Data processing system and method

Abstract

Provided are a data processing system (10) and method. The data processing system (10) comprises a plurality of industrial personal computers (102-1 to 102-n) and a centralized control system (101). The industrial personal computers (102-1 to 102-n) are used for acquiring device operating states of production devices corresponding to the industrial personal computers (102-1 to 102-n); when the device operating states are different from the last device operating states of the production devices, acquiring device operating data of the production devices; when the device operating data represents that the production devices change from a first state to a second state, acquiring a device change reason of the production devices; and generating device-associated data on the basis of the device change reason and the device operating data, and uploading the device-associated data to the centralized control system (101). The centralized control system (101) is used for analyzing and comparing the device-associated data of the plurality of industrial personal computers (102-1 to 102-n) to obtain an operating state comparison result of the production devices corresponding to the plurality of industrial personal computers (102-1 to 102-n) on a battery production line.

Description

Data processing system and method

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This disclosure is based on the Chinese patent application with application number 202410211570.9, application date February 27, 2024, and invention name “Data Processing System and Method”, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is hereby introduced into this disclosure as a reference. Technical Field

[0003] The embodiments of the present disclosure relate to the field of intelligent manufacturing technology, and are related to, but not limited to, a data processing system and method. Background Art

[0004] During the battery production process, the operating status of the production equipment is recorded locally on the upper computer on the battery production line, and the operating data is stored in the local database. The production equipment alarms are continuously monitored by an independent module, and the centralized control system is used to count the alarm duration of each machine.

[0005] However, because the operating status of production equipment is only stored in a local database, and there is no correlation between equipment alarms and operating status, when an equipment alarm occurs, the centralized control system needs to query the equipment's operating status in the local database based on the alarm time, which is not very real-time. Therefore, how to centrally manage the operating status and alarm processing of production equipment on the production line is a pressing issue.

[0006] Summary of the Invention

[0007] In order to solve the problems existing in the related technologies, the embodiments of the present disclosure provide a data processing system and method. When the status of equipment on the production line changes, the industrial computer collects the operating status of the equipment, associates the operating status with the reason for the equipment change, and uploads the associated data to the centralized control system, so that the centralized control system does not need to obtain data locally every time, and can query and compare the operating status of production equipment corresponding to multiple industrial computers, thereby improving query efficiency and real-time performance.

[0008] In a first aspect, an embodiment of the present disclosure provides a data processing system, which is applied to a battery production line; it is characterized in that the data processing system includes: an industrial computer, which is used to obtain the equipment operating status of the production equipment corresponding to the industrial computer; the battery production line includes multiple industrial computers; the industrial computer is also used to obtain the equipment operating data of the production equipment when the equipment operating status is different from the previous equipment operating status of the production equipment; the industrial computer is also used to obtain the equipment change reason of the production equipment when the equipment operating data indicates that the production equipment has changed from a first state to a second state; the industrial computer is also used to generate equipment association data based on the equipment change reason and the equipment operation data, and upload the equipment association data to a centralized control system; the centralized control system is used to analyze and compare the equipment association data of the multiple industrial computers to obtain a comparison result of the operating status of the production equipment corresponding to the multiple industrial computers on the battery production line.

[0009] In the above embodiments, firstly, the industrial control computer of the disclosed embodiment can collect the operating status of the equipment when the equipment status on the production line changes, and associate the operating status with the reason for the equipment change, and upload the associated data to the centralized control system. When the centralized control system wants to inquire about the equipment shutdown, it can quickly determine the shutdown reason and downtime based on the associated data, and the data is more accurate and traceability is more convenient. Secondly, after receiving the associated data, the centralized control system does not need to obtain data locally every time, and can query and compare the operating status of the production equipment corresponding to multiple industrial control computers. Not only can the production equipment corresponding to the same type of industrial control computers be horizontally compared, thereby improving the query efficiency and real-time performance, but all the production equipment in a process section can also be compared to determine the equipment in each process section that is prone to blockage and shutdown, so as to improve the production efficiency of the battery production line.

[0010] In some embodiments, the system also includes a controller; wherein the industrial computer is also used to detect the communication channel between the industrial computer and the controller to obtain a detection result; the industrial computer is also used to trigger the equipment operation status point in the controller when the detection result indicates that the communication channel is normal; the controller is used to obtain the equipment operation status of the production equipment corresponding to the industrial computer when the equipment operation status point is triggered, and send the equipment operation status to the industrial computer.

[0011] In some embodiments, the system also includes a publish-subscribe service; wherein, the industrial computer is further used to associate the state change moment when the production equipment in the equipment operation data changes to the second state and the state duration of the production equipment in the second state with the equipment resource number of the industrial computer to obtain the equipment-associated data; the industrial computer is further used to upload the equipment-associated data to the operation status topic of the publish-subscribe service; wherein, the centralized control system subscribes to the operation status topic; the centralized control system is used to obtain the equipment-associated data when the equipment-associated data appears in the operation status topic.

[0012] In a second aspect, an embodiment of the present disclosure provides a data processing method, which is applied to the above-mentioned data processing system; it is characterized in that the data processing method includes: an industrial computer obtains the equipment operating status of the production equipment corresponding to the industrial computer; the battery production line includes multiple industrial computers; when the equipment operating status is different from the previous equipment operating status of the production equipment, the industrial computer obtains the equipment operating data of the production equipment; when the equipment operating data indicates that the production equipment changes from a first state to a second state, the industrial computer obtains the equipment change reason of the production equipment; the industrial computer generates equipment-related data based on the equipment change reason and the equipment operating data, and uploads the equipment-related data to the centralized control system; the centralized control system analyzes and compares the equipment-related data of the multiple industrial computers to obtain a comparison result of the operating status of the production equipment corresponding to the multiple industrial computers on the battery production line.

[0013] In the above embodiments, on the first hand, the industrial control computer of the disclosed embodiment can collect the operating status of the equipment when the equipment status on the production line changes, and associate the operating status with the reason for the equipment change, and upload the associated data to the centralized control system. When the centralized control system wants to inquire about the equipment shutdown, it can quickly determine the shutdown reason and downtime based on the associated data, and the data is more accurate and traceability is more convenient. On the second hand, after receiving the associated data, the centralized control system does not need to obtain data locally every time, and can query and compare the operating status of the production equipment corresponding to multiple industrial control computers. Not only can the production equipment corresponding to the same type of industrial control computers be horizontally compared, thereby improving the query efficiency and real-time performance, but all the production equipment in a process section can also be compared to determine the equipment in each process section that is prone to blockage and shutdown, so as to improve the production efficiency of the battery production line.

[0014] In some embodiments, the industrial computer obtains the equipment operation status of the production equipment corresponding to the industrial computer, including: the industrial computer detects the communication channel between the industrial computer and the controller to obtain a first detection result; when the first detection result indicates that the communication channel is normal, the industrial computer triggers the equipment operation status point in the controller; when the equipment operation status point is triggered, the controller obtains the equipment operation status of the production equipment corresponding to the industrial computer, and sends the equipment operation status to the industrial computer.

[0015] In the above embodiment, before the industrial computer obtains the equipment operating status of the production equipment, the connection between the industrial computer and the controller is detected, and maintenance is continuously performed in the event of an abnormal connection, thereby avoiding the problem that the industrial computer cannot read the midpoint position of the controller due to network fluctuations or other reasons, thereby improving data processing efficiency.

[0016] In some embodiments, the first state includes multiple first operating states; the data processing method also includes: when the equipment operation data represents that the production equipment changes among the multiple first operating states, the industrial computer determines the operating time corresponding to each first operating state of the production equipment based on the equipment operation data; the industrial computer associates the operating time corresponding to each first operating state of the production equipment with the equipment resource number of the industrial computer to obtain operation association data; the industrial computer sends the operation association data to the centralized control system.

[0017] In the above embodiment, the operating time corresponding to each first operating state of the production equipment is uploaded to the centralized control system, so that the centralized control system can collect data on the production equipment corresponding to each industrial computer according to the operating states such as normal production, waiting for materials, and material blockage, thereby realizing the comparison of equipment operating states between different industrial computers.

[0018] In some embodiments, the industrial computer obtains the reason for the equipment change of the production equipment, including: the industrial computer obtains the alarm array in the controller; the alarm array contains multiple alarm points; the industrial computer compares the alarm array with the local alarm array configured by the industrial computer, and determines the target alarm point corresponding to the change of the production equipment from the first state to the second state among the multiple alarm points; the industrial computer determines the alarm reason corresponding to the target alarm point as the reason for the equipment change of the production equipment.

[0019] In the above embodiment, based on the set alarm array, the triggered alarm point is determined, the cause of the equipment change can be quickly determined, and the engineer can be reminded to deal with the cause of the shutdown, avoiding the situation where the production line is stagnant and the materials cannot be processed and piled up, thereby improving the production line operation efficiency.

[0020] In some embodiments, the alarm array contains multiple alarm values, the multiple alarm values ​​correspond to multiple alarm points, and each alarm point corresponds to an alarm level; the industrial computer compares the alarm array with a local alarm array configured by the industrial computer, and determines the target alarm point corresponding to the change of the production equipment from the first state to the second state among the multiple alarm points, including: the industrial computer compares the multiple alarm values ​​of the alarm array with the multiple alarm values ​​of the local alarm array configured by the industrial computer, and determines the alarm point in the alarm array where the alarm value changes as the initial alarm point; the industrial computer determines the alarm point in the initial alarm point whose alarm level meets the equipment change condition as the target alarm point based on the alarm level of the initial alarm point.

[0021] In the above embodiment, based on the set alarm array, the triggered alarm point is determined, the cause of the equipment change can be quickly determined, and the engineer can be reminded to deal with the cause of the shutdown, avoiding the situation where the production line is stagnant and the materials cannot be processed and piled up, thereby improving the production line operation efficiency.

[0022] In some embodiments, the equipment operation data includes at least the state change moment when the production equipment changes to the second state and the state duration of the production equipment in the second state; the industrial computer generates equipment-associated data based on the equipment change reason and the equipment operation data, and uploads the equipment-associated data to the centralized control system, including: the industrial computer associates the state change moment, the state duration and the equipment resource number of the industrial computer to obtain the equipment-associated data; the industrial computer uploads the equipment-associated data to the operation status topic of the publish-subscribe service; wherein, the centralized control system subscribes to the operation status topic; when the equipment-associated data appears in the operation status topic, the centralized control system obtains the equipment-associated data.

[0023] In the above embodiment, the industrial computer uploads the device-related data to different topics, so that the centralized control system can obtain the data by classification, and the centralized control system can perform data analysis and processing according to the data category.

[0024] In some embodiments, the data processing method also includes: when there is device-related data uploaded by multiple industrial computers in the operating status topic, the publish-subscribe service sorts the device-related data uploaded by the multiple industrial computers based on the preset priority of each industrial computer to form a data sequence; correspondingly, the centralized control system obtains the device-related data, including: the centralized control system obtains the multiple device-related data in the operating status topic in sequence based on the data sequence.

[0025] In the above embodiment, the centralized control system can preferentially obtain data with a high priority, thereby avoiding failure to promptly pay attention to the operating status of the production equipment corresponding to the industrial computer with a high priority.

[0026] In some embodiments, the data processing method also includes: when the communication channel between the industrial computer and the controller is normal and the emergency stop point in the controller is triggered, the industrial computer obtains the equipment emergency stop data in the controller; the industrial computer uploads the equipment emergency stop data to the emergency stop topic of the publish-subscribe service; wherein, the centralized control system subscribes to the emergency stop topic, and the emergency stop topic includes the equipment emergency stop data corresponding to the multiple industrial computers on the battery production line; when the equipment emergency stop data appears in the emergency stop topic, the centralized control system obtains the equipment emergency stop data to obtain the equipment emergency stop data corresponding to the multiple industrial computers.

[0027] In the above embodiment, the industrial computer collects data on non-fault shutdowns and uploads the data to the centralized control system, thereby avoiding the problem of inaccurate analysis results due to non-fault shutdowns when the centralized control system performs shutdown analysis on equipment on the production line, thereby improving the accuracy of the analysis results.

[0028] In some embodiments, the data processing method further includes: when the communication channel between the industrial computer and the controller is normal, the industrial computer periodically obtains the equipment operation data of the production equipment and stores the equipment operation data in the database of the industrial computer.

[0029] In the above embodiment, the industrial computer stores equipment operating data such as equipment status, shutdown reasons, and three-color lights in the local database of the industrial computer, so that in the event of data loss in the centralized control system, the local database can be retrospectively queried to avoid data loss.

[0030] In some embodiments, the data processing method further includes: the industrial computer detects the connection channel between the industrial computer and the database to obtain a second detection result; when the second detection result indicates that the connection channel is normal, the industrial computer determines the storage date of the device operation data in the database; based on the storage date, the industrial computer deletes the device operation data in the database whose storage date meets the storage conditions, so as to clean up the device operation data in the database.

[0031] In the above embodiment, the industrial computer regularly cleans up the data in the local database to avoid the problem of useless data occupying too much memory, which leads to low efficiency of the industrial computer, thereby improving the processing efficiency of the industrial computer.

[0032] In some embodiments, the data processing method also includes: the industrial computer determines the maximum number of available threads in the thread pool corresponding to the industrial computer and the required number of threads for obtaining the operating status of the device; when the required number of threads is less than or equal to the maximum number of available threads, the industrial computer obtains the operating status of the device; when the required number of threads is greater than the maximum number of available threads, the industrial computer closes the thread for data cleaning or waits until the required number of threads is less than or equal to the maximum number of available threads.

[0033] In the above embodiment, the threads in the thread pool are managed based on the number of threads required for the tasks to be executed by the industrial computer, so that the industrial computer can give priority to executing high-priority tasks, ensuring real-time data acquisition and real-time data transmission of high-priority tasks to the centralized control system.

[0034] The above description is only an overview of the technical solution of the present disclosure. In order to more clearly understand the technical means of the present disclosure, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present disclosure more obvious and easy to understand, the specific implementation methods of the present disclosure are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] FIG1 is a structural diagram 1 of a data processing system provided by an embodiment of the present disclosure;

[0036] FIG2 is a second structural diagram of a data processing system provided by an embodiment of the present disclosure;

[0037] FIG3 is a first optional flow chart of a data processing method provided by an embodiment of the present disclosure;

[0038] FIG4 is a second optional flow chart of a data processing method provided in an embodiment of the present disclosure;

[0039] FIG5 is a schematic diagram of a flow chart of a data acquisition tool for local data storage according to an embodiment of the present disclosure;

[0040] FIG6 is a schematic diagram of a process for performing regular database cleaning using a data acquisition tool according to an embodiment of the present disclosure;

[0041] FIG7 is a schematic diagram of a device status collection and upload process according to an embodiment of the present disclosure;

[0042] FIG8 is a schematic diagram of a fixed LOSS device status monitoring process provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting the present disclosure. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0044] In the following description, references to "some embodiments" describe a subset of all possible embodiments, but it is understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. Unless otherwise defined, all technical and scientific terms used in the embodiments of the present disclosure have the same meaning as commonly understood by those skilled in the art to which the embodiments of the present disclosure belong. The terms used in the embodiments of the present disclosure are only for the purpose of describing the embodiments of the present disclosure and are not intended to limit the present disclosure.

[0045] Currently, market developments indicate that power batteries are becoming increasingly widely used. Power batteries are not only used in energy storage systems such as hydropower, thermal, wind, and solar power plants, but are also widely used in electric vehicles like electric bicycles, electric motorcycles, and electric vehicles, as well as in aerospace and other fields. As power battery applications continue to expand, market demand is also growing.

[0046] The present inventors note that in the battery production process, related technologies only record the operating status of production equipment locally on the production line via a host computer and store this data in a local database. Equipment alarms are continuously monitored by independent modules, with the centralized control system then using them to calculate the duration of each alarm. The three-color indicator light only serves as a visual indicator for the centralized control system to indicate whether the equipment is online.

[0047] However, the equipment status is only counted and displayed locally, and it is impossible to directly compare the same type of machines. Data comparison requires manual sorting, which is time-consuming and labor-intensive, and has poor real-time performance. There is no correlation between the equipment operating status and the cause of the alarm shutdown. When the centralized control system queries the equipment on the production line for an alarm shutdown, it needs to query the historical alarms in the local database based on the time of the shutdown, which makes the query difficult. At the same time, when counting equipment shutdowns, there is no distinction between fault shutdowns and non-fault shutdowns, which will affect the big data analysis of the shutdown causes and the statistics of normal production efficiency.

[0048] In order to solve the problems existing in the relevant technologies, the author of the study found that when the status of the equipment on the production line changes, the industrial computer can collect the operating status of the equipment, associate the operating status with the reason for the equipment change, and upload the associated data to the centralized control system, so that the centralized control system does not need to obtain data locally every time, and can query and compare the operating status of the production equipment corresponding to multiple industrial computers. Not only can the production equipment corresponding to the same type of industrial computers be horizontally compared, thereby improving the query efficiency and real-time performance, but all production equipment in a process section can also be compared to determine the equipment in each process section that is prone to blockage and shutdown, thereby improving the production efficiency of the battery production line. At the same time, associating the operating status with the reason for the equipment change enables the centralized control system to quickly determine the cause and time of the shutdown, making the data more accurate and traceability more convenient.

[0049] Based on the above-mentioned inventive concept, the embodiments of the present disclosure provide a data processing system and method. The data processing method is applied to the data processing system of a battery production line. The data processing system includes at least a centralized control system configured on the main server of the battery production line and an industrial computer in multiple on-site machines in each process section. The on-site machine has a human-machine interface (HMI). The industrial computer is installed with data acquisition software for collecting operating data of the production equipment corresponding to the industrial computer from the controller. The industrial computer of each on-site machine corresponds to at least one production equipment on the battery production line. The production equipment may refer to equipment such as robots, battery cell winding machines, pole welding equipment, battery assembly equipment, and product transport vehicles (AGV, Automated Guided Vehicle) on the production line.

[0050] In an embodiment of the present disclosure, an industrial computer obtains the equipment operating status of the production equipment corresponding to the industrial computer, and when the equipment operating status is different from the previous equipment operating status of the production equipment, obtains the equipment operating data of the production equipment, and when the equipment operating data indicates that the production equipment changes from a first state to a second state, obtains the equipment change reason of the production equipment, generates equipment-related data based on the equipment change reason and the equipment operating data, and uploads the equipment-related data to a centralized control system; the centralized control system analyzes and compares the equipment-related data of multiple industrial computers, and obtains a comparison result of the operating status of the production equipment corresponding to multiple industrial computers on the battery production line.

[0051] In this way, on the first hand, the industrial computer of the embodiment of the present disclosure can collect the operating status of the equipment when the equipment status on the production line changes, and associate the operating status with the reason for the equipment change, and upload the associated data to the centralized control system. When the centralized control system wants to query the equipment shutdown, it can quickly determine the shutdown reason and downtime based on the associated data, and the data is more accurate and traceability is more convenient. On the second hand, after receiving the associated data, the centralized control system does not need to obtain data locally every time, and can query and compare the operating status of the production equipment corresponding to multiple industrial computers. Not only can the production equipment corresponding to the same type of industrial computers be horizontally compared, thereby improving the query efficiency and real-time performance, but all the production equipment in a process section can also be compared to determine the equipment in each process section that is prone to blockage and shutdown, so as to improve the production efficiency of the battery production line.

[0052] The battery packs produced by the battery production line disclosed in the embodiments of the present disclosure can be used, but are not limited to, in electrical devices such as vehicles, ships, or aircraft. A power supply system comprising the battery packs and batteries disclosed herein can be used to construct such electrical devices. This can help mitigate and automatically regulate deterioration in cell expansion, replenish electrolyte consumption, and improve battery performance stability and battery life.

[0053] The battery packs produced by the battery production line disclosed in the embodiments of the present disclosure can be used as power sources for electrical devices, which may include, but are not limited to, mobile phones, tablets, laptops, electric toys, power tools, electric vehicles, electric cars, ships, spacecraft, and the like. Electric toys may include fixed or mobile electric toys, such as game consoles, electric car toys, electric ship toys, and electric airplane toys, and spacecraft may include airplanes, rockets, space shuttles, and spacecraft, among others.

[0054] In the embodiments of the present disclosure, the battery pack produced by the battery production line may be formed by a plurality of batteries connected in series and in parallel, wherein the battery may be a battery cell. A battery cell refers to a basic unit that can realize the mutual conversion of chemical energy and electrical energy, and can be used to make a battery module or a battery pack, thereby being used to supply power to an electrical device. The battery cell may be a secondary battery, which refers to a battery cell that can be continuously used by activating the active material by charging after the battery cell is discharged. The battery cell may be a lithium-ion battery, a sodium-ion battery, a sodium-lithium-ion battery, a lithium metal battery, a sodium metal battery, a lithium-sulfur battery, a magnesium-ion battery, a nickel-hydrogen battery, a nickel-cadmium battery, a lead-acid battery, etc., and the embodiments of the present disclosure are not limited thereto.

[0055] In some embodiments, a battery pack includes multiple cells, which can be connected in series, in parallel, or in a hybrid configuration. A hybrid configuration refers to a combination of series and parallel connections. The series, parallel, or hybrid configuration of the cells is achieved by welding the cell terminals to a busbar assembly. Each cell can be a secondary battery or a primary battery; it can also be a lithium-sulfur battery, a sodium-ion battery, or a magnesium-ion battery, but is not limited thereto. The cells can be cylindrical, flat, rectangular, or have other shapes.

[0056] In the embodiments of the present disclosure, the data processing system and method can be applied not only to battery production lines, but also to any production line, such as an automobile production line or a steel manufacturing production line. The embodiments of the present disclosure do not limit the specific application scenarios of the data processing system and method.

[0057] Next, we will explain the data processing method based on the application of it in a battery production line as an example.

[0058] An embodiment of the present disclosure provides a battery production line, including a data processing system and a plurality of production equipment. A centralized control system is provided on a battery production line, and the centralized control system can be arranged on the main server of the battery production line. The battery production line includes multiple process sections, such as electrode winding, cell grouping, battery pack addressing and battery welding. Each process section uses multiple production equipment to perform various process operations on the process section. For example, in addition to the welding robot, there are also production equipment for moving battery packs, equipment for cell winding, battery assembly equipment and production equipment for placing busbars during welding. Each process section is equipped with an on-site machine including an industrial computer and an HMI. The industrial computer collects the operating data of the production equipment through a controller (PLC, Programmable Logic Controller). On-site engineers can set alarm information based on the HMI according to the situation of the production site, and import the alarm information into the industrial computer and the centralized control system. In some embodiments, the industrial computer can be a host computer.

[0059] An embodiment of the present disclosure provides a data processing system. FIG1 is a structural schematic diagram of the data processing system provided by an embodiment of the present disclosure. As shown in FIG1 , the data processing system 10 includes at least a centralized control system 101 and multiple industrial computers 102 - 1 to 102 - n on a battery production line.

[0060] In some embodiments, a battery production line is equipped with a centralized control system 101, which can be arranged on the main server of the battery production line. The battery production line includes multiple industrial computers 102-1 to 102-n, each industrial computer corresponds to at least one production equipment, and each process section of battery production is performed by multiple production equipment. For example, battery welding is performed by a welding robot in the welding process.

[0061] In some embodiments, each industrial computer 102-1 to 102-n is configured to obtain the equipment operating status of the production equipment corresponding to each industrial computer, to obtain equipment operating data of the production equipment when the equipment operating status is different from the previous equipment operating status of the production equipment, to obtain the reason for the equipment change of the production equipment when the equipment operating data indicates that the production equipment has changed from a first state to a second state, and to generate equipment-related data based on the reason for the equipment change and the equipment operating data, and to upload the equipment-related data to the centralized control system 101. The centralized control system 101 is configured to analyze and compare the equipment-related data of the multiple industrial computers to obtain a comparison result of the operating status of the production equipment corresponding to the multiple industrial computers on the battery production line, and to display the comparison result on the display interface 101-1 of the centralized control system 101.

[0062] In some embodiments, the data processing system 10 also includes multiple controllers 103-1 to 103-n and a publish-subscribe service 104 corresponding to each industrial computer 102-1 to 102-n. The controller can refer to any one of a PLC, a single-chip microcomputer, a mid-level computer, and a host computer; the publish-subscribe service 104 can refer to a Kafka server (Kafka server). The Kafka server is a distributed publish-subscribe message system. Each industrial computer 102-1 to 102-n can upload device-related data to the topic (Topic) corresponding to the Kafka server. The centralized control system subscribes to the topic corresponding to the Kafka server to obtain the equipment operation data and equipment change reasons of the production equipment corresponding to each industrial computer 102-1 to 102-n.

[0063] In some embodiments, the publish-subscribe service 104 can also be a message queue. Each industrial computer 102-1 to 102-n can upload device-related data to the message queue. The centralized control system obtains the equipment operation data and equipment change reasons of the production equipment corresponding to each industrial computer 102-1 to 102-n based on the message queue.

[0064] Figure 2 is a second structural diagram of the data processing system provided by an embodiment of the present disclosure. As shown in Figure 2, each industrial computer 102-1 to 102-n is also used to detect the communication channel between each industrial computer 102-1 to 102-n and the corresponding controller 103-1 to 103-n to obtain the detection result, and is also used to trigger the equipment operation status point in each controller 103-1 to 103-n when the detection result indicates that the communication channel is normal. Each controller 103-1 to 103-n is used to obtain the equipment operation status of the production equipment corresponding to each industrial computer 102-1 to 102-n when the equipment operation status point is triggered, and send the equipment operation status to each industrial computer 102-1 to 102-n.

[0065] In some embodiments, each controller 103 - 1 to 103 - n is further configured to send the equipment change reason and equipment operation data of the production equipment to each industrial computer 102 - 1 to 102 - n.

[0066] In some embodiments, each industrial computer 102-1 to 102-n is also used to associate the state change time when the production equipment changes to the second state and the state duration of the production equipment in the second state in the equipment operation data with the equipment resource number of the industrial computer to obtain equipment association data, and upload the equipment association data to the operation status topic of the publish and subscribe service 104. The centralized control system 101 subscribes to the operation status topic and obtains the equipment association data when the equipment association data appears in the operation status topic.

[0067] It should be noted that the description of the system in the embodiment of the present disclosure is similar to the description of the method embodiment described below, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the embodiment of the system, please refer to the description of the method embodiment of the present disclosure for understanding.

[0068] Based on the aforementioned data processing system, an embodiment of the present disclosure provides a data processing method. FIG3 is a first optional flow chart of the data processing method provided by the embodiment of the present disclosure. As shown in FIG3 , the data processing method provided by the embodiment of the present disclosure can be implemented through steps S301 to S305:

[0069] Step S301: An industrial computer obtains the equipment operation status of the production equipment corresponding to the industrial computer; the battery production line includes multiple industrial computers.

[0070] In the embodiment of the present disclosure, the battery production line includes multiple industrial computers. All production equipment in a process section may correspond to one industrial computer, or there may be multiple industrial computers in a process section, each industrial computer corresponding to the same or different production equipment. Here, if two industrial computers correspond to the same production equipment respectively, then the two industrial computers are of the same type.

[0071] In some embodiments, the equipment operating status of the production equipment refers to the current operating status of the production equipment, for example, the production equipment is in a shutdown, normal operation, waiting for material, or blocked state.

[0072] The industrial computer can obtain the equipment operation status by triggering and reading the equipment operation status point in the PLC to obtain the equipment operation status of the production equipment corresponding to the industrial computer.

[0073] In some embodiments, the point where the industrial computer reads the device operating status in the PLC may be read periodically, for example, once every 1 second (s).

[0074] Step S302: When the equipment operation state is different from the previous equipment operation state of the production equipment, the industrial computer obtains equipment operation data of the production equipment.

[0075] In some embodiments, after reading the equipment operating status of the production equipment, the industrial computer will store the equipment operating status in the database of the industrial computer. Therefore, after obtaining the equipment operating status of the production equipment, the industrial computer can compare it with the previous equipment operating status. If the operating status changes, the industrial computer needs to obtain the equipment operating data of the production equipment to determine what changes have occurred in the production equipment, whether it has been shut down or whether blockage has occurred.

[0076] Here, equipment operation data may include data such as the time of state change when the production equipment changes, the duration of the state change after the production equipment changes, the production equipment's three-color light, and the reason for the state change. The three-color light of the production equipment can be obtained by reading the three-color light points of the equipment in the PLC. A red light indicates that the production equipment is shut down, a green light indicates that the production equipment is operating normally, and a yellow light indicates that the production equipment is blocked. The reason for the state change, the time of the state change, and the duration of the state can all be obtained by reading the corresponding points in the PLC.

[0077] In some embodiments, if the device operating status is the same as the last device operating status of the production device, no subsequent operation is required, and the device operating status can be read again after 1 second.

[0078] Step S303: When the equipment operation data indicates that the production equipment changes from the first state to the second state, the industrial computer obtains a reason for the equipment change of the production equipment.

[0079] In some embodiments, the first state may be an operating state of the production equipment, such as normal production, waiting for material, or material blockage, and the second state may be a shutdown state. When the production equipment is shut down, the corresponding alarm point in the PLC is triggered. Therefore, the cause of the equipment change of the production equipment can be determined based on the triggered alarm point. For example, if the alarm point indicating that the safety door is opened is triggered, the opening of the safety door can be considered the cause of the equipment change of the production equipment.

[0080] In some embodiments, an HMI is provided on a machine including an industrial computer. On-site engineers set multiple (for example, 10,000) alarm points for the production line according to the production line conditions. Each alarm point includes the cause of the alarm and the type of alarm, for example, the safety door is opened, the transport vehicle collides, or an unknown object enters the grating. In order to reduce the amount of data, multiple alarm points can be standardized. After standardization of the alarm points, an alarm array with 600 words can be obtained. Each word in the alarm array corresponds to multiple alarm points one-to-one. For example, every 16 alarm points correspond to one word. That is, there is a mapping relationship between 600 words and 10,000 alarm points, and one word point reads out 16 alarm points. Here, the 16 alarm points corresponding to one word point can refer to 16 bits of binary. Each position is 0, which means that the 16 alarm points corresponding to the word are not triggered, and a 1 in it means that the alarm point is triggered.

[0081] Here, after setting the alarm array in the HMI, the engineer can import the alarm array into the industrial computer. When the production equipment changes from the first state to the second state, the industrial computer obtains the PLC alarm array, compares the PLC alarm array with the alarm array of the industrial computer, determines the triggered alarm point, and then obtains the reason for the shutdown, that is, the reason for the equipment change of the production equipment.

[0082] In some embodiments, the first state may include multiple first operating states, such as normal operation, waiting for material, and material blocking states of the production equipment. Therefore, in addition to being shut down, the production equipment may also change between the multiple first operating states. Therefore, the data processing method provided in the embodiment of the present disclosure may further include steps S1 to S3:

[0083] Step S1: When the equipment operation data indicates that the production equipment changes among the multiple first operation states, the industrial computer determines the operation time corresponding to each first operation state of the production equipment based on the equipment operation data.

[0084] In some embodiments, the changes of production equipment in the multiple first operating states may refer to situations such as normal production becoming blocked, normal production becoming waiting for material, etc. At this time, none of the alarm points are triggered, and the operating time corresponding to each first operating state of the production equipment can be determined. For example, at 9:55 am, it changes from normal production to waiting for material, and then returns to normal production after the waiting time lasts for 15 minutes.

[0085] Step S2: The industrial computer associates the operating time corresponding to each first operating state of the production equipment with the equipment resource number of the industrial computer to obtain operating association data.

[0086] In the embodiment of the present disclosure, each industrial computer has a corresponding equipment resource number. The embodiment of the present disclosure associates the operating time corresponding to each first operating state with the equipment resource number of the industrial computer to obtain operating association data, and sends the operating association data to the centralized control system, so that the centralized control system can perform data statistics according to operating states such as normal production, waiting for materials, and material blockage, and realize comparison of equipment operating states between different industrial computers.

[0087] Step S3: The industrial computer sends the operation-related data to the centralized control system.

[0088] The embodiment of the present disclosure uploads the operating time corresponding to each first operating state of the production equipment to the centralized control system, so that the centralized control system can collect data on the production equipment corresponding to each industrial computer according to the operating states such as normal production, waiting for materials, and material blockage, thereby realizing the comparison of equipment operating states between different industrial computers.

[0089] Step S304: The industrial computer generates device-related data based on the device change reason and the device operation data, and uploads the device-related data to the centralized control system.

[0090] In some embodiments, the cause of equipment change is associated with the equipment operation data, and equipment association data is generated and then uploaded to the centralized control system. When the centralized control system queries the cause of the downtime alarm based on the equipment downtime, it can quickly obtain it based on the equipment association data without having to query the machine corresponding to the production equipment, thereby improving the query efficiency.

[0091] Step S305 : The centralized control system analyzes and compares the equipment-related data of the multiple industrial computers to obtain a comparison result of the operating states of the production equipment corresponding to the multiple industrial computers on the battery production line.

[0092] In some embodiments, after obtaining device-related data from multiple industrial computers, the centralized control system can analyze and compare the device-related data of each industrial computer to obtain an operational status comparison result. For example, if there are 24 machines in the battery cell grouping process, and the device-related data uploaded by the industrial computers of 23 machines indicates normal production, but the production equipment corresponding to one machine frequently shuts down, a horizontal comparison can be used to identify the machine with the problem. A vertical comparison can also be used to determine whether the production equipment corresponding to a machine in a process section frequently shuts down, resulting in low output for the entire production line.

[0093] In the disclosed embodiment, after obtaining the operating status comparison results of the production equipment, the operating status comparison results can be displayed on the display interface of the centralized control system. Here, the operating status comparison results can be displayed in the form of reports, and daily and monthly reports can be generated to intuitively display the operating status of the production equipment of different machines on the production line. This can help managers understand the production status of each process section and each machine on the production line, greatly improving production efficiency.

[0094] Thus, on the one hand, the industrial computer of the embodiment of the present disclosure can collect the operating status of the equipment when the equipment status on the production line changes, associate the operating status with the reason for the equipment change, and upload the associated data to the centralized control system. When the centralized control system queries whether the equipment is down, it can quickly determine the reason and time of the downtime based on the associated data, and the data is more accurate and traceability is more convenient. On the other hand, after receiving the associated data, the centralized control system can query and compare the operating status of the production equipment corresponding to multiple industrial computers without having to obtain data locally every time. Not only can the production equipment corresponding to the same type of industrial computers be horizontally compared, thereby improving the query efficiency and real-time performance, but all the production equipment in a process section can also be compared to determine the equipment in each process section that is prone to blockage and shutdown, so as to improve the production efficiency of the battery production line.

[0095] In some embodiments, the data processing system further includes a controller (PLC), and the industrial computer is used to trigger corresponding points in the PLC to obtain the operating data of the production equipment. Step S301 can be implemented through steps S3011 to S3013:

[0096] Step S3011: The industrial computer detects the communication channel between the industrial computer and the controller to obtain a first detection result.

[0097] In some embodiments, the IPC will first test the communication channel between the IPC and the controller to determine whether the connection between the IPC and the controller is normal. If it is not normal, it may be due to network fluctuations that caused the connection failure. In this case, an error log can be generated. After a preset time period (for example, 100 milliseconds), the connection between the IPC and the controller can be reconfirmed to determine whether it is normal. If there are multiple connection anomalies, a pop-up window can be displayed on the IPC display interface or the machine's HMI interface to prompt on-site engineers to maintain the connection between the IPC and the controller.

[0098] Step S3012: When the first detection result indicates that the communication channel is normal, the industrial computer triggers the device operation status point in the controller.

[0099] In some embodiments, when the connection between the industrial computer and the controller is normal, the device operation status bit in the controller is triggered to read the device operation data corresponding to the device operation status bit. The device operation status bit can be a Boolean bit, which is false when not triggered and true when triggered.

[0100] Step S3013: When the equipment operation status point is triggered, the controller obtains the equipment operation status of the production equipment corresponding to the industrial computer, and sends the equipment operation status to the industrial computer.

[0101] In some embodiments, when the equipment operation status point is triggered, the controller obtains the equipment operation status of the production equipment corresponding to the industrial computer through the PLC program, and sends the equipment operation status to the industrial computer based on the communication channel.

[0102] The disclosed embodiment detects the connection between the industrial computer and the controller before the industrial computer obtains the equipment operating status of the production equipment, and continuously performs maintenance in the event of an abnormal connection, thereby avoiding the problem that the industrial computer cannot read the PLC midpoint due to network fluctuations or other reasons, thereby improving data processing efficiency.

[0103] In some embodiments, the change of the production equipment from the first state to the second state may refer to a change from a running state to a stopped state. When the production equipment stops, the stop alarm point in the PLC is triggered, and the reason for the stop can be obtained. Therefore, determining the reason for the equipment change of the production equipment, that is, step S103, can be implemented through steps S1031 to S1032:

[0104] Step S1031: The industrial computer obtains an alarm array in the controller; the alarm array includes multiple alarm points.

[0105] In some embodiments, after engineers set up the alarm array in the HMI, they can import the alarm array into the industrial computer and the controller. When the production equipment changes from a running state to a shutdown state, the industrial computer will trigger the alarm point in the controller. At this time, the controller obtains the alarm array of the PLC, compares the alarm array of the PLC with the alarm array of the industrial computer, determines the triggered alarm point, and then obtains the reason for the shutdown, that is, the reason for the equipment change of the production equipment.

[0106] In some embodiments, on-site engineers set multiple (for example, 10,000) alarm points for the production line based on the actual operation of the production line. Each alarm point includes the cause of the alarm and the type of alarm, such as the alarm point where the safety door is opened, the transport vehicle collides, or an unknown object enters the grating. In order to reduce the amount of data, multiple alarm points can be standardized. After standardization of the alarm points, an alarm array with 600 words can be obtained. Each word in the alarm array corresponds one-to-one to multiple alarm points. For example, every 16 alarm points correspond to one word. That is, there is a mapping relationship between 600 words and 10,000 alarm points, and one word point reads out 16 alarm points. Here, the 16 alarm points corresponding to one word point can refer to 16 bits of binary, where each position is 0 for not triggered, and 1 for the alarm point being triggered.

[0107] Step S1032: the industrial computer compares the alarm array with a local alarm array configured for the industrial computer, and determines a target alarm point corresponding to the change of the production equipment from the first state to the second state among the multiple alarm points.

[0108] In some embodiments, the industrial computer compares the controller's alarm array with a local alarm array configured for the industrial computer, identifies an alarm point in the controller's alarm array that differs from the local alarm array, i.e., a triggered point, and determines that point as the target alarm point corresponding to the production equipment changing from a first state to a second state. For example, if the alarm point indicating a safety door is opened is 1 in the controller's alarm array but 0 in the local alarm array, indicating that the alarm point indicating the safety door is opened is triggered, the target alarm point can be determined.

[0109] In some embodiments, the alarm array includes multiple alarm values, each of which corresponds to a plurality of alarm points. Each alarm point corresponds to an alarm level, and the alarm levels may include at least level 1 (F-Alarm), level 2 (Alarm), level 3 (Warning), and level 4 (Info). Triggering the alarm points corresponding to level 1 (F-Alarm) and level 2 (Alarm) will cause the production equipment to shut down. Step S1032 can be implemented through steps S4 and S5:

[0110] Step S4: the industrial computer compares the multiple alarm values ​​of the alarm array with the multiple alarm values ​​of the local alarm array configured by the industrial computer, and determines the alarm point where the alarm value in the alarm array changes as the initial alarm point.

[0111] In some embodiments, when the production equipment is shut down, many alarm points may be triggered, for example, the safety door corresponding to the first-level alarm is not closed, the transport cart corresponding to the third-level alarm is crowded, etc. However, not all of the multiple triggered alarm points will cause the equipment to shut down. Only the alarm points corresponding to the first level (F-Alarm) and the second level (Alarm) will cause the production equipment to shut down when they are triggered. Therefore, it is necessary to determine the alarm point that causes the shutdown among the multiple triggered alarm points (i.e., the initial alarm point).

[0112] Here, the alarm level of the alarm point where the alarm value in the alarm array changes can be set by the engineer when setting the alarm point.

[0113] Step S5: The industrial computer determines, based on the alarm levels of the initial alarm points, an alarm point whose alarm level meets the equipment change condition among the initial alarm points as the target alarm point.

[0114] In some embodiments, the equipment change condition may be that the alarm levels are level one and level two, that is, the target alarm points are the level one and level two alarm points among the multiple triggered alarm points.

[0115] In some embodiments, when the equipment is shut down, there may be multiple factors that cause the shutdown. Therefore, when the equipment change reason is sent to the centralized control system, the five shutdown reasons with the highest confidence will be sent to the centralized control system. In the aforementioned embodiment, when the equipment operation status of the production equipment is different from the equipment operation status of the production equipment last time, the industrial control machine will obtain the equipment operation data of the production equipment. The equipment operation data includes an equipment shutdown reason sent by a PLC. Therefore, the equipment change condition can also be the alarm level of level one and level two, and the four alarm points with the highest confidence. At this time, there are four target alarm points. Based on the four target alarm points, four shutdown alarm reasons can be obtained. The four shutdown alarm reasons and one equipment shutdown reason constitute the equipment change reason for the production equipment shutdown and are sent to the centralized control system.

[0116] Here, the confidence levels of alarm points of different alarm levels are set together when setting the alarm points. For example, the confidence level of a safety door being opened is higher than that of an unknown object entering the grating.

[0117] Step S1033: The industrial computer determines the alarm cause corresponding to the target alarm point as an equipment change cause of the production equipment.

[0118] In the disclosed embodiment, the alarm cause corresponding to the target alarm point can be determined as the equipment change cause of the production equipment. The equipment downtime cause sent by the PLC and the alarm cause corresponding to the target alarm point can also be determined as the equipment change cause of the production equipment.

[0119] In some embodiments, after determining the reason for the equipment change, the industrial computer may display a pop-up window of the reason for the equipment change on a display interface of the industrial computer.

[0120] The disclosed embodiment determines the triggered alarm points based on the set alarm array, can quickly determine the cause of the equipment change, can remind engineers to deal with the cause of the shutdown, avoid production line stagnation, and cause materials to be unable to be processed and piled up, thereby improving the production line operation efficiency.

[0121] In some embodiments, the equipment operation data includes at least the state change time of the production equipment into the second state and the state duration of the production equipment in the second state. Figure 4 is a second optional flow diagram of the data processing method provided by an embodiment of the present disclosure. As shown in Figure 4, step S104 can be implemented by steps S401 to S403:

[0122] Step 401: The industrial computer associates the state change time, the state duration, and the device resource number of the industrial computer to obtain the device association data.

[0123] In some embodiments, the state change time and state duration of the production equipment are associated with the equipment resource number of the industrial computer and then uploaded, so that when the centralized control system queries the operating status of the equipment based on time, it can quickly determine the status of the equipment and analyze and compare the operating status of the equipment based on the state duration.

[0124] Step 402: The industrial computer uploads the device-related data to the operating status topic of the publish-subscribe service; wherein the centralized control system subscribes to the operating status topic.

[0125] In some embodiments, there are multiple different topics in the publish-subscribe service, and the centralized control system subscribes to corresponding topics to obtain corresponding data when the topics publish the corresponding data.

[0126] Step 403: When the device-related data appears in the running status topic, the centralized control system obtains the device-related data.

[0127] In some embodiments, the centralized control system subscribes to the running status topic of the publish-subscribe service. After the industrial computer uploads the device-related data to the running status topic of the publish-subscribe service, the centralized control system can obtain the device-related data.

[0128] The disclosed embodiment uploads device-related data to different topics, so that the centralized control system can obtain data by classification, and the centralized control system can perform data analysis and processing according to data categories.

[0129] In some embodiments, the device-related data generated by all industrial computers on a battery production line is sent to the operating status topic of the publish-subscribe service. Therefore, a large amount of device-related data may sometimes be included in the operating status topic. In this case, it is necessary to sort the multiple device-related data so that the centralized control system can prioritize important data. Here, the data processing method provided by the embodiment of the present disclosure may also include: when the operating status topic contains device-related data uploaded by multiple industrial computers, the publish-subscribe service sorts the device-related data uploaded by the multiple industrial computers based on the preset priority of each industrial computer to form a data sequence.

[0130] In some embodiments, the preset priority of each industrial computer can be determined in advance by technical personnel based on the process segments corresponding to each industrial computer. For example, the priority of the industrial computer corresponding to the battery filling process is greater than the priority of the industrial computer corresponding to the battery welding process. The priority setting can also be based on which process segments the technical personnel want to observe the operating status of the production equipment. For example, if multiple process segments of battery grouping need to be observed this month, the priority of the industrial computer corresponding to the battery grouping is greater than the priority of other process segments.

[0131] Here, after determining the priority level of each IPC, the publish-subscribe service sorts the device-related data uploaded by the multiple IPCs based on their preset priorities, forming a data sequence. Accordingly, step 403 can be implemented by the centralized control system sequentially obtaining the multiple device-related data in the operating status topic based on this data sequence. This allows the centralized control system to preferentially obtain high-priority data, avoiding missing timely attention to the operating status of production equipment corresponding to high-priority IPCs.

[0132] In some embodiments, when production equipment changes from an operating state to a shutdown state, it may be due to a fault or equipment maintenance. The engineer took a photo of a non-fault shutdown caused by the emergency stop button on the production line, but the production equipment did not distinguish between non-fault shutdowns when it changed from the first state to the second state. Therefore, when the centralized control system analyzes the equipment-related data, the comparison result of the operating state of the production equipment obtained will be inaccurate due to the non-fault shutdowns. Therefore, it is necessary to distinguish non-fault shutdowns in shutdowns. Therefore, the data processing method provided in the embodiment of the present disclosure can also include steps S10 to S12:

[0133] Step S10: When the communication channel between the industrial computer and the controller is normal and the emergency stop point in the controller is triggered, the industrial computer obtains the equipment emergency stop data in the controller.

[0134] In some embodiments, if the equipment on the production line needs maintenance, or the production line needs to be cut, pulled, or changed, the engineer will press the emergency stop button on the production line to shut down the equipment on the production line to prevent the moving equipment from causing harm to the personnel on the production line. At this time, the shutdown caused by pressing the emergency stop button is a non-fault shutdown, the alarm point will not be triggered, and the reason for the equipment change from the first state to the second state of the production equipment is the default reason.

[0135] Here, the equipment emergency stop data may be the emergency stop start time and the emergency stop duration. The equipment emergency stop data is obtained by associating the emergency stop start time and the emergency stop duration with the industrial computer equipment resource number corresponding to the production equipment where the emergency stop occurs.

[0136] Step S11: The industrial computer uploads the equipment emergency stop data to the emergency stop topic of the publish-subscribe service; wherein the centralized control system subscribes to the emergency stop topic, which includes the equipment emergency stop data corresponding to the multiple industrial computers on the battery production line.

[0137] Step S12: When the equipment emergency stop data appears in the emergency stop topic, the centralized control system obtains the equipment emergency stop data to obtain the equipment emergency stop data corresponding to the multiple industrial computers.

[0138] In the disclosed embodiment, the equipment emergency stop data generated by all industrial computers on the battery production line during emergency stop will be sent to the emergency stop topic of the publish-subscribe service, and the centralized control system will obtain all emergency stop data on the production line based on the emergency stop topic.

[0139] In the disclosed embodiment, data is collected for non-fault shutdowns and uploaded to the centralized control system, thereby avoiding the problem of inaccurate analysis results due to non-fault shutdowns when the centralized control system performs shutdown analysis on equipment on the production line, thereby improving the accuracy of the analysis results.

[0140] In some embodiments, in order to allow the industrial computer to query the local database of the corresponding machine for verification when an abnormality or loss of equipment data occurs in the centralized control system, the PLC will store point data such as equipment status, shutdown reason, and three-color light in the local database of the industrial computer when looping through the corresponding points. This allows the local database to be retroactively queried in the event of data loss in the centralized control system. Therefore, the data processing method provided by the embodiment of the present disclosure may also include step S20:

[0141] Step S20: When the communication channel between the industrial computer and the controller is normal, the industrial computer periodically obtains the equipment operation data of the production equipment and stores the equipment operation data in a database of the industrial computer.

[0142] In some embodiments, periodicity may mean obtaining equipment operation data of production equipment at fixed intervals. Since the operating status of production equipment on the production line may change at any time, the periodicity may be shorter, such as obtaining it once a minute, to avoid inaccurate data.

[0143] The disclosed embodiment stores equipment operating data such as equipment status, shutdown reasons, and three-color lights in a local database of an industrial computer, so that in the event of data loss in the centralized control system, the local database can be retrospectively queried to avoid data loss.

[0144] In some embodiments, in order to prevent the data in the local database from occupying too much memory and causing the industrial computer to have lower efficiency, the industrial computer can periodically clean up the data in the local database through a thread. Therefore, the data processing method provided by the embodiment of the present disclosure can also include steps S30 to S32:

[0145] Step S30: The industrial computer detects the connection channel between the industrial computer and the database to obtain a second detection result.

[0146] Step S31: When the second detection result indicates that the connection channel is normal, the industrial computer determines the storage date of the device operation data in the database.

[0147] In some embodiments, the storage date of the device operation data refers to the time when the device operation data is stored in the database.

[0148] Step S32: The industrial computer deletes the device operation data in the database whose storage date meets the storage condition based on the storage date, so as to clean up the device operation data in the database.

[0149] In some embodiments, the storage condition may be one month, that is, the industrial control machine will periodically (for example, every day) clear outdated data that is more than one month old.

[0150] The disclosed embodiment regularly cleans up data in a local database to avoid the problem of useless data occupying too much memory, which leads to low efficiency of the industrial computer, thereby improving the processing efficiency of the industrial computer.

[0151] In some embodiments, the industrial computer obtains the equipment operating status and equipment emergency stop data of the production equipment on the production line, performs local data storage, and deletes expired data based on threads. Therefore, the embodiment of the present disclosure also provides a thread allocation method, as shown in steps S33 to S35:

[0152] Step S33: The industrial computer determines the maximum number of available threads in the thread pool corresponding to the industrial computer and the required number of threads for obtaining the operating status of the device.

[0153] In some embodiments, the industrial computer may determine the number of threads required to execute the operation based on the amount of tasks corresponding to the acquired device operating status, and query the current maximum number of available threads in the thread pool.

[0154] Step S34: When the required number of threads is less than or equal to the maximum number of available threads, the industrial computer obtains the device operation status.

[0155] Step S35: When the required number of threads is greater than the maximum number of available threads, the industrial computer shuts down the thread for data cleanup or waits until the required number of threads is less than or equal to the maximum number of available threads.

[0156] In some embodiments, if the required number of threads is less than or equal to the maximum number of available threads, the industrial computer obtains the device operating status. If the required number of threads is greater than the maximum number of available threads, the industrial computer can shut down the thread performing data cleanup or wait until the required number of threads is less than or equal to the maximum number of available threads. Here, data cleanup has a lower priority than obtaining the device operating status of the production equipment, so the industrial computer can shut down the thread performing data cleanup.

[0157] In some embodiments, the priorities of the industrial computer in obtaining equipment emergency stop data, obtaining equipment operating status, performing local data storage, and deleting expired data can be in a descending order. Based on the above sorting, low-priority threads can be closed to meet the number of threads for high-priority tasks.

[0158] In some embodiments, when the industrial computer performs operations such as obtaining equipment emergency stop data, performing local data storage, and deleting expired data, threads can be allocated based on steps S33 to S35 to enable the industrial computer to operate in an orderly manner.

[0159] The disclosed embodiment manages the threads in the thread pool based on the number of threads required for the tasks to be executed by the industrial computer, so that the industrial computer can give priority to executing high-priority tasks, ensuring real-time data acquisition and real-time data transmission of high-priority tasks to the centralized control system.

[0160] The following describes an exemplary application of an embodiment of the present disclosure in a practical application scenario, specifically relating to a process for collecting device status of devices on a production line.

[0161] In related technologies, the host computer locally records the operating status of equipment on the production line, stores it in a local database, and calculates the operating time of each state. Equipment alarms are continuously monitored by an independent module in the centralized control system, which uses it to calculate the duration of each alarm. The three-color indicator light only serves as a visual indicator for the centralized control system to indicate whether the equipment is online.

[0162] In related technologies, equipment status is only counted and displayed locally, making it impossible to directly compare machines of the same type. Comparing upper-level data between machines of the same type requires manual compilation, which is time-consuming and labor-intensive, and has poor real-time performance. There is no correlation between the equipment's operating status and the cause of the alarm shutdown. Historical alarms need to be queried based on the time the shutdown occurred, which is difficult to query. The three-color light only serves as display information and has no basis for display. Non-fault shutdowns (such as pressing the emergency stop button, production line switching, and equipment maintenance) are also counted as fault downtime, which will affect the big data analysis of the shutdown cause and the statistics of normal production efficiency.

[0163] Based on the problems existing in related technologies, the embodiments of the present disclosure provide an equipment status collection process, which is implemented through the on-site machines on the production line and the centralized control system corresponding to the battery production line. The on-site machines are equipped with an industrial computer and a human-machine interaction module (HMI, Human Machine Interface), and the industrial computer is equipped with data collection software (i.e., data collection tools) for collecting the operating status and operating data of the equipment on the production line.

[0164] This system collects equipment status data from the machine's industrial computer and uploads it to a Kafka server via the Kafka protocol. The centralized control system subscribes to the Kafka server, allowing it to query the corresponding downtime cause for each equipment downtime. The centralized control system can simply calculate equipment status by normal production, waiting for material, material blockage, and downtime, and can also break down the specific downtime cause, making data more accurate and traceable more convenient.

[0165] After the centralized control system receives the equipment status of each production equipment corresponding to each machine (for example, the robot arm, battery cell winding machine, terminal welding equipment, battery assembly equipment, and product transport vehicle (AGV) on the production line), it stores it in the centralized control system database with the equipment resource number as the primary key. The centralized control system provides an information query interface, which can be used to collect statistics on the status of each single device; it can also be used to select multiple devices for horizontal comparison.

[0166] When equipment on the production line triggers a shutdown, the industrial control unit on the machine immediately uploads the equipment status and then starts a thread to monitor the trigger point for fixed loss (i.e., non-fault shutdowns, such as pressing the emergency stop button on the production line). If the on-site operator (OPN, Operations) selects the corresponding shutdown reason for the fixed loss (such as cutting, pulling, changing, or equipment maintenance) on the touch screen (i.e., the human-computer interaction module), the data related to the fixed loss will be monitored and collected, and the data will be uploaded to the centralized control system again. In this way, the centralized control system can collect information related to the fixed loss.

[0167] The equipment status acquisition process provided by the embodiment of the present disclosure is divided into four parts. The first part is the local storage of equipment status information. The change of equipment status on the production line is accidental and it is not certain when it will occur. It is also not guaranteed whether the equipment status data will be lost. In order to enable the industrial computer (i.e., data acquisition tool) to query the local database on the corresponding machine for verification when equipment data anomalies or data loss occur in the centralized control system, the PLC will store the equipment status, shutdown reasons, three-color light and other point data in the local database when looping through the corresponding points. Therefore, if the data of the centralized control system is lost, the local database can be used for backtracking query.

[0168] The second part is the automatic cleaning of local data. Too much data in the local database will slow down the operation of the data acquisition tool and reduce its efficiency. Therefore, in order to prevent the data in the local database from occupying too much memory, the data acquisition tool can start a thread to regularly clean up data that has expired for more than 1 month.

[0169] The third part is the device status upload. In order to enable the centralized control system to view the device operation status in multiple dimensions and perform cross-machine comparison, the data acquisition tool can use a thread to collect relevant information about the device operation, package and upload this data to the Kafka server, and allow the centralized control system to subscribe to and analyze this data.

[0170] The fourth part is the fixed LOSS (non-fault shutdown) upload. If the device changes from non-shutdown to shutdown, a fixed LOSS monitoring thread will be opened to collect fixed LOSS alarms and upload them to the centralized control system, which is used by the centralized control system to distinguish between fault shutdown and fixed LOSS.

[0171] The disclosed embodiment provides a data acquisition tool for local data storage. When the data acquisition tool program is running in the industrial computer, the industrial computer containing the data acquisition tool will have a thread to continuously store key points such as the device's operating status, the device's three-color light, and the reason for the device's downtime in the local database. This function mainly consists of two parts: the PLC and the data acquisition tool.

[0172] FIG5 is a schematic diagram of a flow chart of a data acquisition tool performing a local data storage function according to an embodiment of the present disclosure. As shown in FIG5 , the flow chart of a data acquisition tool performing a local data storage function may be implemented through steps S501 to S504:

[0173] Step S501: Check whether the PLC connection is normal.

[0174] First, the data acquisition tool software of the industrial computer determines whether the connection status between the PLC and the data acquisition tool software is normal. If the PLC connection is abnormal, the PLC disconnection situation will be written to the error log, and step S503 will be executed. After sleeping for 100ms, step S501 will be repeated; if the connection status is normal, step S502 will be executed.

[0175] Step S502: Read the device status, three-color light, and shutdown reason point.

[0176] In some embodiments, if the PLC connection status is normal, the PLC will batch read the following points: device operating status (PackTags.Status.MachineStatus), device shutdown reason (PackTags.Admin.FirstOutAlarm), and device three-color light (PackTags.Status.LightStack.words).

[0177] Step S503: Write an error log.

[0178] Step S504: Store the data in a local database.

[0179] In some embodiments, the PLC stores these point data in the local database of the data acquisition tool, sleeps for 100ms and then returns to step S501.

[0180] This disclosed embodiment provides a timed cleanup process for a data acquisition tool database. When the data acquisition tool program is started, a thread monitors the data acquisition tool device status information table in the database and automatically clears outdated data to prevent insufficient database memory. This process primarily consists of two parts: the local database and the data acquisition tool.

[0181] FIG6 is a schematic diagram of a process flow of performing a database regular cleanup on a data acquisition tool according to an embodiment of the present disclosure. As shown in FIG6 , the process flow of performing a database regular cleanup on a data acquisition tool may be implemented through steps S601 to S606:

[0182] Step S601: Check whether the database connection is normal.

[0183] In some embodiments, it is first determined whether the connection between the local database and the data acquisition tool is normal. If the local database connection is abnormal, step S603 is executed, an abnormality log is written once, and then the system sleeps for 5 seconds and returns to step S601; if the local database connection is normal, step S602 is executed.

[0184] Step S602: Query key point data about the device.

[0185] In some embodiments, the key point data of the device refers to the device operating status and device downtime reasons stored in the local database. If the database connection is normal, the device status record (device_state_record) will be queried in the database.

[0186] Step S603: Write an error log.

[0187] Step S604: Determine whether the key point data is older than one month.

[0188] In some embodiments, in order to ensure that the data in the database does not cause low efficiency of the data acquisition tool due to excessive data, it is necessary to clear the data in the local database older than one month. Therefore, it is necessary to determine whether the key point data is older than 1 month. If it is older than 1 month, execute step S605.

[0189] Step S605: call the database.

[0190] Step S606: Delete the corresponding record.

[0191] In some embodiments, when the data acquisition tool finds that there is data older than one month in the local database, it calls the database to delete the data older than one month.

[0192] This disclosed embodiment provides a device status collection and upload process. When the program starts, a data acquisition tool thread collects corresponding points in the PLC. When a device status point changes, the relevant data is packaged and uploaded to a Kafka server. The centralized control system also has a thread that continuously subscribes to data from the corresponding topic in the Kafka server to update device status information and statistical results. The device status collection and upload process primarily consists of three components: the PLC, the data acquisition tool, and the centralized control system.

[0193] FIG7 is a schematic diagram of a device status collection and upload process according to an embodiment of the present disclosure. As shown in FIG7 , the device status collection and upload process may be implemented through steps S701 to S714:

[0194] Step S701: Check whether the PLC connection is normal.

[0195] In some embodiments, the data acquisition tool of the industrial computer determines whether the connection status between the PLC and the data acquisition tool is normal. If the PLC connection is abnormal, the PLC disconnection status will be written into the error log, and step S701 will be repeated after sleeping for 1000ms; if the connection status is normal, step S702 will be executed.

[0196] Step S702: Read the PLC position.

[0197] In some embodiments, reading the PLC point here means instructing the PLC to read the equipment operation status point on the production line to determine whether the equipment status is consistent with the last time.

[0198] Step S703: Check whether the device status is consistent with the last time.

[0199] In some embodiments, a consistent state with the previous one indicates that the device is operating stably and has not stopped. In this case, after a 100ms sleep, step S701 is executed again. A inconsistent state with the previous one indicates that the device has changed, possibly to a stop or a change from production to waiting for material. In this case, it is necessary to read the device's three-color indicator light and the reason for the device stop to determine whether a stop has occurred, its duration, and the reason for the stop.

[0200] Step S704: Close the thread monitoring the fixed LOSS and read the PLC point.

[0201] In some embodiments, when the equipment operating status is inconsistent with the last equipment status, it means that the equipment has changed, which may be a shutdown or a change from a production status to a waiting status. At this time, it is necessary to read the equipment's three-color light and the reason for the equipment shutdown to determine whether a shutdown has occurred and the duration and reason of the shutdown.

[0202] Step S705: Check whether the device status changes from non-shutdown to shutdown.

[0203] Here, it can be determined based on the three-color light of the device whether the device is currently in shutdown mode. If so, step S706 is executed; if not, step S707 is executed.

[0204] Step S706: Read the alarm point array.

[0205] In some embodiments, the alarm point array includes the alarm points of all production equipment corresponding to the industrial computer. By reading the alarm point array and comparing the read alarm point array with the alarm points configured in the industrial computer, it is possible to determine the specific alarm point that was triggered, and then determine the cause of the shutdown.

[0206] Step S707: If the shutdown reason is 0, the alarm information is set to default and uploaded together with the three-color light information.

[0207] In some embodiments, if the device is not in a non-shutdown state but is shut down, the alarm information is set to default and uploaded to a designated topic (eg, device operation status topic) in the Kafka server together with the three-color light information.

[0208] Step S708: Detect whether the configured alarm point is triggered.

[0209] After reading the alarm point array, the read alarm point array is compared with the alarm points configured in the industrial computer to detect whether the configured alarm points are triggered. If so, the shutdown reason given by the PLC is uploaded to the specified topic in the Kafka server (for example, the equipment operation status topic).

[0210] Step S709: Package and upload the reasons for downtime.

[0211] Step S710: Start a thread to monitor fixed LOSS triggering.

[0212] In some embodiments, it is uncertain whether the equipment shutdown is due to a fault or a fixed LOSS (i.e., a non-fault shutdown). At this time, a thread needs to be started to monitor the fixed LOSS trigger to avoid the centralized control system analyzing the shutdown cause of the machine and analyzing the shutdown corresponding to the fixed LOSS, which leads to inaccurate analysis results.

[0213] Step S711: Subscribe to the corresponding Topic in Kafka.

[0214] In some embodiments, the centralized control system has a thread that continuously subscribes to data in a corresponding Topic (eg, a device operation status topic) in a Kafka server to update device status information and statistical results.

[0215] Step S712: Obtain corresponding data.

[0216] Step S713: Calculate the duration of the last shutdown state.

[0217] Based on the acquired equipment operating status, three-color light data and equipment downtime reasons, the equipment downtime duration and downtime reasons can be obtained, and then comparisons can be made between different machines.

[0218] Step S714: Create a new record about the start of the new device state.

[0219] This disclosed embodiment provides a process for monitoring the status of fixed-loss devices. Once the thread is started, the data acquisition tool continuously monitors the trigger point corresponding to the fixed loss (a Boolean value in the PLC). When the trigger point is True, the data is uploaded to the centralized control system. The centralized control system also has a thread that continuously subscribes to data in the corresponding Topic to update device status information and statistical results. This function primarily consists of the data acquisition tool, PLC, and centralized control system.

[0220] FIG8 is a schematic diagram of a fixed LOSS device status monitoring process according to an embodiment of the present disclosure. As shown in FIG8 , the fixed LOSS device status monitoring process may be implemented through steps S801 to S810:

[0221] Step S801: Check whether the PLC connection is normal.

[0222] In some embodiments, the data acquisition tool of the industrial computer determines whether the connection status between the PLC and the data acquisition tool is normal. If the PLC connection is abnormal, the PLC disconnection status will be written into the error log, and step S801 will be repeated after sleeping for 1000ms; if the connection status is normal, step S802 will be executed.

[0223] Step S802: Read the PLC point.

[0224] In some embodiments, reading the PLC point here means instructing the PLC to read the fixed LOSS point on the production line and determine whether the fixed LOSS point is triggered.

[0225] Step S803: Check whether LOSS is True.

[0226] In some embodiments, if the fixed LOSS trigger point is False, the process returns to step S801 after sleeping for 100 ms; if the fixed LOSS trigger point is True, the process executes step S804.

[0227] Step S804: Read the PLC position.

[0228] In some embodiments, reading the PLC point here refers to reading the three-color light of the device, the reason for the device shutdown, and the last word of the alarm array, where the last word contains the reason for the fixed LOSS.

[0229] Step S805: parse Word and extract fixed LOSS information.

[0230] In the disclosed embodiment, the reason for the downtime of the fixed LOSS can be obtained by parsing the last word.

[0231] Step S806: Pack and fix the LOSS information.

[0232] In some embodiments, the downtime reason of the fixed LOSS is uploaded to the corresponding Topic (eg, the fixed LOSS topic) in the Kafka server.

[0233] Step S807: Subscribe to the corresponding Kafka Topic.

[0234] In some embodiments, the centralized control system has a thread that continuously subscribes to data in the corresponding Topic (for example, the fixed LOSS topic) in the Kafka server, which is used to determine the duration of the fixed LOSS based on the data in the aforementioned embodiments and to modify the duration of the data failure shutdown in the machine.

[0235] Step S808: Pull corresponding data.

[0236] Step S809: Calculate the duration of the last state.

[0237] Step S810: Create a new record about the start of a new device state.

[0238] The disclosed embodiment collects the equipment status by the industrial control computer on the machine and uploads it to the Kafka server via the Kafka protocol. The centralized control system subscribes to the Kafka server so that each time the equipment stops, the corresponding equipment stop reason can be queried; the centralized control system can simply count the equipment status according to normal production, waiting for material, material blockage and shutdown, and can also be subdivided into specific shutdown reasons, making the data more accurate and traceable more convenient. After the centralized control system receives the equipment status of each machine's corresponding equipment, it stores it in the database of the centralized control system with the equipment resource number as the primary key. The centralized control system provides an information query interface, which can be used to count the various statuses of a single device; it can also be used to select multiple devices for horizontal comparison. When the equipment on the production line triggers a shutdown, the industrial control computer on the machine will immediately upload the equipment status once, and then start a thread to monitor the fixed LOSS trigger point. If the on-site operator selects the shutdown reason corresponding to the fixed LOSS on the touch screen, it will be monitored and collected, and the data about the fixed LOSS will be uploaded to the centralized control system again. In this way, the centralized control system can count the relevant information of the fixed LOSS.

[0239] The above description is merely an embodiment of the present disclosure and is not intended to limit the scope of protection of the present disclosure. Any modifications, equivalent replacements, and improvements made within the spirit and scope of the present disclosure are included in the scope of protection of the present disclosure. Industrial Applicability

[0240] The disclosed embodiments provide a data processing system and method, wherein the data processing system includes multiple industrial computers and a centralized control system. The industrial computers are used to obtain the equipment operating status of the production equipment corresponding to the industrial computers. When the equipment operating status is different from the previous equipment operating status of the production equipment, the equipment operating data of the production equipment is obtained. When the equipment operating data indicates that the production equipment has changed from a first state to a second state, the equipment change reason of the production equipment is obtained. Based on the equipment change reason and the equipment operating data, equipment-related data is generated and uploaded to the centralized control system. The centralized control system is used to analyze and compare the equipment-related data of the multiple industrial computers to obtain a comparison result of the operating status of the production equipment corresponding to the multiple industrial computers on the battery production line. In this way, the centralized control system can query and compare the operating status of the production equipment on the production line without having to obtain data locally each time.

Claims

1. A data processing system, the data processing system being applied to a battery production line; The data processing system comprises: An industrial computer, used to obtain the equipment operating status of the production equipment corresponding to the industrial computer; The battery production line includes multiple industrial computers; The industrial computer is further configured to obtain the equipment operation data of the production equipment when the equipment operation state is different from the equipment operation state of the production equipment last time; The industrial computer is further configured to obtain a reason for a change in the production equipment when the equipment operation data indicates that the production equipment has changed from a first state to a second state; The industrial computer is further configured to generate device-related data based on the device change reason and the device operation data, and upload the device-related data to the centralized control system; The centralized control system is used to analyze and compare the equipment-related data of the multiple industrial computers to obtain a comparison result of the operating status of the production equipment corresponding to the multiple industrial computers on the battery production line.

2. The data processing system according to claim 1, wherein: The system further includes a controller; wherein, The industrial computer is further used to detect the communication channel between the industrial computer and the controller to obtain a detection result; The industrial computer is further configured to trigger a device operation status point in the controller when the detection result indicates that the communication channel is normal; The controller is used to obtain the equipment operation status of the production equipment corresponding to the industrial computer when the equipment operation status point is triggered, and send the equipment operation status to the industrial computer.

3. The data processing system according to claim 1 or 2, wherein: The data processing system also includes a publish-subscribe service; wherein, The industrial computer is further configured to associate the state change time when the production equipment changes to the second state and the state duration of the production equipment in the second state in the equipment operation data with the equipment resource number of the industrial computer to obtain the equipment association data; The industrial computer is further configured to upload the device-related data to the operating status topic of the publish-subscribe service; wherein the centralized control system subscribes to the operating status topic; The centralized control system is configured to obtain the device-associated data when the device-associated data appears in the operating status topic.

4. A data processing method, applied to a data processing system; The data processing method includes: The industrial computer obtains the equipment operation status of the production equipment corresponding to the industrial computer; the battery production line includes multiple industrial computers; When the equipment operation state is different from the last equipment operation state of the production equipment, the industrial computer obtains equipment operation data of the production equipment; When the equipment operation data indicates that the production equipment changes from a first state to a second state, the industrial computer obtains a reason for the equipment change of the production equipment; The industrial computer generates device-related data based on the device change reason and the device operation data, and uploads the device-related data to the centralized control system; The centralized control system analyzes and compares the equipment-related data of the multiple industrial computers to obtain a comparison result of the operating states of the production equipment corresponding to the multiple industrial computers on the battery production line.

5. The data processing method according to claim 4, wherein: The industrial computer obtains the equipment operation status of the production equipment corresponding to the industrial computer, including: The industrial computer detects the communication channel between the industrial computer and the controller to obtain a first detection result; When the first detection result indicates that the communication channel is normal, the industrial computer triggers the device operation status point in the controller; When the equipment operation status point is triggered, the controller obtains the equipment operation status of the production equipment corresponding to the industrial computer and sends the equipment operation status to the industrial computer.

6. The data processing method according to claim 4 or 5, wherein: The first state includes a plurality of first operating states; The data processing method further includes: In a case where the equipment operation data indicates that the production equipment changes between the multiple first operation states, the industrial computer determines the operation time corresponding to each first operation state of the production equipment based on the equipment operation data; The industrial computer associates the operating time corresponding to each first operating state of the production equipment with the equipment resource number of the industrial computer to obtain operating association data; The industrial computer sends the operation-related data to the centralized control system.

7. The data processing method according to any one of claims 4 to 6, wherein: The industrial computer obtains the reason for the equipment change of the production equipment, including: The industrial computer obtains an alarm array in the controller; the alarm array includes multiple alarm points; The industrial computer compares the alarm array with a local alarm array configured for the industrial computer, and determines a target alarm point corresponding to when the production equipment changes from the first state to the second state among the multiple alarm points; The industrial computer determines the alarm cause corresponding to the target alarm point as an equipment change cause of the production equipment.

8. The data processing method according to claim 7, wherein: The alarm array includes a plurality of alarm values, the plurality of alarm values ​​correspond to a plurality of alarm points, and each alarm point corresponds to an alarm level; The industrial computer compares the alarm array with a local alarm array configured for the industrial computer, and determines, from the multiple alarm points, a target alarm point corresponding to when the production equipment changes from a first state to a second state, including: The industrial computer compares the multiple alarm values ​​of the alarm array with the multiple alarm values ​​of the local alarm array configured by the industrial computer, and determines the alarm point where the alarm value in the alarm array changes as the initial alarm point; The industrial computer determines, based on the alarm levels of the initial alarm points, an alarm point whose alarm level satisfies an equipment change condition among the initial alarm points as the target alarm point.

9. The data processing method according to any one of claims 4 to 8, wherein: The equipment operation data at least includes the state change time when the production equipment changes to the second state and the state duration of the production equipment in the second state; The industrial computer generates device-related data based on the device change reason and the device operation data, and uploads the device-related data to the centralized control system, including: The industrial computer associates the state change time, the state duration and the device resource number of the industrial computer to obtain the device association data; The industrial computer uploads the device-related data to the operating status topic of the publish-subscribe service; wherein the centralized control system subscribes to the operating status topic; When the device-related data appears in the running status topic, the centralized control system obtains the device-related data.

10. The data processing method according to claim 9, wherein: The data processing method further includes: In the case where the running status topic contains device-related data uploaded by multiple industrial computers, the publish-subscribe service sorts the device-related data uploaded by the multiple industrial computers based on the preset priority of each industrial computer to form a data sequence; Correspondingly, the centralized control system obtains the device-related data, including: The centralized control system sequentially obtains the plurality of device-related data in the operation status topic based on the data sequence.

11. The data processing method according to any one of claims 4 to 10, wherein: The data processing method further includes: When the communication channel between the industrial computer and the controller is normal and the emergency stop point in the controller is triggered, the industrial computer obtains the equipment emergency stop data in the controller; The industrial computer uploads the equipment emergency stop data to the emergency stop topic of the publish-subscribe service; wherein the centralized control system subscribes to the emergency stop topic, and the emergency stop topic contains the equipment emergency stop data corresponding to the multiple industrial computers on the battery production line; When the equipment emergency stop data appears in the emergency stop topic, the centralized control system obtains the equipment emergency stop data to obtain the equipment emergency stop data corresponding to the multiple industrial computers.

12. The data processing method according to any one of claims 4 to 11, wherein: The data processing method further includes: When the communication channel between the industrial computer and the controller is normal, the industrial computer periodically obtains the equipment operation data of the production equipment and stores the equipment operation data in a database of the industrial computer.

13. The data processing method according to claim 12, wherein: The data processing method further includes: The industrial computer detects the connection channel between the industrial computer and the database to obtain a second detection result; If the second detection result indicates that the connection channel is normal, the industrial computer determines a storage date of the device operation data in the database; The industrial computer deletes the device operation data in the database whose storage date meets the storage condition based on the storage date, so as to clean up the device operation data in the database.

14. The data processing method according to any one of claims 4 to 13, wherein: The data processing method further includes: The industrial computer determines the maximum number of available threads in the thread pool corresponding to the industrial computer and the required number of threads for obtaining the running status of the device; When the required number of threads is less than or equal to the maximum number of available threads, the industrial computer obtains the operating status of the device; When the required number of threads is greater than the maximum number of available threads, the industrial computer shuts down the thread for data cleanup or waits until the required number of threads is less than or equal to the maximum number of available threads.

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