagram of the principle of subpackaging tasks in DAG1;

[0044] Figure 5 It is a data structure diagram of target alarm information;

[0045] Figure 6 A schematic diagram of the structure of an embodiment of an urban rail intelligent operation and maintenance management device of the present invention;

[0046] Figure 7 The figure is a schematic structural diagram of an embodiment of an electronic device of the present invention. DETAILED DESCRIPTION

[0047] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0048] Figure 1A flow chart of the first embodiment of an intelligent operation and maintenance management method for urban rail provided by the present invention is shown, and the intelligent operation and maintenance management method for urban rail can be executed by electronic devices such as terminal devices or servers. Among them, the terminal device can be any fixed or mobile terminal such as user equipment (User Equipment, UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (Personal Digital Assistant, PDA), handheld device, computing device, vehicle-mounted device, wearable device, etc. The server can be a single server or a server cluster composed of multiple servers. Any electronic device can implement the intelligent operation and maintenance management method for urban rail by calling computer-readable instructions stored in a memory through a processor. Figure 1 As shown, the following steps are included:

[0049] S1. Obtain target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information.

[0050] Among them, the urban rail intelligent operation and maintenance system includes multiple subsystems: automatic train monitoring (ATS), vehicle-mounted controller (VOBC), zone controller (ZC), computer interlocking (CI), etc. The target alarm information is the alarm information currently obtained from the kafka database.

[0051] In S1, specifically:

[0052] 1) Obtain the target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system from the Kafka database.

[0053] Among them, multiple alarm information can be stored in the Kafka database and arranged in chronological order.

[0054] 2) The step of determining whether the target alarm information has a matching target fault model comprises:

[0055] Based on the mapping relationship between the alarm information and the fault model, it is determined whether the target alarm information has a corresponding fault model to obtain a first determination result.

[0056] Among them, different alarm information corresponds to a fault model respectively.

[0057] If the first judgment result is yes, it is determined whether the duration of the target alarm information reaches a threshold to obtain a second judgment result.

[0058] The default threshold of duration is 10S, which can be adjusted according to actual conditions and is not limited here.

[0059] If the second judgment result is yes, it is determined that the target alarm information has a matching target fault model.

[0060] 3) The step of determining whether the target alarm information has a matching target fault model further includes:

[0061] If the first judgment result is no, determining that the target alarm information does not have a matching target fault model;

[0062] If the second judgment result is no, the preset time interval is used to re-judge whether the duration of the target alarm information reaches the threshold; until the duration is reached, it is determined that the target alarm information has a matching target fault model, or, when the duration is not reached, the target alarm information is invalid, and it is determined that the target alarm information does not have a matching target fault model.

[0063] Among them, the preset duration is 8S by default, and can also be adjusted according to actual conditions. There is no limit here.

[0064] S2. If there is a matching target fault model for the target alarm information, the target fault model is called to analyze the target alarm information to obtain a target diagnosis result.

[0065] Among them, the target diagnosis result is: the diagnosis information and disposal suggestion information corresponding to the target alarm information.

[0066] In S2, specifically:

[0067] The alarm information and equipment status information of the subsystem of the urban rail intelligent operation and maintenance system corresponding to the target alarm information are obtained from the Elasticsearch database, and the model code of the target fault model is combined for analysis and calculation to obtain the target diagnosis result.

[0068] Among them, the Elasticsearch database is used to store the alarm information and equipment status information of each subsystem of the urban rail intelligent operation and maintenance system.

[0069] In an optional manner, the method further includes:

[0070] S3. Store the target diagnosis result in the Elasticsearch database, so that the urban rail intelligent operation and maintenance system obtains the target diagnosis result from the Elasticsearch database and outputs it for display.

[0071] Among them, the target diagnosis results are displayed through the web front-end page of the urban rail intelligent operation and maintenance system.

[0072] The technical solution of this embodiment can realize real-time automatic diagnosis of faults in the process of urban rail intelligent operation and maintenance, thereby reducing labor costs and improving the efficiency of urban rail intelligent operation and maintenance management.

[0073] The present invention provides a second embodiment of an urban rail intelligent operation and maintenance management method, which is executed by a management platform system and includes the following steps:

[0074] Obtain the target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information.

[0075] If there is a matching target fault model for the target alarm information, the target fault model is called to analyze the target alarm information to obtain a target diagnosis result.

[0076] In this embodiment, the following contents need to be explained:

[0077] like Figure 2 As shown in the figure, the management platform system is based on the demand of intelligent operation and maintenance for intelligent algorithm model scheduling, monitoring and management, and is implemented based on the static management component of the Python development model. The management platform system is a programmable scheduling and monitoring workflow platform. Based on the directed acyclic graph (DAG), it can flexibly define dependent task groups. DAG is the core concept. Tasks are loaded into DAG and encapsulated into task dependency chains. DAG determines the execution rules of these tasks. Write DAG task scripts to implement workflow tasks, define the execution time and execution interval of the workflow through the configuration file, and customize the relationship between tasks in the script. In this flexible way, workflow tasks can be scheduled and managed.

[0078] The management platform system is able to handle a variety of complex workflows while maintaining the efficiency and reliability of task execution. Through its comprehensive monitoring and logging functions, it ensures that users can easily manage and audit the entire data processing process. The management platform system has the functions of model management and model scheduling. The management platform system provides a model registration management mechanism. Developers can dynamically develop model script codes based on the requirements and register them to the management platform system in a similar way to configuration files in a specified format. Model registration information includes but is not limited to model name and model version. The management platform system supports dynamic updates of models. The management platform system generates log files to record information such as task scheduling execution records and model execution records.

[0079] Two interdependent task groups DAG1 and DAG2 are designed in the management platform system. The two task groups each encapsulate different tasks, and the tasks within them constitute a task dependency chain. When the DAG task flow is executed, the tasks within it are executed in order according to the fixed execution rules of DAG. At the same time, there is a dependency relationship between the two task groups, that is, the execution of DAG2 depends on the execution result of DAG1.

[0080] Specifically:

[0081] 1) The tasks of subpackaging in DAG1 mainly include:

[0082] ① Obtain the target alarm information of each subsystem (CI, ZC, ATS, VOBC) stored in the urban rail intelligent operation and maintenance system from the Kafka database in real time.

[0083] ② For the acquired target alarm information, the mapping relationship between different alarms of different subsystems and different fault models is realized through the preset configuration file. Figure 3 As shown in the figure, "4:7002" means the subsystem type and alarm subtype code to which the target alarm information belongs, 4 represents computer interlocking (CI), 7002 is the alarm subtype code, the "model" field value is the name of the fault model, such as "Model_Ci_Logic_Down", and the "time" field value is an integer value in seconds, which means that the duration of a target alarm information must reach this value before the fault model needs to be triggered for analysis (some alarms are caused by subsystem instability and will automatically recover soon after they occur, so there is no need for the fault model to be executed for analysis). According to Figure 4 The algorithm flow shown in the figure determines whether a target alarm message needs to trigger a fault model. If it needs to be triggered, the content of this target alarm message and its matching fault model name information are transmitted to the DAG2 task group. It should be noted that Figure 5 A schematic diagram of the data structure of the target alarm information is shown, where id is the unique identifier of a target alarm information, alarm_time is the occurrence time of the target alarm information, recover_time is the recovery time of the target alarm information (recovery means that the fault represented by the alarm has disappeared), alarm_type indicates the subsystem category to which the target alarm information belongs (such as computer interlocking (CI) is 4, ZC subsystem is 3), alarm_subtype indicates the subtype code of the target alarm information, and the alarm_subtype field values ​​of all target alarm information of the same subsystem are inconsistent.

[0084] 2) The tasks encapsulated in DAG2 mainly include:

[0085] ① Model matching. The code of the fault model is a python file, which is placed in the model folder under the same directory as the model scheduling and management platform system software. The DAG2 task group module function will automatically read the python code files of each fault model and obtain the model information, that is, complete the model information registration of each fault model in the DAG2 task flow. After the DAG2 task group receives the fault model information sent by the DAG1 task group, it will match and identify the name of the fault model to be triggered with the names of all registered fault models. After the fault models match, the corresponding fault model code is called to perform analysis and calculation.

[0086] ② Model execution. After the model matching is completed, the DAG2 task group calls the corresponding fault model code for analysis and calculation according to the matched fault model name. The calculation process can obtain the alarm information and equipment status information of each subsystem stored in the urban rail intelligent operation and maintenance system from the Elasticsearch database, comprehensively analyze the cause of the alarm fault that triggers this fault model, and finally give the diagnosis results and disposal suggestions.

[0087] ③ The fault diagnosis results and disposal suggestions given after the model is executed will be stored in the Elasticsearch database in a complete data structure. The output results of all fault models of each subsystem adopt a unified data structure format for acquisition and display by the intelligent operation and maintenance web front-end interface.

[0088] Figure 6 FIG. 2 shows a schematic diagram of the structure of an embodiment of an urban rail intelligent operation and maintenance management device 200 provided by the present invention. Figure 6 As shown, the system 200 includes: a processing module 210 and an operation module 220;

[0089] The processing module 210 is used to: obtain target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information;

[0090] The operation module 220 is used to: if there is a matching target fault model for the target alarm information, call the target fault model to analyze the target alarm information to obtain a target diagnosis result.

[0091] In an optional manner, the processing module 210 is specifically used for:

[0092] The target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system is obtained from the kafka database.

[0093] In an optional manner, the processing module 210 is further configured to:

[0094] Based on the mapping relationship between the alarm information and the fault model, determining whether the target alarm information has a corresponding fault model, and obtaining a first determination result;

[0095] If the first judgment result is yes, then judging whether the duration of the target alarm information reaches a threshold value, and obtaining a second judgment result;

[0096] If the second judgment result is yes, it is determined that the target alarm information has a matching target fault model.

[0097] In an optional manner, the processing module 210 is further configured to:

[0098] If the first judgment result is no, determining that the target alarm information does not have a matching target fault model;

[0099] If the second judgment result is no, the preset time interval is used to re-judge whether the duration of the target alarm information reaches the threshold; until the duration is reached, it is determined that the target alarm information has a matching target fault model, or, when the duration is not reached, the target alarm information is invalid, and it is determined that the target alarm information does not have a matching target fault model.

[0100] In an optional manner, the operation module 220 is specifically used to:

[0101] The alarm information and equipment status information of the subsystem of the urban rail intelligent operation and maintenance system corresponding to the target alarm information are obtained from the Elasticsearch database, and the model code of the target fault model is combined for analysis and calculation to obtain the target diagnosis result.

[0102] In an optional manner, the device further includes: a storage display module; the storage display module is used to:

[0103] The target diagnosis result is stored in the Elasticsearch database, so that the urban rail intelligent operation and maintenance system obtains the target diagnosis result from the Elasticsearch database and outputs it for display.

[0104] The technical solution of this embodiment can realize real-time automatic diagnosis of faults in the process of urban rail intelligent operation and maintenance, thereby reducing labor costs and improving the efficiency of urban rail intelligent operation and maintenance management.

[0105] For the above-mentioned parameters in the urban rail intelligent operation and maintenance management device 200 of this embodiment and the steps for each module to implement the corresponding functions, reference can be made to the parameters and steps in the embodiment of the urban rail intelligent operation and maintenance management method above, and no further details will be given here.

[0106] like Figure 7 As shown, an electronic device 300 of an embodiment of the present invention includes a processor 320, the processor 320 is coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the electronic device 300 implements any of the above-mentioned urban rail intelligent operation and maintenance management methods, specifically:

[0107] The electronic device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein the one or more memories 310 store at least one computer program 330, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the electronic device 300 implements any of the urban rail intelligent operation and maintenance management methods provided in the above embodiments. Of course, the electronic device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output, and the electronic device 300 may also include other components for implementing device functions, which will not be described in detail here.

[0108] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that the computer implements any of the above-mentioned urban rail intelligent operation and maintenance management methods.

[0109] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0110] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes any of the above-mentioned urban rail intelligent operation and maintenance management methods.

[0111] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0112] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0113] Any combination of one or more computer-readable media can be used. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0114] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for intelligent operation and maintenance of urban rail, characterized in that: include: Obtain target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information; If there is a matching target fault model for the target alarm information, the target fault model is called to analyze the target alarm information to obtain a target diagnosis result.

2. The urban rail intelligent operation and maintenance management method according to claim 1 is characterized in that: The steps of obtaining target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system include: The target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system is obtained from the kafka database.

3. The urban rail intelligent operation and maintenance management method according to claim 1 is characterized in that: The step of determining whether the target alarm information has a matching target fault model comprises: Based on the mapping relationship between the alarm information and the fault model, determining whether the target alarm information has a corresponding fault model, and obtaining a first determination result; If the first judgment result is yes, then judging whether the duration of the target alarm information reaches a threshold value, and obtaining a second judgment result; If the second judgment result is yes, it is determined that the target alarm information has a matching target fault model.

4. The urban rail intelligent operation and maintenance management method according to claim 3 is characterized in that: The step of determining whether the target alarm information has a matching target fault model also includes: If the first judgment result is no, determining that the target alarm information does not have a matching target fault model; If the second judgment result is no, the preset time interval is used to re-judge whether the duration of the target alarm information reaches the threshold; until the duration is reached, it is determined that the target alarm information has a matching target fault model, or, when the duration is not reached, the target alarm information is invalid, and it is determined that the target alarm information does not have a matching target fault model.

5. The urban rail intelligent operation and maintenance management method according to any one of claims 1 to 4, characterized in that: The step of calling the target fault model to analyze the target alarm information to obtain a target diagnosis result includes: The alarm information and equipment status information of the subsystem of the urban rail intelligent operation and maintenance system corresponding to the target alarm information are obtained from the Elasticsearch database, and the model code of the target fault model is combined for analysis and calculation to obtain the target diagnosis result.

6. The urban rail intelligent operation and maintenance management method according to claim 5 is characterized in that: Also includes: The target diagnosis result is stored in the Elasticsearch database, so that the urban rail intelligent operation and maintenance system obtains the target diagnosis result from the Elasticsearch database and outputs it for display.

7. An intelligent operation and maintenance management device for urban rail, characterized in that: include: Processing module and operation module; The processing module is used to: obtain target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system, and determine whether there is a matching target fault model for the target alarm information; The operation module is used for: if there is a matching target fault model for the target alarm information, calling the target fault model to analyze the target alarm information to obtain a target diagnosis result.

8. The urban rail intelligent operation and maintenance management device according to claim 7, characterized in that: The processing module is specifically used for: The target alarm information of any subsystem monitored by the urban rail intelligent operation and maintenance system is obtained from the kafka database.

9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the electronic device implements the urban rail intelligent operation and maintenance management method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by the processor so that the computer-readable storage medium implements the urban rail intelligent operation and maintenance management method as described in any one of claims 1 to 6.

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