A data processing method and system for PLC controller functional modules

Abstract

This invention proposes a PLC controller functional module data processing method and system, belonging to the field of functional module data processing technology. It classifies the control task information and functional module information of the PLC controller, calculates the control adaptability, and associates control task groups and functional module groups to obtain control association groups. A data processing chain is established for the functional module groups based on the control task information, and the data processing sequence of the functional module groups is marked with serial numbers. The functional module groups process data according to the associated control task information to obtain the final processed data, which is then sent to the central processing unit. Data processing anomalies are calculated and compared with preset anomaly thresholds. Based on the comparison results, data processing annotations are added to the functional modules to obtain data processing annotation information, thereby determining whether data reprocessing is necessary. This invention achieves efficient and effective control of data processing by the functional modules of the PLC controller, improving the reliability and stability of the system.

Description

Technical Field

[0001] This invention proposes a PLC controller functional module data processing method and system, which relates to the field of functional module data processing technology. Background Technology

[0002] With the rapid development of industrial automation and intelligence, programmable logic controllers (PLCs) are playing an increasingly important role in industrial automation control systems. PLC controllers receive control task information and control various functional modules to process data, thereby achieving automated control of industrial production. However, in practical applications, how to efficiently process and control large amounts of control task information, and how to effectively associate control tasks with functional module groups, remain significant challenges for PLC control systems. In existing PLC control systems, control task information and functional module information are often not clearly categorized and managed, making real-time data processing difficult and leading to inefficiencies and high error rates in control task allocation and functional module invocation. Furthermore, there is a lack of unified standards and effective methods for handling the data processing sequence of functional module groups and for dealing with outliers, further reducing the system's reliability and stability. Summary of the Invention

[0003] This invention provides a PLC controller functional module data processing method and system to address the problems in existing PLC control systems where control task information and functional module information are often not clearly classified and managed, leading to inefficiencies and high error rates in control task allocation and functional module invocation. Furthermore, the lack of unified standards and effective methods for handling the data processing sequence of functional module groups and the processing of outliers further reduces the system's reliability and stability.

[0004] This invention proposes a data processing method and system for a PLC controller functional module, the method comprising:

[0005] The control task information and functional module information of the PLC controller are classified, the control adaptability of the control task group and functional module group obtained by the classification is calculated, and the control task group and functional module group are associated according to the control adaptability to obtain the control association group.

[0006] A data processing chain for functional module groups is established based on the control task information. The functional module groups are labeled with the sequence number of the data processing order. The functional module groups process the data according to the associated control task information to obtain the processing data of each functional module, and then obtain the final processed data, which is sent to the central processing unit.

[0007] Calculate the data processing anomaly value for each functional module, compare the data processing anomaly value with the preset anomaly threshold, and label the data processing of the functional module according to the comparison result to obtain data processing labeling information, and then determine whether to perform data reprocessing.

[0008] Furthermore, the classification of the control task information and functional module information of the PLC controller includes:

[0009] The control task information of the PLC controller is obtained, the control task information is preprocessed to obtain preprocessed control task information, and the control task information is classified according to the type of control task to obtain multiple control task groups.

[0010] Obtain multiple functional modules of the PLC controller, classify the multiple functional modules according to their function types, and obtain multiple groups of functional modules.

[0011] Furthermore, the calculation of the control fit degree of the control task group and functional module group obtained through classification includes:

[0012] The control compatibility between the control task groups and the functional module groups is calculated based on the control task information of multiple control task groups and the functional information of the functional module groups.

[0013] The formula for calculating the control adaptability is:

[0014]

[0015] Where SP controls the matching degree, Y c To control the average required output data of the task group, Y r To control the average required input data for the task group, S c S represents the average actual output data of the functional module group. r This represents the average actual input data for the functional module group.

[0016] Further, the step of associating the control task group and the functional module group based on the control adaptability to obtain a control association group includes:

[0017] Obtain a preset adaptation threshold, compare the control adaptation with the preset adaptation threshold, and when the control adaptation is greater than the preset adaptation threshold, associate the corresponding control task group and functional module group to obtain the corresponding control association group.

[0018] When the control adaptability is less than or equal to the preset adaptability threshold, the corresponding control task group and functional module group are not associated.

[0019] Furthermore, the step of establishing a data processing chain for functional module groups based on control task information, and marking the data processing sequence of functional module groups with serial numbers, includes:

[0020] Based on the control task information corresponding to multiple functional module groups in the control association group, the control sequence of multiple functional module groups is connected to obtain the data processing chain.

[0021] Each functional module group in the data processing chain is labeled with a sequence number indicating its data processing order, thus obtaining functional module labeling information. Further, the functional module group processes data according to associated control task information to obtain the processing data for each functional module, thereby obtaining the final processed data, which is then sent to the central processing unit, including:

[0022] Suppose there are n functional module groups in total. The nth functional module group performs data processing for the corresponding function based on the control task information of the control task group associated with it, and obtains the processed data of the nth functional module group.

[0023] Send the processing data of the nth functional module group to the (n-1)th functional module group;

[0024] The data is retrieved from all functional modules in the order of the data processing chain and sent to the central processing unit.

[0025] Furthermore, the step of acquiring the processing data of all functional modules in the order of the data processing chain and sending it to the central processing unit includes:

[0026] The (n-1)th functional module group performs data processing for its corresponding function based on the control task information of its associated control task group, and obtains the processing data of the (n-1)th functional module group. This process continues until all functional module groups have completed data processing and all functional module processing data has been obtained. The processing data of the last functional module to perform data processing is the final processing data. All functional module processing data and the final processing data are then sent to the central processing unit.

[0027] Further, the step of calculating data processing anomalies for each functional module, comparing the data processing anomalies with a preset anomaly threshold, and labeling the functional modules based on the comparison results to obtain data processing labeling information includes:

[0028] The central processing unit calculates the data processing anomaly value for each functional module based on the processing data acquired from each functional module;

[0029] The comparison results are obtained by comparing the data processing anomalies with the preset anomaly threshold.

[0030] The formula for calculating outliers in data processing is as follows:

[0031]

[0032] Where CY represents outliers in data processing, L represents the total number of data processing categories, and SC represents... i YC represents the actual output data of the i-th data processing functional module. i Preset output data for the i-th data processing functional module, SR i YR is the actual input data for the i-th type of data processing functional module. i Preset input data for the i-th type of data processing functional module;

[0033] When the abnormal value of the data processing exceeds the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as abnormal.

[0034] When the abnormal value of the data processing is less than or equal to the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as normal processing. The abnormal processing label and the normal processing label are the data processing label information.

[0035] Furthermore, the step of obtaining data processing annotation information and then determining whether to perform data reprocessing includes:

[0036] When the data processing label information is normal, the central processing unit processes the final processed data according to the preset program;

[0037] When the data processing label information indicates an anomaly, the central processing unit generates control instructions to control the data processing chain to reprocess the data.

[0038] Furthermore, the system includes:

[0039] The control function association module is used to classify the control task information and function module information of the PLC controller, calculate the control compatibility of the control task group and function module group obtained by classification, and associate the control task group and function module group according to the control compatibility to obtain the control association group.

[0040] The functional data processing module is used to establish a data processing chain for the functional module group based on the control task information, mark the sequence number of the data processing order of the functional module group, and the functional module group processes the data according to the associated control task information to obtain the processing data of each functional module, thereby obtaining the final processed data and sending it to the central processing unit.

[0041] The anomaly labeling and judgment module is used to calculate the data processing anomaly value of each functional module, compare the data processing anomaly value with the preset anomaly threshold, and label the data processing of the functional module according to the comparison result to obtain data processing labeling information, and then determine whether to perform data reprocessing.

[0042] The beneficial effects of this invention are as follows: By intelligently classifying and associating control tasks with functional modules, the system ensures that each control task is processed by the most suitable functional module, thereby improving resource utilization efficiency. The establishment and execution of the data processing chain ensures efficient data transfer and processing between functional modules, reducing unnecessary waiting time and data transmission delays, and improving overall processing efficiency. Through anomaly detection and handling mechanisms, the system can promptly detect and handle anomalies during data processing, avoiding data errors or system crashes, thus enhancing system stability and reliability. Finally, the processed data provides crucial decision support information to the central processing unit, helping the system make more accurate decisions and control actions, and improving the system's intelligence level. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of a data processing method for a PLC controller functional module. Detailed Implementation

[0044] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0045] In one embodiment of the present invention, a data processing method and system for a PLC controller functional module is provided, the method comprising:

[0046] S1. Classify the control task information and functional module information of the PLC controller, calculate the control compatibility of the control task group and functional module group obtained by classification, and associate the control task group and functional module group according to the control compatibility to obtain the control association group.

[0047] S2. Establish a data processing chain for the functional module group based on the control task information, mark the sequence number of the data processing order for the functional module group, and the functional module group processes the data according to the associated control task information to obtain the processing data of each functional module, thereby obtaining the final processing data and sending it to the central processing unit.

[0048] S3. Calculate the data processing anomaly value for each functional module, compare the data processing anomaly value with the preset anomaly threshold, and mark the data processing of the functional module according to the comparison result to obtain the data processing annotation information, and then determine whether to perform data reprocessing.

[0049] The working principle of the above technical solution is as follows: The system first classifies the control task information and functional module information of the PLC controller. Classification is based on factors such as the type of task control and the functional type of the functional modules. The control fit between the classified control task groups and functional module groups is calculated. Based on the control fit, the system associates the control task groups with the functional module groups, forming control association groups. The purpose of association is to ensure that each control task can be processed by the most suitable functional module. Based on the control task information, the system establishes a data processing chain for each control association group. The data processing chain defines the data processing order between functional modules. The system assigns a sequence number to each functional module to identify its position in the data processing chain. The functional module group processes data according to the associated control task information and the predetermined data processing order. After each functional module finishes processing the data, it passes the result to the next module until the final processed data is obtained. The final processed data is sent to the central processing unit. The system calculates the outliers for each functional module during data processing. The calculated outliers are compared with a preset outlier threshold. If the outlier exceeds the threshold, the data processing is considered abnormal. Based on the comparison results, the system annotates the functional modules with data processing information, generating data processing annotation information. The system then determines whether reprocessing of the data is necessary based on this annotation information. If reprocessing is required, the system may reselect the functional modules, adjust the processing order, or take other measures to ensure the accuracy and reliability of the data processing.

[0050] The technical effects of the above solution are as follows: By intelligently classifying and associating control tasks with functional modules, the system ensures that each control task is processed by the most suitable functional module, thereby improving resource utilization efficiency. The establishment and execution of the data processing chain ensures efficient data transfer and processing between functional modules, reducing unnecessary waiting time and data transmission delays, and improving overall processing efficiency. Through anomaly detection and handling mechanisms, the system can promptly detect and handle anomalies during data processing, avoiding data errors or system crashes, and enhancing system stability and reliability. Finally, the processed data provides crucial decision support information to the central processing unit, helping the system make more accurate decisions and control actions, thus improving the system's intelligence level.

[0051] In one embodiment of the present invention, the classification of control task information and functional module information of the PLC controller includes:

[0052] The control task information of the PLC controller is obtained, the control task information is preprocessed to obtain preprocessed control task information, and the control task information is classified according to the type of control task to obtain multiple control task groups.

[0053] Obtain multiple functional modules of the PLC controller, classify the multiple functional modules according to their function types, and obtain multiple groups of functional modules.

[0054] The working principle of the above technical solution is as follows: acquire the control task information of the PLC controller, preprocess the control task information to obtain preprocessed control task information, classify the control task information according to the type of control task to obtain multiple control task groups; the control task includes control data acquisition, control data communication, control data storage, control data preprocessing, and data processing according to preset logic rules, etc.

[0055] The PLC controller's multiple functional modules are obtained and categorized according to their functions, resulting in multiple groups of functional modules. These functional modules include data acquisition modules, data processing modules, data communication modules, and data logic operation modules, used to implement corresponding data processing functions.

[0056] The technical effects of the above solution are as follows: By preprocessing and classifying control task information, different types of control tasks, such as data acquisition, data communication, and data storage, can be clearly identified. This helps the system process these tasks more efficiently, avoiding processing delays or resource waste caused by mixed tasks. Classifying the PLC controller's functional modules according to their function ensures that each module is assigned to the most suitable task. This helps optimize system resource allocation, improve resource utilization, and reduce unnecessary resource waste. Categorizing and managing control task information and functional modules makes the system structure clearer, facilitating understanding and operation by maintenance personnel. When the system malfunctions or needs upgrading, maintenance personnel can quickly locate the problem and take appropriate measures to reduce the impact of the malfunction on normal system operation. Classifying functional modules according to their function allows for easy addition, deletion, or modification to adapt to different control task requirements. This enhances the system's flexibility, enabling it to cope with various complex and changing control scenarios. Unified management and classification of control task information and functional modules helps achieve data standardization. Standardized data formats and interfaces can improve the efficiency and accuracy of data exchange and reduce the risk of data errors. By categorizing and managing control task information and functional modules, access and transmission permissions for data can be controlled more precisely. This helps prevent unauthorized access and data leaks, thereby improving system security.

[0057] In one embodiment of the present invention, the calculation of the control fit degree of the control task group and functional module group obtained through classification includes:

[0058] The control compatibility between the control task groups and the functional module groups is calculated based on the control task information of multiple control task groups and the functional information of the functional module groups.

[0059] The formula for calculating the control adaptability is:

[0060]

[0061] Where SP controls the matching degree, Y c To control the average required output data of the task group, Y r To control the average required input data for the task group, S c S represents the average actual output data of the functional module group. r This represents the average actual input data for the functional module group.

[0062] The working principle of the above technical solution is as follows: Based on the steps mentioned earlier, the PLC controller's control tasks are divided into multiple control task groups, and the functional modules are also divided into multiple functional module groups. Each control task group contains one or more similar control tasks, while each functional module group contains modules capable of performing specific functions. To determine which functional module groups are best suited to execute which control task groups, their control fit needs to be calculated. This typically involves comparing and evaluating the requirements of the task groups with the capabilities of the functional module groups. A higher fit value indicates that the functional module group is more suitable for executing that control task group. Based on these fit values, the system can decide how to allocate functional modules to execute control tasks.

[0063] The technical effects of the above solution are as follows: By calculating control adaptability, the system can more accurately determine which functional modules are best suited to perform which control tasks. This helps optimize resource allocation, ensuring that each functional module is used to perform its best tasks. Functional module groups with high adaptability can more effectively execute corresponding control tasks, thereby reducing resource waste and task execution time. This helps improve the efficiency of the entire PLC control system. By matching the most suitable functional modules to execute control tasks, the risk of system failures due to insufficient resources or module mismatch can be reduced. This helps improve the reliability and stability of the system. Through a clear adaptability calculation and allocation process, system design and maintenance become simpler and more intuitive. Maintenance personnel can more easily understand the system's structure and functions and quickly locate and resolve potential problems.

[0064] In one embodiment of the present invention, the step of associating control task groups and functional module groups according to the control adaptability to obtain a control association group includes:

[0065] Obtain a preset adaptation threshold, compare the control adaptation with the preset adaptation threshold, and when the control adaptation is greater than the preset adaptation threshold, associate the corresponding control task group and functional module group to obtain the corresponding control association group.

[0066] When the control adaptability is less than or equal to the preset adaptability threshold, the corresponding control task group and functional module group are not associated.

[0067] The working principle of the above technical solution is as follows: The system obtains an adaptation threshold from preset parameters or configurations. This threshold is usually set based on factors such as the system's actual needs, performance, and stability requirements. The system compares the previously calculated control adaptation with this preset adaptation threshold. Control adaptation is calculated by evaluating the degree of matching between the requirements of a control task group and the capabilities of a functional module group. If the control adaptation between a control task group and a functional module group is greater than the preset adaptation threshold, the system considers that the functional module group can well meet the requirements of the control task group, and therefore associates them to form a control association group. This association group represents a task-resource matching relationship, meaning that this functional module group will be used to execute this control task group. Conversely, if the control adaptation between a control task group and a functional module group is less than or equal to the preset adaptation threshold, the system considers that the functional module group cannot meet the requirements of the control task group, or the degree of satisfaction is insufficient. In this case, the system will not associate them, but will continue to look for other more suitable functional module groups, or consider optimizing the requirement description of the control task group to improve the adaptation.

[0068] The technical effects of the above solution are as follows: By matching tasks and resources based on adaptability, more rational utilization of system resources can be ensured. High-adaptability association groups indicate efficient resource utilization, while tasks with low adaptability will not be allocated resources, thus avoiding resource waste. High-adaptability association groups mean a high degree of matching between tasks and resources, enabling faster task completion and improving system execution efficiency. Simultaneously, it avoids task execution delays or failures due to resource mismatch. By rationally matching tasks and resources, the risk of system failures due to insufficient resources or task overload can be reduced. This helps enhance system stability and reliability. This method allows the system to dynamically adjust the matching relationship between tasks and resources according to actual needs. When system requirements change, the adaptability threshold can be adjusted or the task requirement description optimized to adapt to new requirements, maintaining system flexibility and scalability. By managing tasks and resources in association, system management and maintenance can be simplified.

[0069] In one embodiment of the present invention, the step of establishing a data processing chain for a functional module group based on control task information and marking the data processing sequence of the functional module group with serial numbers includes:

[0070] Based on the control task information corresponding to multiple functional module groups in the control association group, the control sequence of multiple functional module groups is connected to obtain the data processing chain.

[0071] Each functional module group in the data processing chain is labeled with a sequence number representing the data processing order, thus obtaining the functional module labeling information.

[0072] The working principle of the above technical solution is as follows: The system determines the control task information corresponding to each functional module group based on the control association groups formed in the previous steps. This control task information describes the specific tasks and data processing requirements that the functional module group needs to perform. The system determines the execution order between functional module groups based on the dependencies and logical order between control tasks. This order is based on the logical flow of the tasks and the requirements of the data flow. According to the determined execution order, the system connects the functional module groups to form a complete data processing chain. This chain represents the entire processing flow from data input to output. In the data processing chain, the system assigns a unique sequence number to each functional module group to indicate its position and order in the data processing flow. This sequence number is usually based on the actual position of the functional module group in the chain. The system associates the sequence number with the information of the functional module group to generate functional module labeling information. This labeling information contains key information such as the unique identifier of the functional module group, the sequence number, and the data type processed.

[0073] The technical effects of the above solution are as follows: By forming a data processing chain and generating functional module annotation information, the system can clearly display the relationships and order between various functional module groups in the data processing flow. By optimizing the connection order between functional module groups and the data processing flow, the system can process data more efficiently. This helps reduce data processing delays and errors, improving the overall performance of the system. The functional module annotation information facilitates system maintenance and management. Specific functional module groups can be quickly located, and their related processing order and data types can be viewed. This helps simplify maintenance processes and improve management efficiency. When the system needs to add new functional modules or modify existing functions, it can adapt to new requirements by adjusting the data processing chain and updating the functional module annotation information. This flexibility enables the system to cope with constantly changing business needs and technical environments. Through annotation information, the system can achieve real-time monitoring and tracking of the data processing flow. Administrators can view the status and processing progress of each functional module group in real time, promptly identifying and resolving problems. This helps improve the stability and reliability of the system.

[0074] In one embodiment of the present invention, the functional module group performs data processing based on associated control task information to obtain processing data for each functional module, thereby obtaining final processing data, which is then sent to the central processing unit, including:

[0075] Suppose there are n functional module groups in total. The nth functional module group performs data processing for the corresponding function based on the control task information of the control task group associated with it, and obtains the processed data of the nth functional module group.

[0076] Send the processing data of the nth functional module group to the (n-1)th functional module group;

[0077] The data is retrieved from all functional modules in the order of the data processing chain and sent to the central processing unit.

[0078] The working principle of the above technical solution is as follows: Based on the control task information, the nth functional module group (where n is the number of functional module groups, and it is assumed that they have been numbered according to the processing order) begins to perform data processing for its corresponding function. This processing includes data acquisition, conversion, storage, communication, or logical operations. After completing the data processing for its corresponding function, the nth functional module group generates processed data. This data may be intermediate results, status information, or raw data that requires further processing. The processed data of the nth functional module group is sent to the previous functional module group in the data processing chain, namely the (n-1)th functional module group. This ensures that data is transmitted between functional module groups in the correct order and logic. After receiving the data, each functional module group performs corresponding data processing according to its own function and control task information, and continues to send the processed data to the previous functional module group in the data processing chain until the data reaches the first functional module group. After completing its data processing, the first functional module group sends the final processed data to the central processing unit (CPU). The CPU is responsible for the control and data processing of the entire system. It receives the final processed data from all functional module groups and executes further processing or decisions as needed.

[0079] The technical effects of the above solution are as follows: By processing and transmitting data according to the data processing chain sequence, the orderliness and correctness of the data are ensured. Each functional module group processes data at its appropriate location and time, thereby improving the accuracy and efficiency of data processing. Modular design allows for parallel processing and pipelined operations, reducing the total data processing time. Simultaneously, since each functional module group only handles its specific task, its internal algorithms and hardware design can be optimized, further improving processing efficiency. By associating functional module groups with control task groups, the system can flexibly adjust the data processing flow to adapt to different control task requirements. Furthermore, when adding new functions or modifying existing functions, only the relevant functional module groups need to be modified, without redesigning the entire system. Modular design makes system maintenance simpler and more intuitive. Administrators can test and debug each functional module group individually, making it easier to locate and resolve potential problems. Moreover, since the interfaces between functional module groups are standardized, functional module groups can be easily replaced or upgraded. By assigning data processing tasks to multiple functional module groups, the system can process multiple tasks in parallel, thereby improving system throughput and reliability. Furthermore, since each functional module group is independent, a failure in one functional module group will not affect the operation of the entire system.

[0080] In one embodiment of the present invention, the step of acquiring the processing data of all functional modules in the order of the data processing chain and sending it to the central processing unit includes:

[0081] The (n-1)th functional module group performs data processing for its corresponding function based on the control task information of its associated control task group, and obtains the processing data of the (n-1)th functional module group. This process continues until all functional module groups have completed data processing and all functional module processing data has been obtained. The processing data of the last functional module to perform data processing is the final processing data. All functional module processing data and the final processing data are then sent to the central processing unit.

[0082] The working principle of the above technical solution is as follows: When the system receives the instruction from the control task group, the nth functional module group in the data processing chain begins to perform data processing for its corresponding function based on its associated control task information. After completing processing, the nth functional module group passes the processed data to the next functional module group, i.e., the (n-1)th functional module group. After receiving the data, the (n-1)th functional module group processes the data according to its own control task information and continues to pass the processed data down. This process continues until the first functional module group completes its data processing task. The data generated by the last functional module group to perform data processing (i.e., the first functional module group) is considered the final processed data of the entire data processing flow. The system summarizes the processed data of each functional module group and the final processed data, and sends this data to the central processing unit (CPU).

[0083] The technical effects of the above solution are as follows: The system processes data according to a preset data processing chain sequence, ensuring the orderly flow of data between functional module groups and avoiding data chaos and errors. Each functional module group focuses on performing its specific task, making data processing more efficient. Simultaneously, because the data processing flow is serial, the integrity of data at each stage is ensured. By assigning data processing tasks to multiple functional module groups, the system can process multiple tasks in parallel, improving overall throughput and reliability. Furthermore, since each functional module group is independent, a failure in one functional module group will not immediately affect the operation of the entire system. Because the system stores the processing data of each functional module group, data traceability and auditing are convenient. This is very helpful for troubleshooting, system optimization, and compliance checks. Modular design simplifies system maintenance. Administrators can test, debug, and upgrade each functional module group individually without modifying the entire system. Moreover, because the interfaces between functional module groups are standardized, new functional module groups can be easily replaced or added. The system can adjust the association and control task information between functional module groups as needed to adapt to different application scenarios and changing requirements. This flexibility gives the system high configurability and scalability.

[0084] In one embodiment of the present invention, the step of calculating the data processing anomaly value of each functional module, comparing the data processing anomaly value with a preset anomaly threshold, and annotating the functional module with data processing information based on the comparison result to obtain data processing annotation information includes:

[0085] The central processing unit calculates the data processing anomaly value for each functional module based on the processing data acquired from each functional module;

[0086] The comparison results are obtained by comparing the data processing anomalies with the preset anomaly threshold.

[0087] The formula for calculating outliers in data processing is as follows:

[0088]

[0089] Where CY represents outliers in data processing, L represents the total number of data processing categories, and SC represents... i YC represents the actual output data of the i-th data processing functional module. i Preset output data for the i-th data processing functional module, SR i YR is the actual input data for the i-th type of data processing functional module. i Preset input data for the i-th type of data processing functional module;

[0090] When the abnormal value of the data processing exceeds the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as abnormal.

[0091] When the abnormal value of the data processing is less than or equal to the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as normal processing. The abnormal processing label and the normal processing label are the data processing label information.

[0092] The working principle of the above technical solution is as follows: After receiving the processed data from all functional module groups, the Central Processing Unit (CPU) analyzes and calculates the processed data of each functional module according to the data processing anomaly calculation formula to obtain the data processing anomaly value for each functional module. The calculated data processing anomaly value is compared with a preset anomaly threshold. This anomaly threshold is set according to system requirements and historical data and is used to determine whether the data processing of a functional module is abnormal. If the data processing anomaly value of a certain functional module is greater than the preset anomaly threshold, the system will mark the functional module as being in an abnormal processing state and generate a corresponding anomaly processing label. If the data processing anomaly value is less than or equal to the preset anomaly threshold, the system will mark the functional module as being in a normal processing state and generate a normal processing label.

[0093] The technical benefits of the above solution are as follows: By calculating data processing anomalies in functional modules and comparing them with anomaly thresholds, the system can monitor the operational status of functional modules in real time, promptly identifying and issuing warnings of potential anomalies. This helps administrators or maintenance personnel respond quickly and prevent problems from escalating. Through anomaly handling annotations, the system can accurately locate the problematic functional module, reducing troubleshooting time and costs. By promptly identifying and handling anomalies in functional modules, the system can ensure service continuity and stability, reducing the impact of system failures or service interruptions on user experience. Data processing anomalies and annotation information can serve as important bases for system performance evaluation, fault analysis, and optimization decisions. By collecting and analyzing this data, administrators can more scientifically formulate system maintenance and improvement strategies, enhancing the overall operational level of the system.

[0094] In one embodiment of the present invention, obtaining data processing annotation information and then determining whether to perform data reprocessing includes:

[0095] When the data processing label information is normal, the central processing unit processes the final processed data according to the preset program;

[0096] When the data processing label information indicates an anomaly, the central processing unit generates control instructions to control the data processing chain to reprocess the data.

[0097] The working principle of the above technical solution is as follows: When the Central Processing Unit (CPU) receives the data processing annotation information from all functional modules and confirms that all annotation information is processed normally, it will begin to further process the final processed data according to a preset program. If the CPU finds any abnormal processing annotations while checking the data processing annotation information, it will generate a control instruction. This control instruction will be sent to the relevant functional module group in the data processing chain, instructing them to reprocess the data. Data reprocessing may involve recollecting data, recalculating, or performing other necessary steps to ensure the accuracy and integrity of the data. After the data reprocessing is completed, the relevant functional module group will regenerate the processed data and update its data processing annotation information. Then, the CPU will re-evaluate the data processing annotation information of all functional modules and, as needed, re-execute normal processing or continue the data reprocessing cycle.

[0098] The technical effects of the above solution are as follows: Through anomaly handling and data reprocessing mechanisms, the system can ensure the accuracy and integrity of data. When a data processing anomaly is detected, the system can automatically trigger a data reprocessing process to correct errors in a timely manner, reducing decision-making mistakes or business losses caused by data errors. The central processing unit can automatically determine the normality or abnormality of data processing based on data processing annotation information and take corresponding processing measures. This automated and intelligent processing method can significantly improve the system's response speed and processing efficiency, reduce the need for manual intervention, and lower operation and maintenance costs. The system has strong fault recovery capabilities. When a data processing anomaly occurs in a functional module, the system can quickly identify and trigger a data reprocessing process, thereby ensuring the stability and reliability of the entire data processing chain. This fault recovery capability is crucial for ensuring the continuous operation of the system and the continuity of business. Through data processing annotation information and anomaly handling mechanisms, the system can provide administrators with detailed error information and processing suggestions. This helps administrators quickly locate problems, analyze the causes of problems, and take appropriate solutions. At the same time, the system can also record historical processing data and annotation information, providing strong support for subsequent troubleshooting and performance optimization. By ensuring data accuracy and system stability, the system can provide users with more reliable and higher-quality services. In the event of system failure or data anomalies, the system can quickly recover and continue providing services.

[0099] According to one embodiment of the present invention, the system includes:

[0100] The control function association module is used to classify the control task information and function module information of the PLC controller, calculate the control compatibility of the control task group and function module group obtained by classification, and associate the control task group and function module group according to the control compatibility to obtain the control association group.

[0101] The functional data processing module is used to establish a data processing chain for the functional module group based on the control task information, mark the sequence number of the data processing order of the functional module group, and the functional module group processes the data according to the associated control task information to obtain the processing data of each functional module, thereby obtaining the final processed data and sending it to the central processing unit.

[0102] The anomaly labeling and judgment module is used to calculate the data processing anomaly value of each functional module, compare the data processing anomaly value with the preset anomaly threshold, and label the data processing of the functional module according to the comparison result to obtain data processing labeling information, and then determine whether to perform data reprocessing.

[0103] The working principle of the above technical solution is as follows: The system first classifies the control task information and functional module information of the PLC controller. Classification is based on factors such as the type of task control and the functional type of the functional modules. The control fit between the classified control task groups and functional module groups is calculated. Based on the control fit, the system associates the control task groups with the functional module groups, forming control association groups. The purpose of association is to ensure that each control task can be processed by the most suitable functional module. Based on the control task information, the system establishes a data processing chain for each control association group. The data processing chain defines the data processing order between functional modules. The system assigns a sequence number to each functional module to identify its position in the data processing chain. The functional module group processes data according to the associated control task information and the predetermined data processing order. After each functional module finishes processing the data, it passes the result to the next module until the final processed data is obtained. The final processed data is sent to the central processing unit. The system calculates the outliers for each functional module during data processing. The calculated outliers are compared with a preset outlier threshold. If the outlier exceeds the threshold, the data processing is considered abnormal. Based on the comparison results, the system annotates the functional modules with data processing information, generating data processing annotation information. The system then determines whether reprocessing of the data is necessary based on this annotation information. If reprocessing is required, the system may reselect the functional modules, adjust the processing order, or take other measures to ensure the accuracy and reliability of the data processing.

[0104] The technical effects of the above solution are as follows: By intelligently classifying and associating control tasks with functional modules, the system ensures that each control task is processed by the most suitable functional module, thereby improving resource utilization efficiency. The establishment and execution of the data processing chain ensures efficient data transfer and processing between functional modules, reducing unnecessary waiting time and data transmission delays, and improving overall processing efficiency. Through anomaly detection and handling mechanisms, the system can promptly detect and handle anomalies during data processing, avoiding data errors or system crashes, and enhancing system stability and reliability. Finally, the processed data provides crucial decision support information to the central processing unit, helping the system make more accurate decisions and control actions, thus improving the system's intelligence level.

[0105] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A data processing method for a PLC controller functional module, characterized in that, The method includes: The control task information and functional module information of the PLC controller are classified, the control adaptability of the control task group and functional module group obtained by the classification is calculated, and the control task group and functional module group are associated according to the control adaptability to obtain the control association group. A data processing chain for functional module groups is established based on the control task information. The functional module groups are labeled with the sequence number of the data processing order. The functional module groups process the data according to the associated control task information to obtain the processing data of each functional module, and then obtain the final processed data, which is sent to the central processing unit. Calculate the data processing anomaly value for each functional module, compare the data processing anomaly value with the preset anomaly threshold, and label the data processing of the functional module according to the comparison result to obtain data processing labeling information, and then determine whether to reprocess the data. The process of calculating data processing anomalies for each functional module, comparing these anomalies with a preset anomaly threshold, and labeling the functional modules based on the comparison results to obtain data processing labeling information includes: The central processing unit calculates the data processing anomaly value for each functional module based on the processing data acquired from each functional module; The comparison results are obtained by comparing the data processing anomalies with the preset anomaly threshold. The formula for calculating outliers in data processing is as follows: Where CY represents outliers in data processing, L represents the total number of data processing categories, and SC represents... i YC represents the actual output data of the i-th data processing functional module. i Preset output data for the i-th data processing functional module, SR i YR is the actual input data for the i-th type of data processing functional module. i Preset input data for the i-th type of data processing functional module; When the abnormal value of the data processing exceeds the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as abnormal. When the abnormal value of the data processing is less than or equal to the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as normal processing. The abnormal processing label and the normal processing label are the data processing label information.

2. The PLC controller functional module data processing method according to claim 1, characterized in that, The classification of control task information and functional module information of the PLC controller includes: The control task information of the PLC controller is obtained, the control task information is preprocessed to obtain preprocessed control task information, and the control task information is classified according to the type of control task to obtain multiple control task groups. Obtain multiple functional modules of the PLC controller, classify the multiple functional modules according to their function types, and obtain multiple groups of functional modules.

3. The PLC controller functional module data processing method according to claim 1, characterized in that, The calculation of the control fit degree of the control task group and functional module group obtained by classification includes: The control compatibility between the control task groups and the functional module groups is calculated based on the control task information of multiple control task groups and the functional information of the functional module groups. The formula for calculating the control adaptability is: Where SP controls the matching degree, Y c To control the average required output data of the task group, Y r To control the average required input data for the task group, S c S represents the average actual output data of the functional module group. r This represents the average actual input data for the functional module group.

4. The PLC controller functional module data processing method according to claim 1, characterized in that, The step of associating control task groups and functional module groups based on the control adaptability to obtain control association groups includes: Obtain a preset adaptation threshold, compare the control adaptation with the preset adaptation threshold, and when the control adaptation is greater than the preset adaptation threshold, associate the corresponding control task group and functional module group to obtain the corresponding control association group. When the control adaptability is less than or equal to the preset adaptability threshold, the corresponding control task group and functional module group are not associated.

5. The PLC controller functional module data processing method according to claim 1, characterized in that, The step of establishing a data processing chain for functional module groups based on control task information, and marking the sequence number of the data processing order for each functional module group, includes: Based on the control task information corresponding to multiple functional module groups in the control association group, the control sequence of multiple functional module groups is connected to obtain the data processing chain. Each functional module group in the data processing chain is labeled with a sequence number representing the data processing order, thus obtaining the functional module labeling information.

6. The PLC controller functional module data processing method according to claim 1, characterized in that, The functional module group processes data based on the associated control task information to obtain the processing data of each functional module, thereby obtaining the final processed data, which is then sent to the central processing unit, including: Suppose there are n functional module groups in total. The nth functional module group performs data processing for the corresponding function based on the control task information of the control task group associated with it, and obtains the processed data of the nth functional module group. Send the processing data of the nth functional module group to the (n-1)th functional module group; The data is retrieved from all functional modules in the order of the data processing chain and sent to the central processing unit.

7. The PLC controller functional module data processing method according to claim 6, characterized in that, The step of acquiring the processing data of all functional modules in the order of the data processing chain and sending it to the central processing unit includes: The (n-1)th functional module group performs data processing for its corresponding function based on the control task information of its associated control task group, and obtains the processing data of the (n-1)th functional module group. This process continues until all functional module groups have completed data processing and all functional module processing data has been obtained. The processing data of the last functional module to perform data processing is the final processing data. All functional module processing data and the final processing data are then sent to the central processing unit.

8. The PLC controller functional module data processing method according to claim 1, characterized in that, The process of obtaining data processing annotation information and then determining whether to perform data reprocessing includes: When the data processing label information is normal, the central processing unit processes the final processed data according to the preset program; When the data processing label information indicates an anomaly, the central processing unit generates control instructions to control the data processing chain to reprocess the data.

9. A PLC controller functional module data processing system, characterized in that, The system includes: The control function association module is used to classify the control task information and function module information of the PLC controller, calculate the control compatibility of the control task group and function module group obtained by classification, and associate the control task group and function module group according to the control compatibility to obtain the control association group. The functional data processing module is used to establish a data processing chain for the functional module group based on the control task information, mark the sequence number of the data processing order of the functional module group, and the functional module group processes the data according to the associated control task information to obtain the processing data of each functional module, thereby obtaining the final processed data and sending it to the central processing unit. The anomaly labeling and judgment module is used to calculate the data processing anomaly value of each functional module, compare the data processing anomaly value with the preset anomaly threshold, and label the data processing of the functional module according to the comparison result to obtain data processing labeling information, and then determine whether to reprocess the data. The process of calculating data processing anomalies for each functional module, comparing these anomalies with a preset anomaly threshold, and labeling the functional modules based on the comparison results to obtain data processing labeling information includes: The central processing unit calculates the data processing anomaly value for each functional module based on the processing data acquired from each functional module; The comparison results are obtained by comparing the data processing anomalies with the preset anomaly threshold. The formula for calculating outliers in data processing is as follows: Where CY represents outliers in data processing, L represents the total number of data processing categories, and SC represents... i YC represents the actual output data of the i-th data processing functional module. i Preset output data for the i-th data processing functional module, SR i YR is the actual input data for the i-th type of data processing functional module. i Preset input data for the i-th type of data processing functional module; When the abnormal value of the data processing exceeds the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as abnormal. When the abnormal value of the data processing is less than or equal to the preset abnormal threshold, the functional module corresponding to the abnormal value of the data processing is marked as normal processing. The abnormal processing label and the normal processing label are the data processing label information.

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