Full-load section analog quantity adaptive control and reliability optimization system adaptive to DCS early warning

Abstract

The invention discloses a full-load section analog quantity adaptive control and reliability optimization system adaptive to DCS (Distributed Control System) early warning, which adopts a multi-layer hierarchical structure and comprises a process control level unit, a process management level unit, a system management level unit and a communication network unit, the whole system realizes mutual connection and real-time transmission and sharing of data through the communication network unit, ensures cooperative work among units of all levels, and has the technical characteristics of realizing real-time transmission and sharing of data, ensuring cooperative work among all levels, being capable of meeting the requirements of efficient, stable and safe operation of a thermal power plant and the like.

Description

Technical Field

[0001] The present invention relates to a system for adaptive control and reliability optimization, and more specifically, to a system for full-load analog adaptive control and reliability optimization adapted to DCS early warning, belonging to the field of thermal power plants. Background Art

[0002] In the thermal process of modern thermal power plants, realizing automation and intelligence of the production process is the key to improving production efficiency and operational safety. The adaptive control of the full-load segment analog control system (MCS) and the early warning mechanism of the distributed control system (DCS) are of great significance to the stable operation of thermal power plants. Adaptive control in the adaptive control and reliability optimization of the full-load segment MCS system is a technology that can automatically adjust the control strategy and parameters according to the system operating status and external environmental changes. In the full-load segment MCS system of a thermal power plant, adaptive control dynamically adjusts the control parameters by real-time monitoring of the system's operating status and load changes to achieve efficient and stable operation of the system.

[0003] As one of the core technologies in the field of industrial automation, DCS (Distributed Control System) has been widely used in industries such as petroleum, chemical, electric power, and metallurgy. It integrates computer technology, network communication technology, and control technology, and achieves efficient and precise control of industrial processes through the mode of decentralized control, centralized operation, and hierarchical management. Summary of the invention

[0004] The purpose of the present invention is to provide a full-load analog adaptive control and reliability optimization system adapted to DCS early warning, which has the technical characteristics of realizing real-time transmission and sharing of data, ensuring collaborative work between various levels, and meeting the requirements of efficient, stable and safe operation of thermal power plants.

[0005] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0006] The present invention provides a full-load analog quantity adaptive control and reliability optimization system adapted to DCS early warning, characterized in that the full-load analog quantity adaptive control and reliability optimization system adopts a multi-layer hierarchical structure, including a process control level unit, a process management level unit, a system management level unit and a communication network unit. The entire system is interconnected and the real-time transmission and sharing of data are achieved through the communication network unit, and the collaborative work between the units at each level is ensured.

[0007] Preferably, the process control level unit includes a communication-connected adaptive control strategy module and a reliability optimization module; the process management level unit includes a hardware configuration control module, and the hardware configuration control module includes a display screen that provides a human-machine interface for displaying the status, parameters, and alarm information of the production process, and receiving instructions and inputs from operators; the graphical interface of the hardware configuration control module adopts an intuitive graphical display method, and the graphical display method includes a flow chart, a trend chart, and an alarm list; the operation panel of the display screen includes buttons, switches, and a keyboard, allowing the operator to perform manual operations and parameter settings.

[0008] The system management layer unit includes a software control module, which includes a control algorithm module. The functions of the software control module are: responsible for implementing various control algorithms, including PID control, fuzzy control, and neural network control, to adapt to different control requirements of the full load section. According to the real-time feedback data of the system, the control parameters are automatically adjusted to achieve adaptive control of analog quantities, ensuring that the control system can achieve the best control effect in the full load section and improve production efficiency and product quality.

[0009] The communication network unit includes a DCS system early warning module, and the DCS system early warning module includes a controller module; the controller module is responsible for executing control tasks and processing process data.

[0010] Preferably, the adaptive control strategy module includes a communication-connected data acquisition and preprocessing module, a model building and parameter identification module, an adaptive control algorithm module, a real-time control and feedback module, and an alarm and interlocking protection module.

[0011] Preferably, the data acquisition and preprocessing module monitors the operating status of the system in real time through sensors and data acquisition equipment, including key parameters such as temperature, pressure, flow, and load, and uses data cleaning and feature extraction to preprocess the data and extract useful feature information.

[0012] The model building and parameter identification module builds the mathematical model of the system based on the historical operation data and real-time data of the system, determines the parameters of the model through parameter identification technology, and updates the model in real time to reflect the latest status of the system;

[0013] The adaptive control algorithm module is designed based on the control strategy of the adaptive control algorithm, which includes adaptive PID control, fuzzy control, and neural network control. By real-time monitoring of the system's operating status and load changes, the parameters of the control algorithm are dynamically adjusted to enable the system to respond quickly to load changes and maintain system stability.

[0014] The real-time control and feedback module uses the output of the adaptive control algorithm as a control signal to adjust the system's operating parameters in real time. At the same time, it monitors the system's response in real time through a feedback mechanism, evaluates the control effect, and adjusts the control strategy accordingly.

[0015] Functions of the alarm and interlock protection module: This module is used to monitor abnormal conditions in the production process and trigger alarms or interlock protection actions when the preset conditions are met to prevent accidents. It also exchanges information with the real-time control and feedback module to close the alarm of abnormal information.

[0016] Preferably, the reliability optimization module includes a communication connection redundant design module, a fault monitoring and prediction module, and a fault-tolerant control module.

[0017] Preferably, the redundant design module includes hardware redundancy and software redundancy. Hardware redundancy includes redundant controllers, sensors and actuators; software redundancy includes redundant control algorithms and data processing modules. When a system failure occurs, redundant components can quickly take over the work to ensure stable operation of the system.

[0018] Preferably, the fault monitoring and prediction module realizes the establishment of a fault monitoring and prediction system based on adaptive technology, monitors the operating status and performance parameters of the system in real time, discovers potential faults in time through data analysis and model prediction, and takes corresponding measures to repair or prevent them;

[0019] The fault-tolerant control module is used to design a fault-tolerant control strategy. When a system failure occurs, the fault-tolerant control mechanism is used to ensure the stable operation of the system. The fault-tolerant control strategy includes fault isolation, fault compensation and fault reconstruction.

[0020] Preferably, the hardware configuration control module includes a distributed processing module, an input and output module, and a redundant configuration module that are communicatively connected.

[0021] Preferably, the software control module includes a communication-connected control strategy module, a real-time monitoring and data analysis module, and a fault diagnosis and prediction module.

[0022] Preferably, the DCS system early warning module includes a network communication status module, a controller operation status module, an I / O module operation status module and multiple control stations. The I / O module operation status module realizes feedback and real-time monitoring of changes in key parameters, and the key parameters include temperature, pressure, flow, and load; the network communication status module realizes communication connection between multiple control stations.

[0023] Beneficial effects: It can meet the needs of efficient, stable and safe operation of thermal power plants, realize real-time transmission and sharing of data, ensure collaborative work among various levels, improve the reliability of the system and the control adaptability under deep regulation and accident conditions, and facilitate the realization of ensuring that important performance indicators such as unit AGC coordination, primary frequency regulation, main steam temperature, reheat steam temperature, etc. meet the technical requirements. DETAILED DESCRIPTION

[0024] The present invention is further described below in conjunction with the specific embodiments of the specification, but the present invention is not limited to the following embodiments.

[0025] This paper aims to design an analog adaptive control system for the full load segment of early warning based on DCS, and introduces in detail its system framework structure, the functions and configurations of modules and subsystems to meet the needs of complex industrial process control. System framework structure design DCS early warning full load segment analog adaptive control system adopts a multi-layer hierarchical structure, which consists of process control level, process management level, system management level and communication network. The entire system framework is interconnected through an information network to achieve real-time transmission and sharing of data, ensuring collaborative work between various levels. This technical solution can achieve full load segment adaptive control and reliability optimization strategy, combined with the design of early warning in the DCS system, to meet the needs of efficient, stable and safe operation of thermal power plants.

[0026] The present invention discloses a specific embodiment of a system for full-load segment analog quantity adaptive control and reliability optimization adapted to DCS early warning. The embodiment discloses a system for full-load segment analog quantity adaptive control and reliability optimization adapted to DCS early warning. The system for full-load segment analog quantity adaptive control and reliability optimization adopts a multi-layer hierarchical structure, including a process control level unit, a process management level unit, a system management level unit and a communication network unit. The entire system realizes mutual connection and real-time transmission and sharing of data through the communication network unit, and ensures the collaborative work between the units at each level.

[0027] Process control level unit: directly facing the field equipment and process, responsible for data acquisition and control signal generation; Function of process control level unit: The process control level unit is the lowest level of the system, directly collecting data and controlling the production process. The process control level unit realizes real-time monitoring and adjustment of production process parameters through decentralized field control stations and data acquisition stations. Configuration of process control level unit: Field control station: including CPU, memory, I / O module and other hardware components. Each control station is responsible for monitoring one or more control loops. Data acquisition station: responsible for collecting sensor data and sending it to the process control station through the communication network unit. I / O module: realizes analog and digital input and output, connects with sensors and actuators, converts signals and transmits them to the controller. Features: High reliability: adopts redundant design and fault-tolerant mechanism to ensure that a single failure does not affect the overall operation of the system. Real-time: has fast response capability and can process field data and control instructions in real time.

[0028] Process management level unit: Centrally monitors and manages the process control level unit, including the operator station and engineer station; the process management level unit is the interface for operators and engineers to interact with the process control level unit, responsible for monitoring the entire production process and configuring and debugging the process control level unit.

[0029] Configuration of process management level unit: Operator station: Provides human-machine interface, displays the status, parameters and alarm information of the production process, and allows operators to manually intervene and control. Engineer station: Used for system configuration, programming and debugging, providing advanced control algorithms and strategies. Features: Centralized monitoring: Realizes centralized monitoring and control of multiple process control stations. Flexible configuration: The system can be easily configured and modified through configuration software.

[0030] The system management level unit is the high-level management part of the DCS system, which is mainly responsible for global optimization, resource scheduling and decision support. Configuration: MIS system: Integrates enterprise resource planning, production scheduling, inventory management and other functions to achieve comprehensive management of the enterprise. Data analysis server: Processes and analyzes the collected production data to provide decision support for the management level. Features: Information sharing: Seamlessly integrates with process management level units and process control level units to achieve information sharing throughout the plant. Optimized decision-making: Based on real-time and historical data, production optimization and decision support are carried out. Higher-level management of the system management level unit, including MIS (Management Information System) system, performs global optimization and decision support;

[0031] Communication network unit: a bridge connecting each unit and submodule, ensuring real-time transmission of data and commands; Function of communication network unit: The communication network unit is the skeleton of the DCS system, responsible for data transmission and communication between various levels and subsystems. Configuration of communication network unit: Industrial Ethernet: as the backbone network, connecting various control stations, operation stations and servers. Fieldbus: connecting field equipment and control stations to achieve the bottom-level transmission of data. Redundant design: using redundant communication links to ensure the reliability and stability of communication. Features: High speed and reliability: supporting high-speed data transmission to ensure real-time and reliability. Open standard: using international standard communication protocols to facilitate system integration and expansion.

[0032] Preferably, the process control level unit includes a communication-connected adaptive control strategy module and a reliability optimization module; the process management level unit includes a hardware configuration control module, and the hardware configuration control module includes a display screen that provides a human-machine interface for displaying the status, parameters, and alarm information of the production process, and receiving instructions and inputs from operators; the graphical interface of the hardware configuration control module adopts an intuitive graphical display method, and the graphical display method includes a flow chart, a trend chart, and an alarm list; the operation panel of the display screen includes buttons, switches, and a keyboard, allowing the operator to perform manual operations and parameter settings. Features: Ease of use: The interface design is concise and clear, and the operation is convenient, which reduces the learning cost of the operator. Real-time: It can display the status and parameter changes of the production process in real time, which is convenient for operator monitoring and intervention;

[0033] The system management layer unit includes a software control module, which includes a control algorithm module. The functions of the software control module are: responsible for implementing various control algorithms, including PID control, fuzzy control, and neural network control, to adapt to different control requirements of the full load section. According to the real-time feedback data of the system, the control parameters are automatically adjusted to achieve adaptive control of analog quantities, ensuring that the control system can achieve the best control effect in the full load section and improve production efficiency and product quality.

[0034] The communication network unit includes a DCS system early warning module, and the DCS system early warning module includes a controller module; the controller module is the core part of the DCS system, responsible for executing control tasks and processing process data; configuration: CPU: high-performance industrial-grade CPU, supporting multi-tasking and real-time response. Memory: including ROM, RAM and E2PROM, used to store programs and data. Algorithm library: built-in multiple control algorithms, such as PID (proportional-integral-differential) control, fuzzy control, predictive control, etc., to meet different control requirements. Features: Adaptability: can automatically adjust the control strategy according to changes in process parameters to improve control accuracy and stability. Redundant configuration: The key controller adopts redundant configuration to ensure that the system can still operate normally when a single device fails.

[0035] The DCS system used in this application can also realize the standby status warning function, and can automatically decide whether to execute according to the actual working conditions of the unit for regular work, and can handle problems found during the execution process and ensure safe operation. The automatic execution and standby status alarm functions are developed for intelligent regular work, which are divided into two parts: intelligent regular switching and regular testing: regular switching means that when the equipment standby time is reached, it needs to start running and shut down the original running equipment; regular testing generally refers to regular start and stop or test, and does not include equipment switching.

[0036] A specific implementation method: The items of intelligent periodic switching include: condensate pump switching, feed water pump switching / automatic parallel pumping, open / closed water pump switching, vacuum pump switching, seal / lubricating oil pump switching, exhaust / shaft fan switching, etc. When the intelligent switching is put into use, it will automatically switch according to the system status and equipment operation status without human intervention. The switching will not affect the normal operation of the system, and the switching anomaly can be detected and handled. Manual switching is also possible. Intelligent periodic test items include: regular backwashing of open water automatic water filter, generator hydrogen leakage test, steam turbine valve activity test, unit water replenishment rate test, DC lubricating oil pump regular start-up test, etc. The fault self-recovery control function realizes that when the unit encounters equipment failures and system anomalies in abnormal and accident conditions, it can automatically handle them under unattended or small intervention conditions through the matching perfect logic, so that the unit can operate normally.

[0037] When designing the fault self-recovery function of this application, control optimization or circuit improvement can be carried out for different working conditions. After the system or equipment abnormality occurs, the system can be automatically adjusted to a safe operating state according to the current system operating conditions. For example, after the condensate pump fails, it is designed to automatically start the standby condensate pump, the inverter adjusts to maintain the pressure, the water valve maintains the water level, and the faulty condensate pump is shut down; if the auxiliary machine trips during the low-load stage, the corresponding program should be started to determine whether to jump the mill to reduce the load and whether the combustion system needs to be put into use; if the fan surges or stalls, the alarm function should be activated, and after confirmation, the load reduction, start and stop of the corresponding side equipment, and opening of the ventilation duct communication door should be automatically executed.

[0038] In a preferred embodiment, the adaptive control strategy module includes a communication-connected data acquisition and preprocessing module, a model building and parameter identification module, an adaptive control algorithm module, a real-time control and feedback module, and an alarm and interlocking protection module.

[0039] The data acquisition and preprocessing module monitors the operating status of the system in real time through sensors and data acquisition equipment, including key parameters such as temperature, pressure, flow, and load, and uses data cleaning and feature extraction technology to preprocess the data and extract useful feature information;

[0040] Function of the data acquisition and processing module: The data acquisition and processing module is responsible for collecting raw data from field sensors, performing preprocessing, filtering, conversion and other operations, and sending it to the controller or host computer for further processing. Configuration of the data acquisition and processing module:

[0041] Data acquisition in the data acquisition and processing module: connects various sensors and supports multiple signal inputs, such as current, voltage, temperature, pressure, etc. Preprocessing in the data acquisition and processing module: runs in the data acquisition station or controller to perform data preprocessing and conversion tasks. Features of the data acquisition and processing module: High precision: uses high-precision data acquisition circuits and software algorithms to ensure data accuracy and reliability. Real-time: has fast data acquisition and processing capabilities to ensure that data can be updated in a timely manner and used for control decisions.

[0042] The model building and parameter identification module builds the mathematical model of the system based on the historical operation data and real-time data of the system, determines the parameters of the model through parameter identification technology, and updates the model in real time to reflect the latest status of the system;

[0043] The adaptive control algorithm module is designed based on the control strategy of the adaptive control algorithm, which includes adaptive PID control, fuzzy control, and neural network control. By real-time monitoring of the system's operating status and load changes, the parameters of the control algorithm are dynamically adjusted to enable the system to respond quickly to load changes and maintain system stability.

[0044] Functions of the adaptive control algorithm module: This module integrates a variety of adaptive control algorithms, which can automatically adjust control parameters according to different load segments and operating conditions to achieve optimized control of the full load segment.

[0045] Configuration of the adaptive control algorithm module: Algorithm library: Contains a variety of advanced adaptive control algorithms, such as adaptive PID, neural network control, genetic algorithm optimization, etc. Parameter optimization: Automatically optimize control parameters through online learning or offline training to improve system control performance. Features: Intelligence: Able to automatically learn and adapt to process changes, improve the system's adaptability and control accuracy. Flexibility: Supports the selection and combination of multiple algorithms to meet the control requirements under different working conditions;

[0046] The real-time control and feedback module uses the output of the adaptive control algorithm as a control signal to adjust the system's operating parameters in real time. At the same time, it monitors the system's response in real time through a feedback mechanism, evaluates the control effect, and adjusts the control strategy accordingly.

[0047] Functions of the alarm and interlock protection module: This module is used to monitor abnormal conditions in the production process and trigger alarms or interlock protection actions when the preset conditions are met to prevent accidents. It also exchanges information with the real-time control and feedback module to close the alarm of abnormal information.

[0048] Configuration of alarm and interlock protection module: Alarm setting: Set alarm thresholds according to process requirements, including high alarm, low alarm, high high alarm, low low alarm, etc. Interlock logic of alarm and interlock protection module: Define the logical relationship of interlock protection, and automatically execute preset safety operations when specific conditions are met. Features: Fast response: Able to detect abnormal conditions and trigger alarms or protection actions at the first time. Safe and reliable: Ensure the correctness and reliability of interlock protection through strict logic verification and testing.

[0049] Statistical analysis can be performed on thermal factors, especially the refusal / maloperation of interlock protection logic, faults that have occurred or potential faults that have been discovered, and the degree of logic mismatch under low-load deep regulation and spot scheduling conditions. The present invention can demonstrate and confirm the reliability of the thermal protection interlock signal sampling point, such as evaluating and analyzing the reliability data of the control system's hardware, logical conditions, and constants, to optimize the thermal protection logic that has a serious impact on the safe operation of the unit equipment from the perspective of improving reliability, improve the adaptability of the unit's control logic under deep regulation and spot scheduling operation modes, evaluate and optimize the alarm or interlock action mode for single-point signal protection that often malfunctions and cannot achieve signal redundancy, confirm the equipment preparation conditions and status, and achieve automatic regular switching / testing, as well as monitoring and alarm.

[0050] In a preferred embodiment, the reliability optimization module includes a redundant design module for communication connection, a fault monitoring and prediction module, and a fault-tolerant control module. The redundant design module includes hardware redundancy and software redundancy. Hardware redundancy includes redundant controllers, sensors, and actuators; software redundancy includes redundant control algorithms and data processing modules. When a system failure occurs, the redundant components can quickly take over the work to ensure the stable operation of the system. The fault monitoring and prediction module realizes the establishment of a fault monitoring and prediction system based on adaptive technology, monitors the operating status and performance parameters of the system in real time, and timely discovers potential faults through data analysis and model prediction, and takes corresponding measures to repair or prevent them; Fault-tolerant control module: used to design fault-tolerant control strategies. When a system failure occurs, the stable operation of the system is guaranteed through a fault-tolerant control mechanism. The fault-tolerant control strategy includes fault isolation, fault compensation, and fault reconstruction.

[0051] From the perspective of reliability, the thermal control logic is comprehensively compared and optimized as a whole. The fault-tolerant logic design method is adopted to optimize and improve the control logic of equipment that is prone to failure during operation. The failure of the entire control logic is reduced or avoided through pre-set logical measures. Further, based on the DL / T261 "Guidelines for Reliability Assessment of Thermal Automation Systems in Thermal Power Plants" and combined with the requirements of DL / T774 "Regulations for Inspection, Operation and Maintenance of Thermal Automation Systems in Thermal Power Plants", a thermal control reliability control method based on fault-tolerant design is proposed, and the final optimization plan is obtained.

[0052] Specific full load segment (MCS) system adaptive control and reliability optimization may include:

[0053] Comprehensively sort out, review and optimize the automatic control system of the unit's full load section. Through strategy optimization and disturbance tests, optimize the regulation quality of each full load section (MCS) system to adapt to the control requirements of the full load section, reduce the fluctuation range of parameters, improve the stability of the unit, and especially solve the optimization problems of control performance in accident conditions and the range below 50%. Sort out and improve the rapid output balancing function of the unit's main auxiliary machines after tripping in the low load section, conduct auxiliary machine tripping tests at low load, and dynamically verify the automatic control function after the auxiliary machine trips to avoid the unit's non-stop due to drastic fluctuations in operating conditions during low load operation. Solve the problems of low load section coordination and control boundaries, safety thresholds, and control mode switching of the main important control system to ensure the safety and stability of the unit under low load deep peak-shaving conditions and normal operation of medium and high loads. Such as the calculation of coal quantity at the initial start-up of the coal feeder, the impact on steam temperature when the pulverizing system is started, and the stall and surge protection control of the fan, etc., and verify through tests that each circuit is stably put into automatic control under full load sections and accident conditions, with good parameter quality and adaptive peak-shaving unit multi-condition operation requirements.

[0054] In a preferred embodiment, the hardware configuration control module includes a distributed processing module, an input / output module, and a redundant configuration module that are communicatively connected.

[0055] In a preferred embodiment, the software control module includes a communication-connected control strategy module, a real-time monitoring and data analysis module, and a fault diagnosis and prediction module.

[0056] In a preferred embodiment, the DCS system early warning module includes a network communication status module, a controller operation status module, an I / O module operation status module and multiple control stations. The I / O module operation status module realizes feedback of changes in key parameters monitored in real time, and the key parameters include temperature, pressure, flow, and load; the network communication status module realizes communication connection between multiple control stations.

[0057] For example, the technical solution of the present invention is applicable to: the #1 and #2 units of the power plant are 660MW ultra-supercritical coal-fired units; the steam turbine adopts the steam turbine produced by Shanghai Steam Turbine Co., Ltd.; the steam turbine type is ultra-supercritical, single intermediate reheat, single shaft, four cylinders and four exhaust, condensing steam turbine; the generator adopts the generator of Shanghai Electric Group Co., Ltd., which is water-hydrogen-hydrogen cooling and static excitation; the boiler adopts the ultra-supercritical parameter variable voltage operation DC furnace produced by Beijing Babcock Wilcock Co., Ltd., model B&WB-1994 / 29.3-M, the boiler is a single furnace, single intermediate reheat, flat street ventilation, open-air layout, solid slag discharge, full steel frame, full suspension structure layout, low NOx double-adjustable air swirl burner, front and rear wall counter-combustion, and the air preheater adopts a full pull-out layout. The distributed control system (DCS) of the unit adopts the OVATION3.6 control system produced by Emerson Process Control Systems Co., Ltd. The distributed control system (DCS) includes: coordinated control system (CCS), analog control system (MCS), data acquisition and monitoring system (DAS), boiler furnace safety monitoring system (FSSS), high and low pressure bypass control system (BPS), sequential control system (SCS), etc.

[0058] The technical solution of the present application can be used to systematically process the reliability of the control logic, including deep regulation and long-term low-load operation conditions, the requirements for rapid response of high-rate loads in the electricity spot market, large-flow heating conditions, and increased discreteness of faults after the expansion of the monitoring range of DCS and thermal systems. Feedback processing and response can be achieved, so as to improve the original thermal control system in terms of control reliability, rationality of logical conditions, system perfection, and the way and configuration of protection signals.

[0059] For example, when the unit characteristics (such as coal quality changes) change, or under abnormal or accident conditions (such as auxiliary machine tripping), the control parameters will be mismatched with the equipment characteristics, and the control logic of the corresponding conditions will be matched. For example, in the low-load stage, all equipment of the unit is operating under non-design conditions, and dynamic adjustment of parameters is achieved to avoid being far away from the design value, so as to avoid system oscillation and divergence, which may cause serious safety hazards. Therefore, the full-load analog adaptive control and reliability optimization system adapted to DCS early warning can realize the adaptive control logic of the full-load section and accident conditions of the development unit.

[0060] Finally, it should be noted that the present invention is not limited to the above embodiments, and there are many variations. All variations that can be directly derived or associated with the content disclosed by ordinary technicians in this field should be considered as the protection scope of the present invention.

Claims

1. A full-load analog adaptive control and reliability optimization system adapted to DCS early warning, characterized by: The system for full-load analog adaptive control and reliability optimization adopts a multi-layer hierarchical structure, including process control level units, process management level units, system management level units and communication network units. The entire system is interconnected and the real-time transmission and sharing of data are achieved through the communication network unit, and the collaborative work between units at each level is ensured.

2. According to claim 1, a full-load analog adaptive control and reliability optimization system adapted to DCS early warning is characterized in that: The process control level unit includes a communication-connected adaptive control strategy module and a reliability optimization module; the process management level unit includes a hardware configuration control module, which includes a display screen providing a human-machine interface for displaying the status, parameters, and alarm information of the production process, and receiving instructions and inputs from operators; the graphical interface of the hardware configuration control module adopts an intuitive graphical display method, and the graphical display method includes a flow chart, a trend chart, and an alarm list; the operation panel of the display screen includes buttons, switches, and a keyboard, allowing the operator to perform manual operations and parameter settings; the system management layer unit includes a software control module, which includes a control algorithm module, and the software control module is responsible for implementing various control algorithms, including PID control, fuzzy control, and neural network control to adapt to different control requirements of the full load segment, and automatically adjust the control parameters according to the real-time feedback data of the system to achieve adaptive control of analog quantities, ensuring that the control system can achieve the best control effect in the full load segment and improve production efficiency and product quality; the communication network unit includes a DCS system early warning module, and the DCS system early warning module includes a controller module; the controller module is responsible for executing control tasks and processing process data.

3. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 1 is characterized by: The adaptive control strategy module includes a communication-connected data acquisition and preprocessing module, a model building and parameter identification module, an adaptive control algorithm module, a real-time control and feedback module, and an alarm and interlocking protection module.

4. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 3 is characterized by: The data acquisition and preprocessing module monitors the operating status of the system in real time through sensors and data acquisition equipment, including key parameters such as temperature, pressure, flow, and load, and uses data cleaning and feature extraction to preprocess the data and extract useful feature information; The model building and parameter identification module builds the mathematical model of the system based on the historical operation data and real-time data of the system, determines the parameters of the model through parameter identification technology, and updates the model in real time to reflect the latest status of the system; The adaptive control algorithm module is designed based on the control strategy of the adaptive control algorithm, which includes adaptive PID control, fuzzy control, and neural network control. By real-time monitoring of the system's operating status and load changes, the parameters of the control algorithm are dynamically adjusted to enable the system to respond quickly to load changes and maintain system stability. The real-time control and feedback module uses the output of the adaptive control algorithm as a control signal to adjust the system's operating parameters in real time. At the same time, it monitors the system's response in real time through a feedback mechanism, evaluates the control effect, and adjusts the control strategy accordingly. Functions of the alarm and interlock protection module: This module is used to monitor abnormal conditions in the production process and trigger alarms or interlock protection actions when the preset conditions are met to prevent accidents. It also exchanges information with the real-time control and feedback module to close the alarm of abnormal information.

5. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 2 is characterized by: The reliability optimization module includes a communication connection redundant design module, a fault monitoring and prediction module, and a fault-tolerant control module.

6. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 5 is characterized by: The redundant design module includes hardware redundancy and software redundancy. Hardware redundancy includes redundant controllers, sensors and actuators; software redundancy includes redundant control algorithms and data processing modules. When a system failure occurs, redundant components can quickly take over the work to ensure the stable operation of the system.

7. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 5 is characterized by: The fault monitoring and prediction module realizes the establishment of a fault monitoring and prediction system based on adaptive technology, monitors the operating status and performance parameters of the system in real time, discovers potential faults in time through data analysis and model prediction, and takes corresponding measures to repair or prevent them; The fault-tolerant control module is used to design a fault-tolerant control strategy. When a system failure occurs, the fault-tolerant control mechanism is used to ensure the stable operation of the system. The fault-tolerant control strategy includes fault isolation, fault compensation and fault reconstruction.

8. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 2 is characterized by: The hardware configuration control module includes a distributed processing module, an input and output module, and a redundant configuration module which are communicatively connected.

9. The full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 2 is characterized by: The software control module includes a communication-connected control strategy module, a real-time monitoring and data analysis module, and a fault diagnosis and prediction module.

10. A full-load analog adaptive control and reliability optimization system adapted to DCS early warning according to claim 2 or 5 or 8 or 9, characterized in that: The DCS system early warning module includes a network communication status module, a controller operation status module, an I / O module operation status module and multiple control stations. The I / O module operation status module realizes feedback and real-time monitoring of changes in key parameters, including temperature, pressure, flow, and load; The network communication status module realizes the communication connection between multiple control stations.