Method, system, device and equipment for evaluating health degree of subway platform door system

Abstract

The invention provides a health degree assessment method, system, device and equipment for a subway platform door system, a station server obtains equipment state data of platform door equipment and sends the equipment state data to a central cloud platform, and collection points corresponding to the equipment state data comprise a DI point and an AI point which are uploaded to the station server after being collected by an Internet of Things equipment sensor; the central cloud platform stores the equipment state data into an IoTDB time sequence database through the central cloud service to obtain target storage data, and the IoTDB time sequence database is a database which uses a time sequence to organize data; target storage data of to-be-evaluated equipment is obtained from the IoTDB time sequence database through the analog input signal server, the health degree result of the to-be-evaluated equipment is determined according to the target storage data of the to-be-evaluated equipment, and the to-be-evaluated equipment is at least one of uplink and downlink platform door equipment. According to the invention, the reliability of health degree evaluation of the subway platform door system is improved.

Description

Technical Field

[0001] This invention relates to the field of rail transit technology, and in particular to a method, system, apparatus and equipment for assessing the health of a subway platform door system. Background Technology

[0002] As a crucial piece of equipment ensuring the safety of subway passengers, the operational health of subway platform screen door systems directly impacts the safety and efficiency of subway operations. Currently, most platform screen door systems rely on periodic inspections and maintenance for health assessments, resulting in low reliability of the assessment results, frequent malfunctions, and high maintenance costs.

[0003] Therefore, improving the reliability of health assessment for subway platform screen door systems has become a pressing technical problem that needs to be solved in the industry. Summary of the Invention

[0004] This invention provides a method, system, apparatus, and equipment for assessing the health of subway platform screen door systems, thereby addressing the shortcomings of low reliability in the assessment results of existing technologies and improving the reliability of health assessment of subway platform screen door systems.

[0005] In a first aspect, the present invention provides a health assessment system for a subway platform screen door system. The system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range from the up and down platform screen door devices. The station server is used to acquire the device status data of the up and down platform screen doors and send the device status data of the up and down platform screen doors to the central cloud platform; the acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points; the device status data of the up and down platform screen doors is acquired by collecting the device status data of the up and down platform screen doors through IoT device sensors and uploading the device status data of the up and down platform screen doors to the station server via the Modbus protocol; The central cloud platform is used to store the device status data of the up and down platform gate devices into the IoTDB time series database through the central cloud service to obtain the target stored data; the IoTDB time series database is a database that uses time series to organize data. The central cloud platform is used to obtain target storage data of the device to be evaluated from the IoTDB time series database through an analog input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices.

[0006] According to the present invention, a health assessment system for a subway platform door system includes the following: DI points: electromagnetic lock status, DCU status, motor status, door status, PEDC status, gap detection status, belt status, limit device status, and battery status; AI points include: motor current, motor speed, motor torque, and door position; the process of acquiring the equipment status data of the up and down platform door devices and sending the equipment status data to the central cloud platform includes: Obtain the equipment status data of the up and down platform screen doors; The equipment status data of the up and down platform screen doors are filtered based on preset data filtering conditions to obtain the filtered equipment status data of the down platform screen door; the preset data filtering conditions are AI points with a KMZ value of 1 when the door is open or a GMZ value of 1 when the door is closed. The filtered device status data is sent to the central cloud platform via gigabit network.

[0007] According to the present invention, a health assessment system for a subway platform door system is provided, wherein the IoTDB time series database is a database that uses time series to organize data, and the time series mainly consists of three main fields: timestamp, device ID, and measurement point value; The process of storing the device status data of the uplink and downlink platform screen doors into the IoTDB time-series database via the central cloud service to obtain the target stored data includes: The device status data of the uplink and downlink platform gate devices is stored in the Redis cache through the central cloud service; The central cloud service stores the device status data of the up and down platform gate devices in the cache according to a custom first data template to obtain the target stored data; the fields of the first data template include: timestamp, station name, device name, point name, point value, and alarm status.

[0008] According to the present invention, a health assessment system for a subway platform door system includes, in which target stored data of the device to be assessed is obtained from the IoTDB time-series database via an analog input signal server, and the health result of the device to be assessed is determined based on the target stored data of the device to be assessed, comprising: The target storage data of the device to be evaluated is obtained from the IoTDB time series database by simulating the input signal server. The analog input signal server determines the measurement curve corresponding to at least one AI point based on the target stored data of the device to be evaluated. Based on the measurement curves corresponding to each AI point and the standard curves corresponding to each AI point, the dynamic time warping (DTW) distance between the measurement curves and the standard curves corresponding to each AI point is determined. The health result of the device to be evaluated is determined based on the dynamic time warping (DTW) distance between the measurement curve and the standard curve corresponding to each AI point.

[0009] According to the health assessment system for a subway platform door system provided by the present invention, the central cloud platform is further used for: When there are multiple devices to be evaluated, the health status of the subway platform door system is determined based on the health status results of each device to be evaluated. The health status results of the subway platform door system are stored in accordance with a custom second data template through the central cloud service; the fields of the second data template include: timestamp, station name, device name, health status and detailed information.

[0010] According to the health assessment system for a subway platform door system provided by the present invention, the central cloud platform is further used for: If an anomaly is found at the DI point of the device under evaluation, an alarm message is generated. The alarm information is distributed through a message queue.

[0011] Secondly, the present invention provides a health assessment method for a subway platform screen door system. This method is applied to a central cloud platform in the health assessment system of the subway platform screen door system. The health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range from the up and down platform screen door devices. The method includes the following steps: The device status data of the up and down platform screen doors is stored in the IoTDB time-series database through the central cloud service to obtain the target stored data. The data collection points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series to organize data. By simulating the input signal server, the target storage data of the device to be evaluated is obtained from the IoTDB time series database, and the health result of the device to be evaluated is determined based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices; Based on the health results of the equipment to be evaluated, the health results of the subway platform door system are determined.

[0012] Thirdly, the present invention also provides a health assessment device for a subway platform screen door system. This device is applied to a central cloud platform in the health assessment system of the subway platform screen door system. The health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range from the up and down platform screen door devices. The device includes the following modules: The storage module is used to store the device status data of the up and down platform screen doors into the IoTDB time-series database via a central cloud service to obtain the target stored data. The acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series data organization. The evaluation module is used to obtain target storage data of the device to be evaluated from the IoTDB time series database through a simulated input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; based on the health result of the device to be evaluated, determine the health result of the subway platform door system; the device to be evaluated is at least one of the up and down platform door devices.

[0013] Fourthly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the health assessment method for any of the subway platform door systems described above.

[0014] Fifthly, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the health assessment method for a subway platform door system as described above.

[0015] Sixthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements a health assessment method for any of the subway platform door systems described above.

[0016] This invention provides a method, system, device, and equipment for health assessment of a subway platform screen door system. The health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server deployed within a preset range of the up and down platform screen door devices. The station server acquires device status data from the up and down platform screen door devices and sends this data to the central cloud platform. The data acquisition points corresponding to the device status data include digital input signal (DI) points and analog input signal (AI) points. The device status data is obtained through IoT devices. Sensors collect equipment status data of the up and down platform screen doors and upload this data to the station server via the Modbus protocol. The central cloud platform first stores the equipment status data of the up and down platform screen doors into the IoTDB time-series database through the central cloud service to obtain target storage data. The IoTDB time-series database is a database that uses time series to organize data. Then, through an analog input signal server, the target storage data of the device to be evaluated is obtained from the IoTDB time-series database, and the health result of the device to be evaluated is determined based on the target storage data of the device to be evaluated. The device to be evaluated is at least one of the up and down platform screen doors.

[0017] This invention employs a cloud-edge-device collaborative approach to achieve data acquisition and processing. The acquisition points corresponding to the equipment status data of the up and down platform screen door devices include digital input signal (DI) points and analog input signal (AI) points. The central cloud platform stores the equipment status data in the IoTDB time-series database, which is a database that uses time series to organize data. Then, the target storage data of the device to be evaluated is obtained from the IoTDB time-series database, and the health result of the device to be evaluated is determined based on the target storage data. This invention improves the reliability of health assessment of subway platform screen door systems. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1This is a schematic diagram of the health assessment system for subway platform door systems provided by the present invention.

[0020] Figure 2 This is a flowchart illustrating the health assessment method for a subway platform door system provided by the present invention.

[0021] Figure 3 This is a schematic diagram of the health assessment device for a subway platform door system provided by the present invention.

[0022] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0024] The following is combined Figures 1-4 This invention describes a method, system, apparatus, and device for assessing the health of a subway platform door system.

[0025] Figure 1 This is a schematic diagram of the health assessment system for subway platform door systems provided by the present invention, as shown below. Figure 1 As shown, the health assessment system for the subway platform screen door system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the up and down platform screen door devices. The station server is used to acquire the device status data of the up and down platform screen doors and send the device status data of the up and down platform screen doors to the central cloud platform; the acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points; the device status data of the up and down platform screen doors is acquired by collecting the device status data of the up and down platform screen doors through IoT device sensors and uploading the device status data of the up and down platform screen doors to the station server via the Modbus protocol; The central cloud platform is used to store the device status data of the up and down platform gate devices into the IoTDB time series database through the central cloud service to obtain the target stored data; the IoTDB time series database is a database that uses time series to organize data. The central cloud platform is used to obtain target storage data of the device to be evaluated from the IoTDB time series database through an analog input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices.

[0026] Specifically, it should be noted that the subject of this invention is a health assessment system for subway platform screen door systems, used to improve the reliability of health assessment of subway platform screen door systems.

[0027] Among them, such as Figure 1 As shown, the health assessment system for subway platform screen door systems includes platform screen door devices for both directions, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the platform screen door devices for both directions. The functions of each module are as follows: Among them, the up and down platform screen door equipment is the equipment whose health status is to be evaluated. In this embodiment, the data acquisition process first collects the equipment status data of the up and down platform screen door equipment through IoT device sensors. The collection points corresponding to the equipment status data of the up and down platform screen door equipment include digital input signal (DI) points and analog input signal (AI) points. The DI point is a switch input signal used to give a command to the programmable logic controller (PLC) or distributed control system (DCS) to open and close. DI signals are typically used for status display, such as when a circuit breaker is closed, which is displayed as closed on the DCS screen. Examples include the status of electromagnetic locks, Data Collection Units (DCUs), motors, doors, Platform Electrical Door Controllers (PEDCs) for subway platforms, gap detection, belt conveyors, limit switches, and batteries. AI points in a control system refer to analog input signals. AI points receive output signals from analog devices in the field, such as motor current, motor speed, motor torque, and door position. AI modules include thermocouple input modules, resistance temperature detector (RTD) input modules, and transmitter signal input modules; these are collectively referred to as AI input devices or AI modules. Therefore, the output signal of each analog device in the field occupies one AI channel of the AI ​​module.

[0028] In terms of data acquisition, existing technologies only collect DI points (digital points 0 and 1) to reduce storage pressure, and usually do not collect AI points (analog points, such as curves) required for intelligent operation and maintenance. This invention can collect AI points without increasing storage pressure.

[0029] After collecting the equipment status data of the up and down platform screen doors, the equipment status data of the up and down platform screen doors is further uploaded to the station server via the Modbus protocol (collected through a data acquisition IC card).

[0030] Furthermore, after receiving the device status data from the up and down platform screen doors, the station server transmits this data to the central cloud platform via a gigabit network. The central cloud platform is configured with a central cloud service and an AI server, with the central cloud service used for data storage. After collecting AI data points, edge devices such as station servers typically struggle to process the data. Therefore, data analysis needs to be performed at the central location through cloud-edge collaboration. This invention solves the data transmission problem using a gigabit network and configures the AI ​​server at the central location for data analysis.

[0031] Furthermore, the central cloud platform stores the device status data of the uplink and downlink platform gate devices into the IoTDB time series database through the central cloud service, obtaining the target stored data. The IoTDB time series database is a database that uses time series to organize data. IoTDB is an open-source industrial IoT time series database that supports edge-cloud collaboration, employing a lightweight architecture and supporting integrated IoT time series data collection, storage, management, and analysis. It features multi-protocol compatibility, ultra-high compression ratio, high-throughput read / write, industrial-grade stability, and extremely simple operation and maintenance. In the IoTDB time series database, there are no traditional "data tables." Instead, IoTDB uses time series to organize data. A time series is similar to a table in a relational database, but it mainly consists of three fields: timestamp, device ID, and measurement value. To facilitate more detailed descriptions of the device information in the time series, IoTDB also adds extended fields such as Tag and Field. Tag supports indexing, while Field does not. In terms of data storage, the industry typically uses relational databases such as MySQL for storage. However, AI data is characterized by its large volume and strong time correlation, making relational database queries slow and unable to meet engineering requirements.

[0032] Furthermore, the central cloud platform is used to obtain the target storage data of the device to be evaluated from the IoTDB time series database through the analog input signal AI server, and to determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated, wherein the device to be evaluated is at least one of the uplink and downlink platform screen door devices.

[0033] The central cloud platform obtains the target storage data of the device to be evaluated from the IoTDB time-series database through the simulated input signal AI server, which can be achieved through the following steps: 1. Identify Devices and Data Paths: First, you need to determine the identifiers of the devices to be evaluated and their corresponding data paths. In IoTDB, devices are identified by time-series paths, such as root.factory1.d1.temperature.

[0034] 2. Constructing Query Statements: Use SQL statements to query data within a specific time period. For example, if you want to query the temperature data of device d1, you can use the following query statement: SELECT * FROM root.factory1.d1 WHERE time<= 2017-11-01T00:01:00 This query will return all temperature data for device d1 up to the specified time.

[0035] 3. Use the INTO clause: If you need to store the query results to other devices or paths, you can use the INTO clause.

[0036] 4. Align by device: If the query results need to be aligned by device, you can use the ALIGN BY DEVICE clause.

[0037] 5. Execute queries and retrieve results: Execute the above query statements through the IoTDB client or API to retrieve the query results. The results can be real-time data streams or static datasets stored in the database.

[0038] Furthermore, the central cloud platform can use an AI server to determine the health status of the device under evaluation based on its target storage data. For example, it can plot a measurement result curve based on the acquired target storage data of the device under evaluation, and then determine the health status of the device under evaluation based on the measurement result curve and a preset standard curve, thereby achieving reliability assessment.

[0039] The health assessment system for a subway platform screen door system provided in this embodiment includes platform screen door devices for both directions, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the platform screen door devices for both directions. The station server is used to acquire the device status data of the platform screen door devices for both directions and send this data to the central cloud platform. The data collection points corresponding to the device status data of the platform screen door devices include digital input signal (DI) points and analog input signal (AI) points. The device status data of the platform screen door devices is collected by sensors of IoT devices. The system prepares equipment status data and uploads the equipment status data of the up and down platform screen doors to the station server via the Modbus protocol. The central cloud platform first stores the equipment status data of the up and down platform screen doors into the IoTDB time series database through the central cloud service to obtain target storage data. The IoTDB time series database is a database that uses time series to organize data. Then, through the simulated input signal server, the system obtains the target storage data of the device to be evaluated from the IoTDB time series database, and determines the health result of the device to be evaluated based on the target storage data of the device to be evaluated. The device to be evaluated is at least one of the up and down platform screen doors.

[0040] This invention employs a cloud-edge-device collaborative approach to achieve data acquisition and processing. The acquisition points corresponding to the equipment status data of the up and down platform screen door devices include digital input signal (DI) points and analog input signal (AI) points. The central cloud platform stores the equipment status data in the IoTDB time-series database, which is a database that uses time series to organize data. Then, the target storage data of the device to be evaluated is obtained from the IoTDB time-series database, and the health result of the device to be evaluated is determined based on the target storage data. This invention improves the reliability of health assessment of subway platform screen door systems.

[0041] According to the present invention, a health assessment system for a subway platform door system includes the following: DI points: electromagnetic lock status, DCU status, motor status, door status, PEDC status, gap detection status, belt status, limit device status, and battery status; AI points include: motor current, motor speed, motor torque, and door position; the process of acquiring the equipment status data of the up and down platform door devices and sending the equipment status data to the central cloud platform includes: Obtain the equipment status data of the up and down platform screen doors; The equipment status data of the up and down platform screen doors are filtered based on preset data filtering conditions to obtain the filtered equipment status data of the down platform screen door; the preset data filtering conditions are AI points with a KMZ value of 1 when the door is open or a GMZ value of 1 when the door is closed. The filtered device status data is sent to the central cloud platform via gigabit network.

[0042] Specifically, in some embodiments, the DI point includes: electromagnetic lock status, DCU status, motor status, door status, PEDC status, gap detection status, belt status, limit device status, and battery status; the AI ​​point includes: motor current, motor speed, motor torque, and door position. The specific implementation process of the station server obtaining the device status data of the up and down platform screen doors and sending the device status data to the central cloud platform includes: First, acquire the equipment status data of the up and down platform screen doors, for example, by collecting data through a data acquisition IC board.

[0043] Furthermore, based on preset data filtering conditions, the device status data of the up and down platform screen doors are filtered to obtain the filtered device status data of the down platform screen door devices. Specifically, in the IC board section, to reduce network transmission bandwidth consumption, AI points are filtered in the acquisition section. The filtering condition is AI point values ​​with KMZ=1 or GMZ=1 (KMZ: door open, GMZ: door closed, these are two DI points). AI point values ​​for other states are not uploaded. This is because AI points generate a large amount of data during the acquisition process; transmitting all of it would consume a significant amount of bandwidth. Filtering allows only the data from the door opening and closing periods to be transmitted.

[0044] Furthermore, the filtered device status data is sent to the central cloud platform via gigabit network.

[0045] The system provided in this embodiment first obtains the equipment status data of the up and down platform screen door devices, and then filters the AI ​​points collected during the opening and closing of the doors according to preset data filtering conditions. The filtered AI points are then uploaded to the central cloud platform, which can improve the efficiency of effective data transmission and reduce bandwidth usage.

[0046] According to the present invention, a health assessment system for a subway platform door system is provided, wherein the IoTDB time series database is a database that uses time series to organize data, and the time series mainly consists of three main fields: timestamp, device ID, and measurement point value; The process of storing the device status data of the uplink and downlink platform screen doors into the IoTDB time-series database via the central cloud service to obtain the target stored data includes: The device status data of the uplink and downlink platform gate devices is stored in the Redis cache through the central cloud service; The central cloud service stores the device status data of the up and down platform gate devices in the cache according to a custom first data template to obtain the target stored data; the fields of the first data template include: timestamp, station name, device name, point name, point value, and alarm status.

[0047] Specifically, in some embodiments, the IoTDB time series database is a database that uses time series to organize data, wherein the time series mainly consists of three main fields: timestamp, device ID, and measurement value.

[0048] The device status data of the uplink and downlink platform gate devices is stored in the IoTDB time-series database through the central cloud service to obtain the target stored data, including: First, the device status data of the uplink and downlink platform gate devices is stored in a Redis cache via a central cloud service. Redis is an open-source, in-memory data structure store used as a database, cache, message broker, and streaming engine. It is known for its high performance and can act as a network memory cache, reducing access to the backend database and thus improving website response speed. Redis caching principles: 1. Caching mechanism: A cache is a temporary storage space used to store frequently accessed data. In Redis, the caching mechanism is implemented by loading data from slow storage media (such as disk) into fast storage media (such as memory). 2. Data structures: Redis supports various data structures for storing cached data, including strings, hashes, lists, and sets. 3. Cache hit and invalidation policies: A cache hit refers to the process of successfully retrieving data from the cache. A cache invalidation refers to the process of data in the cache becoming invalid or expired. Redis provides various invalidation policies to manage data in the cache.

[0049] Furthermore, the device status data of the uplink and downlink platform gate devices in the cache is stored according to a custom first data template through the central cloud service to obtain the target stored data. The fields of the first data template include: timestamp, station name, device name, point name, point value, and alarm status. For example, all DI points and AI points are stored using IoTDB's custom template 1, which includes: [Time, Station ID, Device ID, Point Name, Point Value, Alarm Status].

[0050] The system provided in this embodiment includes a central cloud service on the central cloud platform that includes a Kafka message queue and a Redis caching service. After the data is processed by the central cloud service, it is stored in the IoTDB time-series database. The AI ​​server can obtain data from the IoTDB and perform analysis to assess the reliability of the subway platform door system.

[0051] According to the present invention, a health assessment system for a subway platform door system includes, in which target stored data of the device to be assessed is obtained from the IoTDB time-series database via an analog input signal server, and the health result of the device to be assessed is determined based on the target stored data of the device to be assessed, comprising: The target storage data of the device to be evaluated is obtained from the IoTDB time series database by simulating the input signal server. The analog input signal server determines the measurement curve corresponding to at least one AI point based on the target stored data of the device to be evaluated. Based on the measurement curves corresponding to each AI point and the standard curves corresponding to each AI point, the dynamic time warping (DTW) distance between the measurement curves and the standard curves corresponding to each AI point is determined. The health result of the device to be evaluated is determined based on the dynamic time warping (DTW) distance between the measurement curve and the standard curve corresponding to each AI point.

[0052] Specifically, in some embodiments, the process by which the central cloud platform acquires data and performs data analysis to obtain the health result of the device to be evaluated includes the following steps: First, the target stored data of the device to be evaluated is obtained from the IoTDB time-series database by simulating an input signal server. For example, a query is executed via the IoTDB client or API to obtain the query results. The results can be a real-time data stream or a static dataset stored in the database. For example, an SQL statement can be used to query data for a specific time period. For instance, if you want to query the temperature data of device d1, you can use the following query: Sql: SELECT*FROM root.factory1.d1 WHERE time<= 2017-11-01T00:01:00 Executing this query will return all temperature data for device d1 up to the specified time.

[0053] Furthermore, by simulating the input signal server, the measurement curve corresponding to at least one AI point is determined based on the target stored data of the device under evaluation. Based on the measurement curves corresponding to each AI point and the corresponding standard curves, the Dynamic Time Warping (DTW) distance between the measurement curves and the standard curves for each AI point is determined. For example, the DTW distance is calculated using the DTW algorithm (Dynamic Time Warping algorithm), and the calculation formula is as follows: This represents the i-th point of the standard curve. The j-th point represents the measurement result. This represents the DTW distance between the two curves.

[0054] Furthermore, the health result of the device under evaluation can be determined based on the Dynamic Time Warped (DTW) distance between the measurement curve and the standard curve corresponding to each AI point. For example, it can be calculated using the following formula: in, For the health of a single device to be evaluated. The DTW distance represents the distance between the two curves. This represents the maximum distance between the measured curve and the standard curve.

[0055] The system provided in this embodiment first obtains the target storage data of the device to be evaluated from the IoTDB time-series database through an AI server, and determines the measurement curve corresponding to at least one AI point based on the target storage data of the device to be evaluated. Then, based on the measurement curves corresponding to each AI point and the standard curves corresponding to each AI point, the dynamic time warping (DTW) distance between the measurement curves corresponding to each AI point and the standard curves is determined. Furthermore, based on the DTW distance between the measurement curves corresponding to each AI point and the standard curves, the health result of the device to be evaluated is determined. This invention can effectively analyze and calculate the health of platform screen doors, providing maintenance personnel with a reference for maintenance.

[0056] According to the health assessment system for a subway platform door system provided by the present invention, the central cloud platform is further used for: When there are multiple devices to be evaluated, the health status of the subway platform door system is determined based on the health status results of each device to be evaluated. The health status results of the subway platform door system are stored in accordance with a custom second data template through the central cloud service; the fields of the second data template include: timestamp, station name, device name, health status and detailed information.

[0057] Specifically, in some embodiments, the central cloud platform is further used for: When there are multiple devices to be evaluated, the health result of the subway platform screen door system is determined based on the health results of each device. For example, a weighted average is used to obtain the overall health result (i.e., the health result of the subway platform screen door system): in, For the health status results of the subway platform door system, For the health results of a single device to be evaluated, The weight is the kth device to be evaluated. The weight is initially set to an average distribution and is subsequently adjusted as the curve deviates. The weight adjustment is based on general knowledge and will not be elaborated here.

[0058] Furthermore, the analysis results can be stored in a time-series database. Specifically, the health status results of the subway platform screen door system can be stored according to a custom second data template via a central cloud service. The fields of the second data template include: timestamp, station name, device name, health status, and detailed information. For example, the health status results obtained after data analysis can be stored using a custom template 2 in IoTDB. Custom template 2 includes: [Time, Station ID, Device ID, Health, Detailed Information].

[0059] The system provided in this embodiment uses a central cloud platform to determine the health status of a subway platform door system based on the health status of each of the multiple devices to be evaluated when there are multiple devices to be evaluated. Then, the central cloud service stores the health status of the subway platform door system according to a custom second data template. The fields of the second data template include: timestamp, station name, device name, health status, and detailed information, which improves the reliability of the health status assessment.

[0060] According to the health assessment system for a subway platform door system provided by the present invention, the central cloud platform is further used for: If an anomaly is found at the DI point of the device under evaluation, an alarm message is generated. The alarm information is distributed through a message queue.

[0061] Specifically, the central cloud service of the central cloud platform also includes a message queue, which is specifically used for: When an anomaly occurs at the DI point of the device under evaluation, an alarm message is generated and stored in the Kafka message queue. Kafka is an open-source distributed event streaming platform widely used for high-performance data pipelines, stream analytics, data integration, and mission-critical applications. Kafka's key features include: 1. Distributed message queue system: Kafka can handle high-throughput data and supports reliable data delivery and asynchronous processing. 2. Persistent storage and fault tolerance: Kafka persistently stores messages on disk, providing high reliability and fault tolerance, ensuring no message loss. 3. Diverse data processing methods: Supports various data processing methods such as stream processing, batch processing, and real-time processing to meet the needs of different business scenarios.

[0062] Then, the alarm information is distributed through a message queue.

[0063] The system provided in this embodiment generates alarm information when there is an anomaly at the DI point of the device to be evaluated, and then distributes the alarm information through a message queue to achieve real-time alarm.

[0064] Figure 2 This is a flowchart illustrating the health assessment method for a subway platform screen door system provided by the present invention. This method is applied to the central cloud platform of the subway platform screen door system's health assessment system. The subway platform screen door system's health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge-side server, which is a server deployed within a preset range from the up and down platform screen door devices. Figure 2 As shown, the method includes the following: Step 201: The device status data of the up and down platform screen doors is stored in the IoTDB time-series database via the central cloud service to obtain the target stored data. The data collection points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent to the central cloud platform by the station server. The IoTDB time-series database is a database that uses time series data organization. Specifically, the IoT sensors of the up and down platform screen doors can be used to collect the device status data of the up and down platform screen doors and upload it to the station server on the edge side. The collection points corresponding to the device status data of the up and down platform screen doors include DI points and AI points.

[0065] Furthermore, the device status data of the uplink and downlink platform gate devices is stored in the IoTDB time-series database through the central cloud service to obtain the target storage data. The IoTDB time-series database is a database that uses time series to organize data. The storage part uses the IoTDB time-series database for storage, which facilitates data processing and analysis, and can also reduce the disk usage of storage.

[0066] Step 202: Obtain the target storage data of the device to be evaluated from the IoTDB time series database through the simulated input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the uplink and downlink platform screen door devices; Specifically, the central cloud platform uses an AI server that simulates input signals to retrieve target storage data of the device to be evaluated from the IoTDB time-series database. Based on this target storage data, the platform determines the health status of the device, where the device to be evaluated is at least one of the uplink or downlink platform screen door devices. For example, the data processing section uses a similarity verification method to compare the measurement curve with a standard curve to obtain the current device health status.

[0067] Step 203: Based on the health results of the equipment to be evaluated, determine the health results of the subway platform door system.

[0068] Specifically, based on the health results of the equipment to be evaluated, the health result of the subway platform screen door system is determined. For example, a weighted average of the health results of different equipment is taken to obtain a comprehensive health score for the subway platform screen door system, thus achieving a reliable health assessment.

[0069] The method provided in this embodiment is applied to the central cloud platform of a subway platform door system health assessment system. The subway platform door system health assessment system includes up and down platform door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the up and down platform door devices. The method includes: firstly, storing the device status data of the up and down platform door devices into an IoTDB time-series database through the central cloud service to obtain target stored data; wherein, the collection points corresponding to the device status data of the up and down platform door devices include digital input signal (DI) points and analog input signal (AI) points, and the device status data of the up and down platform door devices is... The system collects device status data of the up and down platform screen doors via IoT device sensors, and uploads this data to the station server via the Modbus protocol. The station server then sends this data to the central cloud platform. The IoTDB time-series database is a database that organizes data using time series. Further, a simulated input signal server retrieves the target storage data of the device to be evaluated from the IoTDB time-series database, and determines the health result of the device to be evaluated based on this data. The device to be evaluated is at least one of the up and down platform screen doors. Finally, based on the health result of the device to be evaluated, the health result of the subway platform screen door system is determined.

[0070] This invention employs a cloud-edge-device collaborative approach to achieve data acquisition and processing. The acquisition points corresponding to the equipment status data of the up and down platform screen door devices include digital input signal (DI) points and analog input signal (AI) points. The central cloud platform stores the equipment status data in the IoTDB time-series database, which is a database that uses time series to organize data. Then, the target storage data of the device to be evaluated is obtained from the IoTDB time-series database, and the health result of the device to be evaluated is determined based on the target storage data. This invention improves the reliability of health assessment of subway platform screen door systems.

[0071] The following describes the health assessment device for a subway platform door system provided by the present invention. The health assessment device for a subway platform door system described below can be referred to in correspondence with the health assessment method for a subway platform door system described above.

[0072] Figure 3This is a schematic diagram of the health assessment device for a subway platform screen door system provided by the present invention. The health assessment device 300 is applied to the central cloud platform of the subway platform screen door system's health assessment system. The subway platform screen door system's health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range from the up and down platform screen door devices. The subway platform screen door system's health assessment device 300 includes the following modules: Storage module 310 is used to store the device status data of the up and down platform screen doors into the IoTDB time-series database through a central cloud service to obtain target stored data. The acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series data organization. The evaluation module 320 is used to obtain target storage data of the device to be evaluated from the IoTDB time series database through the analog input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; and determine the health result of the subway platform door system based on the health result of the device to be evaluated; the device to be evaluated is at least one of the up and down platform door devices.

[0073] The device provided in this embodiment includes a storage module 310 and an evaluation module 320. The storage module 310 is used to store the device status data of the up and down platform screen doors into the IoTDB time-series database through a central cloud service to obtain target storage data. The acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series to organize data. The evaluation module 320 is used to obtain the target storage data of the device to be evaluated from the IoTDB time-series database through an analog input signal server, and determine the health result of the device to be evaluated based on the target storage data. Based on the health result of the device to be evaluated, the health result of the subway platform screen door system is determined. The device to be evaluated is at least one of the up and down platform screen doors.

[0074] This invention employs a cloud-edge-device collaborative approach to achieve data acquisition and processing. The acquisition points corresponding to the equipment status data of the up and down platform screen door devices include digital input signal (DI) points and analog input signal (AI) points. The central cloud platform stores the equipment status data in the IoTDB time-series database, which is a database that uses time series to organize data. Then, the target storage data of the device to be evaluated is obtained from the IoTDB time-series database, and the health result of the device to be evaluated is determined based on the target storage data. This invention improves the reliability of health assessment of subway platform screen door systems.

[0075] According to the present invention, a health assessment device 300 for a subway platform door system includes the following: DI points include: electromagnetic lock status, DCU status, motor status, door status, PEDC status, gap detection status, belt status, limit device status, and battery status; AI points include: motor current, motor speed, motor torque, and door position; the storage module 310 is specifically used for: Obtain the equipment status data of the up and down platform screen doors; The equipment status data of the up and down platform screen doors are filtered based on preset data filtering conditions to obtain the filtered equipment status data of the down platform screen door; the preset data filtering conditions are AI points with a KMZ value of 1 when the door is open or a GMZ value of 1 when the door is closed. The filtered device status data is sent to the central cloud platform via gigabit network.

[0076] According to the present invention, a health assessment device 300 for a subway platform door system is provided, wherein the IoTDB time series database is a database that uses time series to organize data, and the time series mainly consists of three main fields: timestamp, device ID, and measurement point value. The storage module 310 is further used for: The device status data of the uplink and downlink platform gate devices is stored in the Redis cache through the central cloud service; The central cloud service stores the device status data of the up and down platform gate devices in the cache according to a custom first data template to obtain the target stored data; the fields of the first data template include: timestamp, station name, device name, point name, point value, and alarm status.

[0077] According to the present invention, a health assessment device 300 for a subway platform door system is provided, wherein the assessment module 320 is specifically used for: The target storage data of the device to be evaluated is obtained from the IoTDB time series database by simulating the input signal server. The analog input signal server determines the measurement curve corresponding to at least one AI point based on the target stored data of the device to be evaluated. Based on the measurement curves corresponding to each AI point and the standard curves corresponding to each AI point, the dynamic time warping (DTW) distance between the measurement curves and the standard curves corresponding to each AI point is determined. The health result of the device to be evaluated is determined based on the dynamic time warping (DTW) distance between the measurement curve and the standard curve corresponding to each AI point.

[0078] According to the health assessment system for a subway platform door system provided by the present invention, the assessment module 320 is further used for: When there are multiple devices to be evaluated, the health status of the subway platform door system is determined based on the health status results of each device to be evaluated. The health status results of the subway platform door system are stored in accordance with a custom second data template through the central cloud service; the fields of the second data template include: timestamp, station name, device name, health status and detailed information.

[0079] According to the health assessment system for a subway platform door system provided by the present invention, the assessment module 320 is further used for: If an anomaly is found at the DI point of the device under evaluation, an alarm message is generated. The alarm information is distributed through a message queue.

[0080] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a health assessment method for a subway platform screen door system. This method is applied to the central cloud platform of the subway platform screen door system's health assessment system. The subway platform screen door system's health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range from the up and down platform screen door devices. The method includes: The device status data of the up and down platform screen doors is stored in the IoTDB time-series database through the central cloud service to obtain the target stored data. The data collection points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series to organize data. By simulating the input signal server, the target storage data of the device to be evaluated is obtained from the IoTDB time series database, and the health result of the device to be evaluated is determined based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices; Based on the health results of the equipment to be evaluated, the health results of the subway platform door system are determined.

[0081] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the health assessment method for a subway platform screen door system provided by the above methods. This method is applied to the central cloud platform of the subway platform screen door system health assessment system. The subway platform screen door system health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range from the up and down platform screen door devices. The method includes: The device status data of the up and down platform screen doors is stored in the IoTDB time-series database through the central cloud service to obtain the target stored data. The data collection points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series to organize data. By simulating the input signal server, the target storage data of the device to be evaluated is obtained from the IoTDB time series database, and the health result of the device to be evaluated is determined based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices; Based on the health results of the equipment to be evaluated, the health results of the subway platform door system are determined.

[0083] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the health assessment method for a subway platform screen door system provided by the above methods. This method is applied to a central cloud platform in the health assessment system of the subway platform screen door system. The health assessment system of the subway platform screen door system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge-side server, which is a server deployed within a preset range from the up and down platform screen door devices. The method includes: The device status data of the up and down platform screen doors is stored in the IoTDB time-series database through the central cloud service to obtain the target stored data. The data collection points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series to organize data. By simulating the input signal server, the target storage data of the device to be evaluated is obtained from the IoTDB time series database, and the health result of the device to be evaluated is determined based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices; Based on the health results of the equipment to be evaluated, the health results of the subway platform door system are determined.

[0084] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0085] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A health assessment system for a subway platform door system, characterized in that, The health assessment system for the subway platform screen door system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the up and down platform screen door devices. The station server is used to acquire the device status data of the up and down platform screen doors and send the device status data of the up and down platform screen doors to the central cloud platform; the acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points; the device status data of the up and down platform screen doors is acquired by collecting the device status data of the up and down platform screen doors through IoT device sensors and uploading the device status data of the up and down platform screen doors to the station server via the Modbus protocol; The central cloud platform is used to store the device status data of the up and down platform gate devices into the IoTDB time series database through the central cloud service to obtain the target stored data; the IoTDB time series database is a database that uses time series to organize data. The central cloud platform is used to obtain target storage data of the device to be evaluated from the IoTDB time series database through the analog input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices.

2. The health assessment system for subway platform door systems according to claim 1, characterized in that, The DI points include: electromagnetic lock status, DCU status, motor status, door status, PEDC status, gap detection status, belt status, limit device status, and battery status; the AI ​​points include: motor current, motor speed, motor torque, and door position; acquiring the equipment status data of the up and down platform screen door equipment and sending the equipment status data to the central cloud platform includes: Obtain the equipment status data of the up and down platform screen doors; The equipment status data of the up and down platform screen doors are filtered based on preset data filtering conditions to obtain the filtered equipment status data of the down platform screen door; the preset data filtering conditions are AI points with a KMZ value of 1 when the door is open or a GMZ value of 1 when the door is closed. The filtered device status data is sent to the central cloud platform via gigabit network.

3. The health assessment system for subway platform door systems according to claim 1, characterized in that, The IoTDB time series database is a database that uses time series to organize data. The time series mainly consists of three main fields: timestamp, device ID, and measurement point value. The process of storing the device status data of the uplink and downlink platform screen doors into the IoTDB time-series database via the central cloud service to obtain the target stored data includes: The device status data of the uplink and downlink platform gate devices is stored in the Redis cache through the central cloud service; The central cloud service stores the device status data of the up and down platform gate devices in the cache according to a custom first data template to obtain the target stored data; the fields of the first data template include: timestamp, station name, device name, point name, point value, and alarm status.

4. The health assessment system for subway platform door systems according to claim 1, characterized in that, The step of obtaining target storage data of the device to be evaluated from the IoTDB time-series database through an analog input signal server, and determining the health result of the device to be evaluated based on the target storage data of the device to be evaluated, includes: The target storage data of the device to be evaluated is obtained from the IoTDB time series database by simulating the input signal server. The analog input signal server determines the measurement curve corresponding to at least one AI point based on the target stored data of the device to be evaluated. Based on the measurement curves corresponding to each AI point and the standard curves corresponding to each AI point, the dynamic time warping (DTW) distance between the measurement curves and the standard curves corresponding to each AI point is determined. The health result of the device to be evaluated is determined based on the dynamic time warping (DTW) distance between the measurement curve and the standard curve corresponding to each AI point.

5. The health assessment system for subway platform door systems according to claim 4, characterized in that, The central cloud platform is also used for: When there are multiple devices to be evaluated, the health status of the subway platform door system is determined based on the health status results of each device to be evaluated. The health status results of the subway platform door system are stored according to a custom second data template through the central cloud service; The fields of the second data template include: timestamp, station name, device name, health status, and details.

6. The health assessment system for subway platform door systems according to claim 4, characterized in that, The central cloud platform is also used for: If an anomaly is found at the DI point of the device under evaluation, an alarm message is generated. The alarm information is distributed through a message queue.

7. A method for assessing the health of a subway platform door system, characterized in that, A central cloud platform is applied to the health assessment system of a subway platform screen door system. The health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the up and down platform screen door devices. The method includes: The device status data of the up and down platform screen doors is stored in the IoTDB time-series database through the central cloud service to obtain the target stored data. The data collection points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series to organize data. By simulating the input signal server, the target storage data of the device to be evaluated is obtained from the IoTDB time series database, and the health result of the device to be evaluated is determined based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices; Based on the health results of the equipment to be evaluated, the health results of the subway platform door system are determined.

8. A health assessment device for a subway platform door system, characterized in that, A central cloud platform is used in the health assessment system of a subway platform screen door system. The health assessment system includes up and down platform screen door devices, a station server, and a central cloud platform. The station server is an edge server, which is a server deployed within a preset range of the up and down platform screen door devices. The device includes: The storage module is used to store the device status data of the up and down platform screen doors into the IoTDB time-series database via a central cloud service to obtain the target stored data. The acquisition points corresponding to the device status data of the up and down platform screen doors include digital input signal (DI) points and analog input signal (AI) points. The device status data of the up and down platform screen doors is collected by IoT device sensors, uploaded to the station server via the Modbus protocol, and then sent by the station server to the central cloud platform. The IoTDB time-series database is a database that uses time series data organization. The evaluation module is used to obtain the target storage data of the device to be evaluated from the IoTDB time series database through the simulated input signal server, and determine the health result of the device to be evaluated based on the target storage data of the device to be evaluated; the device to be evaluated is at least one of the up and down platform screen door devices.

9. An electronic device 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, it implements the health assessment method for the subway platform door system as described in claim 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the health assessment method for the subway platform door system as described in claim 7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the health assessment method for the subway platform door system as described in claim 7.

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