Signal system monitoring data management method and device and computer storage medium

Abstract

The invention provides a signal system monitoring data management method and device and a computer storage medium. The method comprises the following steps: establishing an equipment model, and setting equipment information and associated information thereof; acquiring equipment original monitoring data of each subsystem of the signal system; based on the equipment model, performing modeling processing on the original monitoring data of the equipment to generate modeling monitoring data; and managing the modeling monitoring data of each subsystem device of the signal system based on the modeling monitoring data. According to the invention, the problem of data inconsistency among the subsystems of the signal system can be solved, data islands among the subsystems are broken, a unified real-time data management method is provided, and a good basis is provided for realizing intelligent operation and maintenance of signals.

Description

Technical Field

[0001] This invention belongs to the field of subway signal monitoring technology, specifically relating to a signal system monitoring data management method, device, and computer storage medium. Background Technology Faced with continuously increasing passenger flow, ever-rising service requirements, and growing pressure on safety, operation and maintenance, and costs, urban rail transit systems are prompting cities to actively explore new operation and maintenance models. Intelligent signaling operation and maintenance systems are currently a mainstream research direction, and the collection, storage, and transmission of real-time data from the signaling system are the foundation of the entire intelligent signaling operation and maintenance system. The current status of intelligent signaling operation and maintenance systems is as follows: 1. Different lines and signal systems built at different times are from different manufacturers and have very different data formats. The data are often independent of each other and difficult to interconnect.

[0002] 2. The signal system consists of multiple subsystems, each monitoring different devices and having its own data display requirements. This results in inconsistent data formats between subsystems, making it difficult for data from different subsystems to contribute. Individual development is required to display data from other subsystems. Each subsystem has its own maintenance and monitoring software and its own data management system, making interoperability impossible. Redevelopment is needed for external data, resulting in low scalability. Furthermore, there is often duplication of monitoring data between different subsystems.

[0003] 3. The data collection frequency is high, the data volume is large, and the real-time requirements for the data are very high, so it is necessary to improve the data storage and update efficiency.

[0004] 4. Maintenance personnel often need to switch between different subsystems and log in repeatedly because the main monitoring data types for different subsystem devices are different. Summary of the Invention

[0005] To overcome the aforementioned technical deficiencies, this invention provides a signal system monitoring data management method, device, and computer storage medium, which can solve the problem of data inconsistency between various subsystems of the signal system, break down data silos between subsystems, provide a unified real-time data management method, and provide a good foundation for realizing intelligent signal operation and maintenance.

[0006] This invention is implemented according to the following technical solution: A method for managing monitoring data of a signal system, the method comprising: Establish equipment models and set equipment information and its associated information; Acquire raw monitoring data from equipment in each subsystem of the signal system; Based on the equipment model, the original monitoring data of the equipment is processed into model-based monitoring data. Based on model-based monitoring data, the model-based monitoring data of each subsystem device in the signal system is managed.

[0007] As a further improvement of the present invention, the step of establishing a device model and setting device information and its associated information includes: Define the device models for various devices in the signal system, including static and dynamic attributes of the devices; static attributes include the common attributes of each device; dynamic attributes include the dynamically changing data collected from each device. The equipment type and the equipment model correspond to each other.

[0008] As a further improvement of the present invention, the original monitoring data of each subsystem of the signal acquisition system includes: Based on the different devices in each subsystem of the signal system, collect the original monitoring data of the devices in each subsystem.

[0009] As a further improvement of the present invention, the step of performing modeling processing on the original monitoring data of the equipment based on the equipment model to generate modeled monitoring data includes: Obtain equipment information based on the original monitoring data; Extract the equipment type and static attributes from the equipment information, and obtain the corresponding equipment model based on the equipment type; Based on the equipment model, relevant data are extracted from the original monitoring data and dynamic attributes of the equipment are generated. The static attributes of the equipment extracted from the equipment information are combined with the dynamic attributes of the equipment generated based on the equipment model to obtain model-based monitoring data.

[0010] As a further improvement of the present invention, the management of model-based monitoring data for each subsystem device of the signal system includes: Receive the processed model-based monitoring data, use the device's static attributes as the unique label for the model-based monitoring data, and cache the model-based monitoring data in the memory; After receiving modeled monitoring data of the same device's static attributes, the system searches for the corresponding modeled monitoring data in the memory and updates the data in the cache according to the data time. If no modeled monitoring data of the same static attributes of the device is received after the timeout, the corresponding modeled monitoring data in the memory is cleared. When a data request is received from the display terminal, the corresponding modeled monitoring data is searched in the memory based on the static attributes of the device in the data request and returned to the display terminal at regular intervals.

[0011] As a further improvement of the present invention, the present invention also includes: a model-based monitoring data lookup algorithm: Upon receiving the device's static attributes, determine whether the static attributes contain a device type; if not, discard the data; if they do, proceed to the next step. Determine if the device's static attributes contain the required content; if not, return to the previous level of data; if the required content is present, proceed to the next step. If all required information is included, the data will be returned if all device static parameters meet the requirements.

[0012] As a further improvement of the present invention, when a data request is received from a display terminal, an optimization algorithm is used to optimize the data request: Iterate through all data requests received at the current moment, merge identical request parameters in the data requests based on the device static attributes in the data requests, and mark the display terminal; Based on the merged request parameters, extract the corresponding model-based monitoring data from the cache; Based on the device's static attributes in the data request, the corresponding modeled monitoring data is returned to the labeled display terminal.

[0013] The present invention also provides a real-time data management system for a signal system, characterized in that it includes the following components for implementing the above-mentioned signal system monitoring data management method: Equipment Model Management Module: Used to manage the equipment models of monitored equipment in the system; Equipment Management Module: Used to manage the basic information of all monitored equipment in the system; Subsystem Interface Module: Used to collect raw monitoring data from equipment in various subsystems of the signal system, and to perform modeling processing on the raw monitoring data to obtain modeled monitoring data; Real-time data management module: Used to receive modeled monitoring data processed by the subsystem interface module and manage the modeled monitoring data of the equipment; A database is used to store model-based monitoring data.

[0014] The present invention also provides a signal system monitoring data management device, comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the above-described signal system monitoring data management method.

[0015] The present invention also provides a computer storage medium storing computer instructions, which, when invoked, are used to execute the above-described signal system monitoring data management method.

[0016] Compared with existing technologies, this invention has the following advantages: The signal system monitoring data management method integrates the original monitoring data of all equipment in each subsystem of the signal system into model-based monitoring data. It transforms original monitoring data of different standards and formats into model-based monitoring data. Whether it's line data from different manufacturers or monitoring data from various subsystems within the signal system, all can be processed into unified-format model-based monitoring data through this method. Cross-line and cross-subsystem data interconnection can be achieved without the need for additional adapter interface development, completely solving the data fragmentation problem. Furthermore, model-based data is more compatible with efficient storage solutions, reducing unnecessary redundant data storage. Simultaneously, the management logic based on a unified equipment model simplifies the data update process and avoids inconsistencies in data formats between different subsystems. Attached Figure Description

[0017] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a flowchart of the signal system monitoring data management method described in Example 1; Figure 2 This is a framework diagram of the real-time data management system for the signal system described in Example 2. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The terms "first," "second," etc., in the specification, claims, and the accompanying drawings of the present invention are used to distinguish different objects, not to describe a specific order. In addition, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends. The reference to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0019] Example 1 Please refer to Figure 1, which illustrates a signal system monitoring data management method disclosed in this embodiment. Figure 1 As shown, it includes: S1. Establish the equipment model and set the equipment information and its associated information. Specifically, this includes the following steps: This invention defines device models for various equipment in a signaling system, including static and dynamic attributes. Static attributes include common attributes possessed by each device, i.e., data that does not change over time, such as device type, line, station, device code, and data timeout. Dynamic attributes include dynamically changing data collected from each device, i.e., dynamically changing data such as switch signals, analog signals, and text signals collected from each device. The device models in this invention include: signal controllers, switch machines, power supply panels, batteries, axle counters, environmental sensors, industrial control computers, cameras, and switches. Each device type corresponds to a specific device model, serving as a unique label for the device model.

[0020] S2. Collect raw monitoring data of equipment in each subsystem of the signal system; specifically, collect raw monitoring data of equipment in each subsystem according to the different equipment in each subsystem of the signal system.

[0021] S3. Based on the equipment model, perform modeling processing on the raw equipment monitoring data to generate modeled monitoring data, including: S31. Obtain equipment information based on the original monitoring data.

[0022] S32. Extract the equipment type and static attributes from the equipment information, and obtain the corresponding equipment model based on the equipment type.

[0023] S33. Based on the equipment model, extract relevant data from the original monitoring data and generate dynamic attributes of the equipment.

[0024] S34. Combine the static attributes of the equipment extracted from the equipment information with the dynamic attributes of the equipment generated based on the equipment model to obtain model-based monitoring data.

[0025] S4. Based on model-based monitoring data, manage the model-based monitoring data of each subsystem device in the signal system, and clear the model-based monitoring data when it times out; when a data request is received, process the data request and return the requested data. Specifically, this includes: S41. Receive the processed modeled monitoring data, use the device static attributes as the unique label of the modeled monitoring data, and cache the modeled monitoring data in the memory.

[0026] S42. After receiving the modeled monitoring data of the same device static attributes, search for the corresponding modeled monitoring data in the memory and update the data in the cache according to the data time.

[0027] S43. If no modeled monitoring data of the same device static attributes is received after the timeout, clear the corresponding modeled monitoring data in the memory.

[0028] S44. When a data request is received from the display terminal, the corresponding modeled monitoring data is searched in the memory according to the static attributes of the device in the data request and returned to the display terminal at regular intervals.

[0029] To optimize the handling of large numbers of data requests, as one implementation method, when a data request is received from the display terminal, an optimization algorithm is used to optimize the data request: S441. Traverse all data requests received at the current moment, merge identical request parameters in the data requests according to the device static attributes in the data requests, and mark the display terminal.

[0030] S442. Based on the merged request parameters, extract the corresponding modeled monitoring data from the cache.

[0031] S443. Based on the device static attributes in the data request, return the corresponding modeled monitoring data to the labeled display terminal.

[0032] To improve the efficiency of searching for large amounts of model-based monitoring data in the cache, one implementation method is to use a model-based monitoring data search algorithm. This algorithm includes: S101. Upon receiving the device static attributes, determine whether the device static attributes contain a device type; if not, discard the data; if so, proceed to the next step of processing.

[0033] S102. Determine whether the device's static attributes contain the required content; if not, return to the previous level of data; if the required content is contained, proceed to the next step of processing.

[0034] S103. If all required information is included, return data that meets all device static parameters simultaneously.

[0035] In the specific implementation process, if the received static attributes of the equipment include equipment type, then it is further determined whether the static attributes of the equipment include route. If the route is not included, then all static parameters of the equipment that meet the equipment type condition are returned. If the route is included, then it is further determined whether the static attributes of the equipment include station. If the station is not included, then all static parameters of the equipment that meet both equipment type and route conditions are returned. If the station is included, then it is further determined whether the static attributes of the equipment include equipment code. If the equipment code is not included, then all static parameters of the equipment that meet both equipment type, route, and station conditions are returned. If the station is included, then all static parameters of the equipment that meet both equipment type, route, station conditions, and equipment code are returned.

[0036] The following explanation will further illustrate the specific implementation process of this embodiment using the interlocking system equipment, signal machines and switch machines, of the signaling systems of Lines 18 and 22 as examples: 1. Establish equipment models and define the dynamic attributes of signal lights, including: signal light color, signal light status, and signal light filament current. Define the dynamic attributes of switch machines, including: switch machine positioning status, switch machine gap value, switch machine housing temperature, and switch machine housing humidity. Save relevant equipment information, including equipment type, track, station, and equipment code.

[0037] 2. Collected raw monitoring data of all signals and switch machines on lines 18 and 22.

[0038] 3. Perform modeling processing on the raw monitoring data to obtain modeled monitoring data: (1) Collect the original monitoring data of the signal machine and switch machine.

[0039] (2) Based on the equipment model and equipment information of the signal and switch machine, the original monitoring data is processed into a model to obtain the model monitoring data of the signal and switch machine.

[0040] (3) Save the model monitoring data of the signal machine and switch machine.

[0041] The modeling methods are as follows: 1) Obtain equipment information for signal lights and switch machines based on the original monitoring data.

[0042] 2) Extract the equipment type and static attributes from the equipment information, and obtain the equipment model of the signal machine and switch machine according to the equipment type.

[0043] 3) Extract the dynamic attributes of the equipment from the original monitoring data based on the equipment models of the signal and switch machines.

[0044] 4) Combine the static attributes of the equipment in 2) with the dynamic attributes of the equipment in 3) to obtain the modeled monitoring data of the signal machine and the switch machine.

[0045] 4. Based on model-based monitoring data, manage the model-based monitoring data of each subsystem device in the signal system; clear the model-based monitoring data when it times out; when a data request is received, process the data request and return the requested data. The main process is as follows: (1) Receive the processed model monitoring data, use the static attributes of the equipment as the unique label of the model monitoring data, and cache the model monitoring data in the memory.

[0046] (2) After receiving the modeled monitoring data of the same static attributes of the device, search for the corresponding modeled monitoring data in the memory and update the data in the cache according to the data time.

[0047] (3) If no modeled monitoring data of the same static attributes of the device is received after the timeout, the corresponding modeled monitoring data in the memory is cleared.

[0048] (4) When a data request is received from the display terminal, the corresponding modeled monitoring data is searched in the memory according to the static attributes of the device in the data request and returned to the display terminal at regular intervals.

[0049] 5. Based on the data request, the display terminal displays the device model data.

[0050] The signal system monitoring data management method in this embodiment integrates the raw monitoring data of all equipment in each subsystem of the signal system into model-based monitoring data. It transforms raw monitoring data of different standards and formats into model-based monitoring data. Whether it's line data from different manufacturers or monitoring data from various subsystems within the signal system, all can be processed into unified-format model-based monitoring data through this method. This achieves cross-line and cross-subsystem data interconnection and interoperability without the need for additional adapter interface development, completely solving the data fragmentation problem. Furthermore, model-based data is more compatible with efficient storage solutions, reducing unnecessary redundant data storage. Simultaneously, the management logic based on a unified equipment model simplifies the data update process and avoids inconsistencies in data formats between different subsystems.

[0051] Example 2 Please see Figure 2This embodiment discloses a real-time data management system for a signal system, comprising: a device model management module, a device management module, a subsystem interface module, a real-time data management module, and a database. The device model management module manages the device models of the monitored devices within the system; the device management module manages the basic information of all monitored devices within the system; the subsystem interface module collects raw monitoring data from various subsystems of the signal system and performs modeling processing on the raw monitoring data to obtain modeled monitoring data; the real-time data management module receives the modeled monitoring data processed by the subsystem interface module and manages the modeled monitoring data of the devices; and the database stores the modeled monitoring data.

[0052] Furthermore, the equipment model management module is used to define equipment models for various types of equipment in the signaling system, including static and dynamic attributes. Static attributes include common attributes possessed by each device, i.e., data that does not change over time, such as equipment type, line, station, equipment code, and data timeout. Dynamic attributes include dynamically changing data collected from each device, i.e., dynamically changing data such as switch signals, analog signals, and text signals collected from each device. The equipment models in this invention include: signal controllers, switch machines, power supply panels, batteries, axle counters, environmental sensors, industrial control computers, cameras, and switches. Equipment types correspond to equipment models and serve as unique labels for each equipment model.

[0053] The subsystem interface module acquires equipment information from the raw monitoring data, extracts the equipment type and static attributes from the equipment information, and obtains the corresponding equipment model based on the equipment type. Based on the equipment model, the subsystem interface module extracts relevant data from the raw monitoring data and generates dynamic attributes for the equipment. The subsystem interface module combines the static attributes extracted from the equipment information with the dynamic attributes generated from the equipment model to obtain model-based monitoring data.

[0054] The real-time data management module receives processed modeled monitoring data, uses device static attributes as unique tags for the modeled monitoring data, and caches the modeled monitoring data in memory. Upon receiving modeled monitoring data with the same device static attributes, the real-time data management module searches for the corresponding modeled monitoring data in memory and updates the cached data according to the data time. If no modeled monitoring data with the same device static attributes is received after a timeout, the real-time data management module clears the corresponding modeled monitoring data from memory. When the real-time data management module receives a data request from the display terminal, it searches for the corresponding modeled monitoring data in memory based on the device static attributes in the data request and periodically returns it to the display terminal.

[0055] To optimize the handling of large numbers of data requests, as one implementation method, the real-time data management module uses an optimization algorithm to optimize the data requests received from the display terminal: The real-time data management module iterates through all data requests received at the current moment, merges identical request parameters in the data requests based on the device static attributes in the data requests, and marks the display terminal.

[0056] The real-time data management module extracts the corresponding modeled monitoring data from the cache based on the merged request parameters.

[0057] The real-time data management module returns the corresponding modeled monitoring data to the labeled display terminal based on the static attributes of the device in the data request.

[0058] To improve the efficiency of searching for large amounts of model-based monitoring data in the cache, as one implementation method, the real-time data management module can search for the corresponding model-based monitoring data using a model-based monitoring data search algorithm. This algorithm includes: The real-time data management module receives the device's static attributes and determines whether the static attributes contain the device type. If not, the data is discarded; if it does, the process proceeds to the next step.

[0059] The real-time data management module determines whether the device's static attributes contain the required content; if not, it returns to the previous level of data; if the required content is included, it proceeds to the next step of processing.

[0060] If all required information is included, the real-time data management module returns data that meets the static parameters of all devices simultaneously.

[0061] In the specific implementation process, if the static attributes of the equipment received by the real-time data management module include equipment type, it further determines whether the static attributes of the equipment include route. If it does not include route, the real-time data management module returns data for all static parameters of the equipment that meet the equipment type condition. If it does include route, the real-time data management module further determines whether the static attributes of the equipment include station. If it does not include station, the real-time data management module returns data for all static parameters of the equipment that simultaneously meet the equipment type and route conditions. If it includes station, the real-time data management module further determines whether the static attributes of the equipment include equipment code. If it does not include equipment code, the real-time data management module returns data for all static parameters of the equipment that simultaneously meet the equipment type, route, and station conditions. If it includes station, the real-time data management module returns data for all static parameters of the equipment that simultaneously meet the equipment type, route, station conditions, and equipment code.

[0062] The following explanation will further illustrate the specific implementation process of this embodiment using the interlocking system equipment, signal machines and switch machines, of the signaling systems of Lines 18 and 22 as examples: 1. Establish equipment models and define the dynamic attributes of signal lights through the equipment model management module, including: signal light color, signal light status, and signal light filament current. Define the dynamic attributes of switch machines, including: switch machine positioning status, switch machine gap value, switch machine housing temperature, and switch machine housing humidity. Enter relevant equipment information through the equipment model management module, including equipment type, track, station, and equipment code.

[0063] 2. The subsystem interface module collects the raw monitoring data of all signals and switch machines on lines 18 and 22.

[0064] 3. The subsystem interface module performs modeling processing on the raw monitoring data to obtain modeled monitoring data: (1) Collect the original monitoring data of the signal machine and switch machine.

[0065] (2) Based on the equipment model and equipment information of the signal and switch machine, the original monitoring data is processed into a model to obtain the model monitoring data of the signal and switch machine.

[0066] (3) Save the modeled monitoring data of the signal and switch machine to the database and send it to the real-time data management module.

[0067] The modeling methods are as follows: 1) The subsystem interface module obtains equipment information of signal machines and switch machines based on the original monitoring data.

[0068] 2) The subsystem interface module extracts the equipment type and static attributes from the equipment information, and obtains the equipment model of the signal machine and switch machine according to the equipment type.

[0069] 3) The subsystem interface module extracts the dynamic attributes of the equipment from the original monitoring data based on the equipment models of the signal and switch machines.

[0070] 4) The subsystem interface module combines the static attributes of the equipment in 2) with the dynamic attributes of the equipment in 3) to obtain the modeled monitoring data of the signal and switch machine.

[0071] 4. The real-time data management module manages the model-based monitoring data of each subsystem device in the signal system; it clears the model-based monitoring data when it times out; and when a data request is received, it processes the request and returns the requested data. Its main process is as follows: (1) The real-time data management module receives the processed modeled monitoring data, uses the static attributes of the equipment as the unique label of the modeled monitoring data, and caches the modeled monitoring data in the memory.

[0072] (2) After receiving the modeled monitoring data of the same static attributes of the device, the real-time data management module searches for the corresponding modeled monitoring data in the memory and updates the data in the cache according to the data time.

[0073] (3) When the real-time data management module does not receive modeled monitoring data of the same static attributes of the device after the timeout, it clears the corresponding modeled monitoring data in the memory.

[0074] (4) When the real-time data management module receives a data request from the display terminal, it searches for the corresponding modeled monitoring data in the memory based on the static attributes of the device in the data request and returns it to the display terminal at regular intervals.

[0075] 5. The display terminal establishes a long connection with the real-time data management system of the signal system via WebSocket, and subscribes to the real-time data management module. The subscription request requires the equipment model data of all signal equipment of Line 18 and Shaxi Station, and the subscription period is 1000 milliseconds.

[0076] 6. The real-time data management module filters out real-time data from Line 18, Shaxi Station, and signal types, and continuously sends equipment model data to the display terminal at 1000 millisecond intervals.

[0077] The real-time data management system for the signal system in this embodiment can realize unified management of data from various subsystems. The original monitoring data of the equipment in each subsystem of the signal system are integrated into model-based monitoring data and stored in the real-time data management system. Maintenance personnel do not need to switch between multiple subsystems. They can log in once and retrieve the model-based monitoring data of different subsystems as needed, avoiding repeated login and system switching operations, significantly reducing the complexity of maintenance operations and improving maintenance efficiency.

[0078] Example 3 This embodiment provides a signal system monitoring data management device, including: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the signal system monitoring data management method described in Embodiment 1.

[0079] Example 4 This embodiment provides a computer storage medium that stores computer instructions. When the computer instructions are invoked, they are used to execute the signal system monitoring data management method described in Embodiment 1.

[0080] Optionally, the computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), solid-state drives (SSDs), or optical discs, etc. The random access memory may include resistive random access memory (ReRAM) and dynamic random access memory (DRAM).

[0081] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Therefore, any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for managing monitoring data of a signal system, characterized in that, The method includes: Establish equipment models and set equipment information and its associated information; Acquire raw monitoring data from equipment in each subsystem of the signal system; Based on the equipment model, the original monitoring data of the equipment is processed into model-based monitoring data. Based on model-based monitoring data, the model-based monitoring data of each subsystem device in the signal system is managed.

2. The signal system monitoring data management method according to claim 1, characterized in that, The process of establishing a device model and setting device information and its associated information includes: Define the device models for various devices in the signal system, including static and dynamic attributes of the devices; static attributes include the common attributes of each device; dynamic attributes include the dynamically changing data collected from each device. The equipment type and the equipment model correspond to each other.

3. The signal system monitoring data management method according to claim 1, characterized in that, The raw monitoring data of each subsystem of the signal acquisition system includes: Based on the different devices in each subsystem of the signal system, collect the original monitoring data of the devices in each subsystem.

4. The signal system monitoring data management method according to claim 1, characterized in that, The process of modeling the raw equipment monitoring data based on the equipment model to generate model-based monitoring data includes: Obtain equipment information based on the original monitoring data; Extract the equipment type and static attributes from the equipment information, and obtain the corresponding equipment model based on the equipment type; Based on the equipment model, relevant data are extracted from the original monitoring data and dynamic attributes of the equipment are generated. The static attributes of the equipment extracted from the equipment information are combined with the dynamic attributes of the equipment generated based on the equipment model to obtain model-based monitoring data.

5. The signal system monitoring data management method according to claim 4, characterized in that, The management of model-based monitoring data for each subsystem of the signal system includes: Receive the processed model-based monitoring data, use the device's static attributes as the unique label for the model-based monitoring data, and cache the model-based monitoring data in the memory; After receiving modeled monitoring data of the same device's static attributes, the system searches for the corresponding modeled monitoring data in the memory and updates the data in the cache according to the data time. If no modeled monitoring data of the same static attributes of the device is received after the timeout, the corresponding modeled monitoring data in the memory is cleared. When a data request is received from the display terminal, the corresponding modeled monitoring data is searched in the memory based on the static attributes of the device in the data request and returned to the display terminal at regular intervals.

6. The signal system monitoring data management method according to claim 5, characterized in that, Also includes: Model-based monitoring data lookup algorithm: Upon receiving the device's static attributes, determine whether the static attributes contain a device type; if not, discard the data; if they do, proceed to the next step. Determine if the device's static attributes contain the required content; if not, return to the previous level of data; if the required content is present, proceed to the next step. If all required information is included, the data will be returned if all device static parameters meet the requirements.

7. The signal system monitoring data management method according to claim 5, characterized in that, Upon receiving a data request from the display terminal, an optimization algorithm is used to optimize the data request: Iterate through all data requests received at the current moment, merge identical request parameters in the data requests based on the device static attributes in the data requests, and mark the display terminal; Based on the merged request parameters, extract the corresponding model-based monitoring data from the cache; Based on the device's static attributes in the data request, the corresponding modeled monitoring data is returned to the labeled display terminal.

8. A real-time data management system for a signal system, characterized in that, A method for managing signal system monitoring data as claimed in any one of claims 1 to 7, comprising: Equipment Model Management Module: Used to manage the equipment models of monitored equipment in the system; Equipment Management Module: Used to manage the basic information of all monitored equipment in the system; Subsystem Interface Module: Used to collect raw monitoring data from equipment in various subsystems of the signal system, and to perform modeling processing on the raw monitoring data to obtain modeled monitoring data; Real-time data management module: Used to receive modeled monitoring data processed by the subsystem interface module and manage the modeled monitoring data of the equipment; A database is used to store model-based monitoring data.

9. A signal system monitoring data management device, characterized in that, include: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the signal system monitoring data management method as described in any one of claims 1-8.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the signal system monitoring data management method as described in any one of claims 1-8.

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