Coal and sludge control system

Abstract

The present application relates to the field of control system, disclose a kind of coal and sludge control system, for the coal and sludge control system is transformed from PLC to safety controllable DCS system, to improve the automation level of coal conveying system.It includes execution system survey and demand analysis, through field survey, data acquisition and personnel operation analysis, generate system analysis document, based on document hardware and software collaborative design, generate control logic configuration file and human-computer interface design scheme, according to both development intelligent application, generate DCS intelligent control system, optimize system debugging, generate debugging report and optimization scheme, through the acquisition real-time data monitoring control production process, and continuously generate optimization instruction.The present application covers from early analysis to continuous optimization whole process, through multidimensional, systematic operation, improve the performance and reliability of coal and sludge control system.

Description

Technical Field

[0001] This invention relates to the field of control systems, and more particularly to a coal conveying and sludge control system. Background Technology

[0002] With the rapid development of industrial automation technology, distributed control systems (DCS) have been widely used in industrial production processes due to their powerful data processing capabilities, flexible configuration methods, and reliable redundancy design. Especially in thermal power plants, the coal conveying system, as a crucial auxiliary system, directly affects the safe operation of the unit. However, many power plants still use traditional programmable logic controller (PLC) systems for their coal conveying control systems, which are gradually showing limitations in handling complex control logic, processing massive amounts of data, and ensuring system scalability.

[0003] The shortcomings of existing technologies are mainly reflected in the following aspects:

[0004] The limited number of points in a PLC system makes it difficult to meet the growing monitoring needs of the coal conveying system. As production scale expands and monitoring parameters increase, the existing PLC system cannot be flexibly expanded, leading to monitoring blind spots and affecting the overall operating efficiency and safety of the system.

[0005] PLC systems have limited capacity to process massive amounts of data, making it difficult to achieve refined management and intelligent optimization control of coal conveying systems. Under complex operating conditions, PLC systems often fail to process and analyze data in a timely and accurate manner, resulting in lagging control strategies and affecting production efficiency and product quality.

[0006] The human-machine interface of PLC systems is relatively simple, making operation and maintenance inconvenient. Operators need to spend a lot of time familiarizing themselves with the interface operation, and there is a lack of intuitive and convenient tools to support troubleshooting and system maintenance, which increases operation and maintenance costs and time.

[0007] The redundancy design of PLC systems is not as perfect as that of DCS systems, and the system reliability needs to be improved. During long-term operation, PLC systems are prone to failure, and the failure recovery time is long, which affects the continuity and stability of production. In addition, many coal conveying control systems are currently operating beyond their equipment lifespan, which further exacerbates the system reliability problem.

[0008] There are protocol barriers between the existing PLC system and the power plant's upper-level information management system, forming data silos. This prevents production data from being transmitted to the upper-level system in a timely and accurate manner, affecting the effectiveness of refined management and decision support.

[0009] Therefore, we propose a coal conveying and sludge control system to solve the above problems. Summary of the Invention

[0010] This invention provides a coal conveying and sludge control system, which is used to transform the coal conveying and sludge control system from a PLC to a safe and controllable DCS system, aiming to improve the automation level of the coal conveying system and enhance the reliability of system operation.

[0011] The first aspect of this invention provides a coal conveying and sludge control system, comprising: an acquisition module for performing system surveying and demand analysis, generating a system analysis document through on-site equipment surveying, historical operating data collection, and operation analysis by maintenance personnel; a collaboration module for performing hardware and software collaborative design based on the system analysis document, generating a control logic configuration file and a human-machine interface design scheme; a setting module for developing intelligent applications for the coal conveying and sludge control system based on the control logic configuration file and the human-machine interface design scheme, generating a DCS intelligent control system; an optimization module for using the DCS intelligent control system to perform debugging and optimization, generating a debugging report and a system optimization scheme; and an allocation module for running the optimized DCS intelligent control system based on the debugging report and the system optimization scheme, monitoring and controlling the coal conveying and sludge production process through collected real-time operating data, and generating system performance optimization instructions.

[0012] Optionally, in the first implementation of the first aspect of the present invention, the method includes: acquiring the physical configuration information of the PLC system, including I / O module models, point distribution, and communication network topology, and generating an equipment configuration list and network topology diagram; collecting historical operating data and performing time-series alignment and abnormal data removal processing to generate a performance data analysis table; identifying operational bottlenecks and interface interaction pain points through operation and maintenance personnel's operation process records and analysis, and generating a human-machine interaction evaluation report; parsing the communication protocol and data exchange format between the existing system and the upper-level information system to generate an interface specification document; and generating a system analysis document based on the equipment configuration list, network topology diagram, performance data analysis table, human-machine interaction evaluation report, and interface specification document using a multi-dimensional weighted evaluation method.

[0013] Optionally, in the second implementation of the first aspect of the present invention, the method includes: dividing the coal conveying process into several independent control stations according to functional areas based on the equipment configuration list and performance data analysis table in the system analysis document; configuring a dual-redundant controller and modular I / O unit for each control station and reserving a 15% margin for points; generating a DCS hardware configuration table and a control station division scheme; and designing a system network using an industrial Ethernet and PROFINET dual-ring network architecture based on the network topology diagram and interface specification document in the system analysis document, and generating a network deployment scheme.

[0014] Optionally, in the third implementation of the first aspect of the present invention, the original PLC ladder diagram program is parsed, and a function block reorganization method oriented towards control flow is adopted to convert the sequential control logic into a function block diagram program based on the IEC 61131-3 standard, generating a preliminary control logic configuration file; based on the equipment fault records and system load peaks in the performance data analysis table, an equipment health status monitoring algorithm and a load balancing scheduling algorithm are developed, generating an intelligent algorithm module library; based on the human-machine interaction evaluation report, a human-machine interface prototype is developed; the function block diagram program, the intelligent algorithm module library, and the human-machine interface prototype are integrated and tested to generate the final control logic configuration file and human-machine interface design scheme.

[0015] Optionally, in the fourth implementation of the first aspect of the present invention, the method includes: establishing a device linkage rule base based on the function block diagram program in the control logic configuration file, and generating multi-device collaborative control logic; developing an intelligent early warning module based on state discrimination according to the device health status monitoring algorithm in the intelligent algorithm module library, and generating a device health status assessment system; and constructing a coal conveyor belt load optimization model based on real-time flow monitoring using the load balancing scheduling algorithm in the intelligent algorithm module library, and generating a belt conveyor unit collaborative operation strategy.

[0016] Optionally, in the fifth implementation of the first aspect of the present invention, based on the human-machine interface design scheme, an intelligent monitoring interface with a hierarchical alarm management mechanism is developed to generate an intelligent alarm processing system; according to the interface specification document, a data interaction interface based on the OPC UA protocol is designed to generate a standard communication module; and the multi-device collaborative control logic, equipment health status assessment system, belt conveyor collaborative operation strategy, intelligent alarm processing system and standard communication module are integrated into a DCS intelligent control system.

[0017] Optionally, in the sixth implementation of the first aspect of the present invention, the method includes: establishing a control system simulation test platform, loading the DCS intelligent control system into the simulation environment, verifying the control logic function, and generating a simulation test report; based on the simulation test report, deploying a control program on the field DCS controller, simulating field equipment signals through a signal generator, performing measurement point transmission tests, and generating a measurement point verification report; according to the measurement point verification report, performing individual equipment debugging in different areas, testing the control performance of each device in manual / automatic mode, and generating individual equipment debugging records; based on the individual equipment debugging records, performing linkage debugging of the entire coal conveying system, testing the execution effect of multi-device collaborative control logic, and generating a linkage debugging report; according to the linkage debugging report, performing a 72-hour continuous trial operation test, collecting system operation data, analyzing system stability and reliability indicators, and generating a trial operation analysis report; and combining all debugging reports and analysis data, using a multi-objective optimization method to determine the final system operating parameters and generating a system optimization scheme.

[0018] Optionally, in the seventh implementation of the first aspect of the present invention, the method includes: establishing a real-time data acquisition and monitoring system, acquiring equipment operating parameters through a sensor network deployed at the coal conveying site, and obtaining real-time monitoring data reports; developing a multi-dimensional equipment health assessment model based on the equipment health status assessment system in the system optimization scheme, and generating equipment health status early warning and preventive maintenance suggestions; optimizing the real-time load of the coal conveying belt system using a dynamic load allocation algorithm based on the real-time monitoring data reports, and generating a load optimization instruction set; automatically adjusting control parameters by comparing the deviation between actual operating data and optimization targets, and generating performance optimization instructions; developing a human-computer interaction optimization algorithm based on operator operation records and system response data, and generating interface layout optimization suggestions and operation process simplification schemes; integrating all optimization instructions and suggestions, establishing a system continuous optimization knowledge base, and generating a comprehensive optimization report.

[0019] The mechanism of this invention is as follows: By analyzing and studying the control logic implementation method, I / O point number and allocation, communication protocol type and data interaction capability with the upper-level information system of the PLC system, the existing system is quantitatively evaluated in terms of scalability, real-time performance and reliability. Research on the technology of safe and controllable DCS system for coal conveying is carried out, and the application and implementation of safe and controllable DCS for coal conveying is realized.

[0020] Based on traditional PLC interlocking control, and addressing the multi-machine coordination problem of coal conveying equipment, a DCS control system for coal conveying and sludge was developed based on the characteristics of DCS system. This system aims to improve the control performance of the coal conveying and sludge control system while ensuring the efficient and safe operation of the coal conveying process control system.

[0021] Beneficial effects: Through the modular design of the DCS system, a 15% margin of points is reserved for each control station, and dual redundant controllers and modular I / O units are adopted, which realizes flexible system expansion, completely eliminates monitoring blind spots, and significantly improves the overall operating efficiency and security of the system.

[0022] By integrating equipment health status monitoring algorithms and load balancing scheduling algorithms, a coal conveyor belt load optimization model based on real-time flow monitoring was constructed. This model realized multi-equipment collaborative control logic and intelligent early warning module, significantly improving data processing speed and the real-time performance of control strategies, and optimizing production efficiency and product quality.

[0023] By developing a hierarchical alarm management mechanism and an intelligent monitoring interface, the system has achieved priority sorting, correlation analysis, and processing suggestions for alarm information. This enables maintenance personnel to quickly locate fault points and take effective measures, significantly shortening fault recovery time and improving system reliability and production continuity.

[0024] By configuring dual redundant controllers for each control station and adopting a dual-ring network architecture of Industrial Ethernet and PROFINET, the fault tolerance and reliability of the system are significantly improved, production interruptions caused by system failures are reduced, and stable production operation is ensured.

[0025] By designing a data interaction interface based on the OPCUA protocol, bidirectional data exchange with the power plant's SIS and MIS systems was realized, enabling production data to be transmitted to the upper-level system in a timely and accurate manner. This provides a strong guarantee for refined management and decision support. The real-time data collection and analysis provides comprehensive production data support for the power plant's management, making management decisions more scientific and precise, and helping to optimize production processes and improve production efficiency.

[0026] Through on-site equipment surveys, historical operation data collection, and operation and maintenance personnel analysis, a system analysis document was generated, which included functional architecture analysis results, performance bottleneck quantitative assessment reports, and interface compatibility analysis reports. This provided a scientific basis for subsequent hardware and software co-design. Based on the system analysis document, the hardware and software co-design of the coal conveying and sludge DCS control system was carried out, generating a system analysis document that included a converted function block diagram program, a control logic configuration file integrating intelligent algorithm modules, and a human-machine interface design scheme. This achieved deep integration and optimized configuration of hardware and software. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of one embodiment of the coal conveying and sludge control system of the present invention. Detailed Implementation

[0028] This invention provides a coal conveying and sludge control system, used to transform a PLC-based coal conveying and sludge control system into a safe and controllable DCS system, aiming to improve the automation level of the coal conveying system and enhance the reliability of system operation. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0029] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the coal conveying and sludge control system of the present invention includes:

[0030] 101. Acquisition module, used to perform system survey and requirements analysis. Through on-site equipment survey, historical operation data collection and operation analysis by maintenance personnel, it generates a system analysis document that includes functional architecture summary results, performance bottleneck quantitative assessment report and interface compatibility analysis report.

[0031] It is understood that the executing entity of this invention can be a coal conveying and sludge control device, or it can be a terminal or a server; no specific limitation is made here. This embodiment of the invention will be described using a server as an example.

[0032] Specifically, physical configuration information of the PLC system is obtained through on-site surveys, including I / O module models, point distribution and communication network topology, and an equipment configuration list and network topology diagram are generated.

[0033] Collect historical operating data and perform time-series alignment and outlier data removal to generate a performance data analysis table that includes equipment fault records, signal delay statistics, and system load peak values.

[0034] By recording and analyzing the operation process of maintenance personnel, operational bottlenecks and interface interaction pain points are identified, and human-computer interaction evaluation reports are generated.

[0035] Analyze the communication protocols and data exchange formats between the existing system and the upper-level information system, and generate an interface specification document that includes protocol types, data field definitions, and transmission frequencies;

[0036] Based on the equipment configuration list, network topology diagram, performance data analysis table, human-computer interaction evaluation report and interface specification document, a multi-dimensional weighted evaluation method is used to quantify the system's shortcomings in scalability, real-time performance and reliability, and generate system analysis document;

[0037] 102. Collaboration Module: Based on system analysis documents, this module is used for the collaborative design of hardware and software for the coal conveying and sludge DCS control system, generating a control logic configuration file containing a converted function block diagram program, an integrated intelligent algorithm module, and a human-machine interface design scheme.

[0038] Specifically, based on the equipment configuration list and performance data analysis table in the system analysis document, the coal conveying process is divided into several independent control stations according to functional areas. Each control station is equipped with a dual redundant controller and a modular I / O unit, and a 15% margin for points is reserved. A DCS hardware configuration table and control station division scheme are generated.

[0039] Based on the network topology diagram and interface specification document in the system analysis document, a system network with a dual-ring network architecture of industrial Ethernet and PROFINET is designed, and a network deployment plan including network device selection, topology structure and security strategy is generated.

[0040] The original PLC ladder diagram program was analyzed, and the function block reorganization method oriented towards control flow was adopted to convert the sequential control logic into a function block diagram program based on the IEC 61131-3 standard, generating a preliminary control logic configuration file.

[0041] Based on the equipment fault records and system load peaks in the performance data analysis table, we developed equipment health status monitoring algorithms and load balancing scheduling algorithms, and generated an intelligent algorithm module library.

[0042] Based on the human-computer interaction evaluation report, a human-computer interface prototype was developed using the "modular + visual" design concept, which includes four functional areas: dynamic display of process flow, parameter monitoring panel, alarm management center, and historical data query.

[0043] The function block diagram program, intelligent algorithm module library and human-machine interface prototype are integrated and tested to generate the final control logic configuration file and human-machine interface design scheme.

[0044] 103. Setting up the module, which is used to develop intelligent applications for the coal conveying and sludge control system based on the control logic configuration file and human-machine interface design scheme, and generate a set of DCS intelligent control system;

[0045] Specifically, based on the function block diagram program in the control logic configuration file, an equipment linkage rule base is established to generate multi-equipment collaborative control logic that includes processes such as coal unloading, coal feeding, and coal blending.

[0046] Based on the equipment health status monitoring algorithms in the intelligent algorithm module library, an intelligent early warning module based on status discrimination is developed to generate an equipment health status assessment system that integrates multiple parameters such as abnormal vibration, excessive temperature, and excessive running time.

[0047] Using the load balancing scheduling algorithm in the intelligent algorithm module library, a coal conveyor belt load optimization model based on real-time flow monitoring is constructed, generating a belt conveyor unit collaborative operation strategy that includes speed regulation and start-stop optimization.

[0048] Based on the four functional areas in the human-machine interface design scheme, an intelligent monitoring interface with a hierarchical alarm management mechanism is developed, generating an intelligent alarm processing system that includes priority sorting, correlation analysis, and processing suggestions.

[0049] Based on the interface specification document, design a data interaction interface based on the OPC UA protocol to generate a standard communication module that can perform bidirectional data exchange with the power plant's SIS and MIS systems;

[0050] The system integrates multi-device collaborative control logic, equipment health status assessment system, belt conveyor collaborative operation strategy, alarm intelligent processing system and standard communication module to generate a complete DCS intelligent control system.

[0051] 104. Optimization module, used to debug and optimize the coal conveying and sludge DCS control system using the DCS intelligent control system, and generate a debugging report and system optimization plan containing optimization parameters and module configuration;

[0052] Specifically, a control system simulation test platform is established, the DCS intelligent control system is loaded into the simulation environment, the control logic function is verified, and a simulation test report containing the logic correctness verification results and response time indicators is generated.

[0053] Based on the simulation test report, a control program is deployed on the field DCS controller. The signal generator simulates the field equipment signals, and the transmission test of the measurement points is carried out to generate a measurement point verification report containing signal accuracy calibration data and I / O channel integrity rate.

[0054] Based on the measurement point verification report, individual equipment debugging is carried out in different areas to test the control performance of each device in manual / automatic mode, and generate individual debugging records containing device response characteristic curves and initial setting values ​​of control parameters.

[0055] Based on the individual unit debugging records, the entire coal conveying system is debugged in a coordinated manner to test the execution effect of the multi-equipment collaborative control logic and generate a coordinated debugging report containing system linkage timing optimization data and equipment collaborative operation parameters.

[0056] Based on the joint commissioning report, a 72-hour continuous trial run test was conducted, system operation data was collected, system stability and reliability indicators were analyzed, and a trial run analysis report containing system performance benchmark data and optimization suggestions was generated.

[0057] Based on all debugging reports and analysis data, a multi-objective optimization method is used to determine the final system operating parameters, and a system optimization plan is generated that includes an optimization parameter setting table, module configuration scheme and maintenance procedures.

[0058] 105. Allocation module, used to run the optimized DCS intelligent control system based on the debugging report and system optimization plan, monitor and control the coal conveying and sludge production process through the collected real-time operation data, and continuously generate system performance optimization instructions.

[0059] Specifically, a real-time data acquisition and monitoring system is established, which collects equipment operating parameters through a sensor network deployed at the coal conveying site, and generates real-time monitoring data reports containing equipment status data, process parameters and energy consumption indicators.

[0060] Based on the equipment health status assessment system in the system optimization scheme, a multi-dimensional equipment health assessment model is developed. By analyzing parameters such as vibration, temperature, and operating time, an early warning of equipment health status and preventive maintenance suggestions are generated.

[0061] Based on real-time monitoring data reports, a dynamic load allocation algorithm is used to optimize the load of the coal conveyor belt system in real time, generating a load optimization instruction set that includes speed adjustment commands and equipment start-up and shutdown sequences.

[0062] Establish a closed-loop optimization mechanism for system performance. By comparing the deviation between actual operating data and optimization targets, automatically adjust control parameters and generate performance optimization instructions that include PID parameter tuning values ​​and control logic correction suggestions.

[0063] Based on operator operation records and system response data, we developed a human-computer interaction optimization algorithm to generate interface layout optimization suggestions and operation process simplification solutions.

[0064] Integrate all optimization instructions and suggestions to establish a knowledge base for continuous system optimization, and generate a comprehensive optimization report that includes equipment maintenance plans, operating parameter optimization schemes, and human-machine interface improvement suggestions.

[0065] In this embodiment of the invention, system information is comprehensively obtained through multiple dimensions such as on-site surveys, historical data collection, and operation and maintenance personnel analysis. This generates a system analysis document containing various aspects such as equipment configuration, performance data, human-computer interaction, and interface specifications, providing a precise basis for subsequent design. It breaks through the limitations of traditional single analysis methods and uses a multi-dimensional weighted evaluation method to quantify the system's deficiencies in scalability, real-time performance, and reliability. This makes system problems visible and specific, providing a clear direction for targeted improvements and effectively improving the efficiency and accuracy of system optimization.

[0066] Based on system analysis documents, hardware and software are co-designed, and the coal conveying process is rationally divided into control stations. Redundant controllers and modular I / O units are configured, and spare capacity is reserved for points. At the same time, a dual-ring network architecture system network is designed to ensure the high reliability and scalability of the hardware system. Equipment health status monitoring algorithms and load balancing scheduling algorithms are developed, and an intelligent algorithm module library is generated and integrated into the control logic to realize intelligent early warning and load optimization of equipment, thereby improving the intelligence level and operating efficiency of the system. Based on the human-machine interaction evaluation report, a human-machine interface prototype is developed using the "modular + visualization" design concept. After integration and testing, the final design scheme is generated, enabling operators to monitor and control the production process more intuitively and conveniently, and improving the human-machine interaction experience.

[0067] Based on the control logic configuration file, an equipment linkage rule base is established to realize the collaborative control of multiple equipment in the coal unloading, coal feeding, and coal blending processes, thereby improving the automation level and collaborative efficiency of the production process. An intelligent early warning module is developed based on the equipment health status monitoring algorithm, and a multi-parameter fusion equipment health status assessment system is constructed. This system can detect potential equipment failures in advance, enabling preventative maintenance, reducing equipment failure rates, and extending equipment lifespan. A load balancing scheduling algorithm is used to construct a coal conveyor belt load optimization model, generating a belt conveyor unit collaborative operation strategy. This achieves load optimization based on real-time flow monitoring, improving energy utilization efficiency and reducing production costs. An intelligent monitoring interface with a hierarchical alarm management mechanism is developed, generating an intelligent alarm processing system capable of prioritizing alarm information, performing correlation analysis, and providing processing suggestions. This helps operators quickly and accurately handle alarm events, improving system security and reliability. Based on the interface specification document, a data interaction interface based on the OPC UA protocol is designed to achieve bidirectional data exchange with the power plant's SIS and MIS systems, promoting enterprise information integration and improving data sharing and utilization efficiency.

[0068] A control system simulation test platform was established to verify the control logic function of the DCS intelligent control system, identify potential problems in advance, reduce on-site debugging time and costs, and improve the efficiency and reliability of system debugging. Through a phased debugging process including on-site measurement point transmission testing, individual equipment debugging, linkage debugging, and 72-hour continuous trial operation testing, the system performance was gradually optimized to ensure that the system can operate stably and reliably under various working conditions. Based on all debugging reports and analysis data, a multi-objective optimization method was used to determine the final system operating parameters, generate a system optimization scheme, and enable the system to achieve the optimal balance on multiple performance indicators, thereby improving the overall performance and operating efficiency of the system.

[0069] A real-time data acquisition and monitoring system is established to collect equipment operating parameters through a sensor network, generate real-time monitoring data reports, and achieve real-time monitoring and control of the coal conveying and sludge production processes. This allows for timely detection and handling of anomalies during production. Based on the real-time monitoring data reports, a dynamic load allocation algorithm is used to optimize the load of the coal conveyor belt system in real time, generating a load optimization instruction set. This enables the system to dynamically adjust equipment operating parameters according to actual production needs, improving production efficiency and energy utilization. A closed-loop optimization mechanism for system performance is established, automatically adjusting control parameters and generating performance optimization instructions by comparing the deviation between actual operating data and optimization targets. This ensures continuous optimization of system performance and keeps the system in optimal operating condition. Based on operator operation records and system response data, a human-machine interaction optimization algorithm is developed to generate interface layout optimization suggestions and simplified operation procedures. These are integrated into the system's continuous optimization knowledge base to continuously improve the human-machine interaction experience and enhance operator efficiency and satisfaction.

[0070] The present invention also provides a coal conveying and sludge control device, the coal conveying and sludge control device including a memory and a processor, the memory storing computer-readable instructions, when the computer-readable instructions are executed by the processor, causing the processor to perform the steps of the coal conveying and sludge control system in the above embodiments.

[0071] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the coal conveying and sludge control system.

[0072] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0073] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A coal conveying and sludge control system, characterized in that, The coal conveying and sludge control system includes: The acquisition module is used to perform system surveying and requirements analysis. Through on-site equipment surveys, historical operational data collection, and analysis of maintenance personnel operations, it generates system analysis documents. Specifically, this includes: acquiring the physical configuration information of the PLC system, including I / O module models, location distribution, and communication network topology, generating an equipment configuration list and network topology diagram; collecting historical operational data and performing time-series alignment and anomaly removal processing, generating a performance data analysis table; identifying operational bottlenecks and interface interaction pain points through maintenance personnel operation process records and analysis, generating a human-machine interaction evaluation report; parsing the communication protocols and data exchange formats between the existing system and the upper-level information system, generating an interface specification document; and generating a system analysis document based on the equipment configuration list, network topology diagram, performance data analysis table, human-machine interaction evaluation report, and interface specification document using a multi-dimensional weighted evaluation method. The collaborative module is used to perform hardware and software collaborative design based on the system analysis document, generate control logic configuration files and human-machine interface design schemes, specifically including: parsing the original PLC ladder diagram program, adopting the function block reorganization method oriented towards control flow, converting the sequential control logic into a function block diagram program, and generating a preliminary control logic configuration file; The configuration module is used to develop intelligent applications for the coal conveying and sludge control system and generate a DCS intelligent control system based on the control logic configuration file and human-machine interface design scheme. The optimization module is used to perform debugging and optimization using the DCS intelligent control system, and generate debugging reports and system optimization schemes. The allocation module is used to run the optimized DCS intelligent control system based on the debugging report and system optimization scheme, monitor and control the coal conveying and sludge production process through the collected real-time operation data, and generate system performance optimization instructions.

2. The coal conveying and sludge control system according to claim 1, characterized in that, include: Based on the equipment configuration list and performance data analysis table in the system analysis document, the coal conveying process is divided into several independent control stations according to functional areas. Each control station is configured with a dual redundant controller and a modular I / O unit, and a 15% margin is reserved for the number of points. A DCS hardware configuration table and control station division scheme are generated. Based on the network topology diagram and interface specification document in the system analysis document, a system network adopting a dual-ring network architecture of industrial Ethernet and PROFINET is designed, and a network deployment plan is generated.

3. The coal conveying and sludge control system according to claim 2, characterized in that, Based on the equipment fault records and system load peaks in the performance data analysis table, develop equipment health status monitoring algorithms and load balancing scheduling algorithms, and generate an intelligent algorithm module library; Based on the aforementioned human-computer interaction evaluation report, a prototype human-computer interface was developed; The functional block diagram program, intelligent algorithm module library, and human-machine interface prototype are integrated and tested to generate the final control logic configuration file and human-machine interface design scheme.

4. The coal conveying and sludge control system according to claim 3, characterized in that, include: Based on the function block diagram program in the control logic configuration file, a device linkage rule base is established to generate multi-device collaborative control logic. Based on the equipment health status monitoring algorithms in the intelligent algorithm module library, develop an intelligent early warning module based on status discrimination and generate an equipment health status assessment system. Using the load balancing scheduling algorithm in the intelligent algorithm module library, a coal conveyor belt load optimization model based on real-time flow monitoring is constructed, and a collaborative operation strategy for belt conveyor units is generated.

5. The coal conveying and sludge control system according to claim 3, characterized in that, Based on the aforementioned human-machine interface design scheme, an intelligent monitoring interface with a hierarchical alarm management mechanism is developed, generating an intelligent alarm processing system. Based on the interface specification document, design a data interaction interface based on the OPC UA protocol and generate a standard communication module; The system integrates multi-device collaborative control logic, equipment health status assessment system, belt conveyor collaborative operation strategy, alarm intelligent processing system and standard communication module to generate DCS intelligent control system.

6. The coal conveying and sludge control system according to claim 5, characterized in that, include: Establish a control system simulation test platform, load the DCS intelligent control system into the simulation environment, verify the control logic function, and generate a simulation test report; Based on the simulation test report, a control program is deployed on the field DCS controller. The signal generator simulates the field equipment signals to perform the measurement point transmission test and generate a measurement point verification report. Based on the measurement point verification report, individual equipment debugging was carried out in different areas, and the control performance of each device in manual / automatic mode was tested, and individual equipment debugging records were generated. Based on the individual unit debugging records, the entire coal conveying system is debugged in a coordinated manner to test the execution effect of the multi-device collaborative control logic and generate a coordinated debugging report. Based on the joint commissioning report, a 72-hour continuous trial operation test was conducted, system operation data was collected, system stability and reliability indicators were analyzed, and a trial operation analysis report was generated. Based on all debugging reports and analysis data, a multi-objective optimization method is used to determine the final system operating parameters and generate a system optimization scheme.

7. The coal conveying and sludge control system according to claim 6, characterized in that, include: Establish a real-time data acquisition and monitoring system to collect equipment operating parameters through a sensor network deployed at the coal conveying site and obtain real-time monitoring data reports; Based on the equipment health status assessment system in the system optimization scheme, a multi-dimensional equipment health assessment model is developed to generate equipment health status early warning and preventive maintenance suggestions. Based on real-time monitoring data reports, a dynamic load allocation algorithm is used to optimize the load of the coal conveyor belt system in real time and generate a load optimization instruction set. By comparing the deviation between actual operating data and optimization targets, control parameters are automatically adjusted to generate performance optimization instructions; Based on operator operation records and system response data, we developed a human-computer interaction optimization algorithm to generate interface layout optimization suggestions and operation process simplification solutions. Integrate all optimization instructions and suggestions, establish a knowledge base for continuous system optimization, and generate a comprehensive optimization report.

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