Industrial Process Complex Control Loop Performance Monitoring And Intelligent Diagnosis Of Actuator Failure

Control systems can be divided into simple control systems and complex control systems.Multi-parameter control systems composed of multiple sensors,multiple regulators,or multiple actuators are usually called complex control systems.At present,the most common are cascade,ratio,uniform,feedforward-feedback and other complex control systems.Complex control systems are often designed according to actual production requirements or to meet special processes.Control performance evaluation techniques can facilitate operators to manage and monitor a large number of control loops in process production,reduce labor cost and improve efficiency.In this thesis,based on generalized minimum variance control,a CARMA model identification algorithm for the mathematical model of the controlled object with unknown parameters,order and delay is proposed,and corresponding control performance evaluation methods are proposed for different complex control loops,such as cascade,ratio and feedforward-feedback control systems.If the current control performance is poor,the operator can check the controller parameters and perform tuning.Finally,some control loops in the coal gasifier system are built in Simulink simulation platform and the effectiveness of the method is confirmed by industrial tests.The failure of the control valve in the industrial production process may affect the stability of the entire control system.This thesis proposes a datadriven fault diagnosis method for the control valve.The residual data of the actual measured value and the estimated value of the data identification model are used to extract the internal leakage and external leakage characteristics of the valve.Then,the extracted classification features are classified based on the Mahalanobis distance,and the autocorrelation analysis of the residuals of the valve input and output data is used to diagnose whether the valve has a viscous fault.In addition,the EMD separation method is used to separate the output signal of the valve viscous system.The control performance benchmark is corrected by the compensation amount of the variance of the nonlinear component signal to obtain a more practical control performance index.Finally,the industrial data generated by the coal gasifier control valve is used to verify the effectiveness of the above method.Finally,according to the proposed method,an industrial control loop performance monitoring and actuator fault diagnosis system is developed.The software realizes the performance evaluation of complex control loops and actuator fault diagnosis.The evaluation results and fault information generated by the system are stored in the database in real time,and can be published through the web page.The system releases information to facilitate the maintenance and viewing of operators and managers.This software is applied in the work of control loop performance evaluation of large coal gasification system and valve fault diagnosis of total oxygen flow and central oxygen flow control loop,and has achieved good results.