双闭环比值控制系统传感器故障诊断方法

Sensor Fault Diagnosis Method of Double Closed Loop Ratio Control System

双闭环比值控制系统由于主从回路滞后效应和闭环回路调节作用,使其故障诊断较为复杂。针对该系统传感器故障难以识别的问题,通过分析反映系统动态特性的实时数据,提出一种基于数据驱动的故障诊断方法。利用拉伊达准则标定检测阈值建立故障检测模型;利用传感器故障传播的滞后特性建立故障定位模型;利用突变故障的幅值特性建立了故障估计模型;利用故障调节动态过程的变化趋势建立了故障分离模型;通过在线数据标定获得了故障诊断动态模型。通过实验验证该方法的有效性和高精度。研究结果表明,所提方法适用于一般双闭环比值控制系统传感器的实时故障诊断,其中故障检测准确率可达98.5%,故障定位准确率可达98.5%,故障估计准确率可达99.28%,故障分离准确率可达98%。

The fault diagnosis of double closed loop ratio control system is more complicated due to the lag effect of master slave loop and the regulating effect of closed loop.Aiming at the problem that sensor faults are difficult to be identified in this system,a data-driven fault diagnosis method is proposed by analyzing the real-time data reflecting the dynamic characteristics of the system.In this method,a fault detection model is established by calibrating the detection threshold using Pauta criterion;A fault location model is established based on the hysteresis characteristic of sensor fault propagation;a fault estimation model is established based on the amplitude characteristics of abrupt faults;a fault separation model is established by using the change trend of dynamic process of fault regulation;and a dynamic model of fault diagnosis is obtained by online data calibration.The effectiveness and high precision of the proposed method are verified by experiments.The results show that the proposed method is suitable for the real-time fault diagnosis of sensors in general double closed loop ratio control system.The accuracy of fault detection can reach 98.5%,the accuracy of fault location can reach 98.5%,the accuracy of fault estimation can reach 99.28%,and the accuracy of fault separation can reach 98%.