基于数据驱动的主燃油计量装置故障诊断

Data-driven fault diagnosis of main fuel metering device

为建立主燃油计量装置的故障诊断方法,提出一种基于快速存取记录器(QAR)数据的燃油计量参数估计模型建模方法,并结合液压机械控制装置工作原理,给出了基于燃油计量参数残差设计的主燃油计量装置故障诊断方案。设计基于系统辨识的燃油计量活门位置(FMVP)估计模型,采取降阶处理策略以提高模型的估计精度和动态响应速度,在此基础上给出基于多项式拟合的燃油流量(FF)估计模型。结果表明:所建立的FMVP模型估计残差不超过±2%,FF估计模型残差不超过±5%;该方案能够有效地诊断出燃油计量活门故障、线性可变差动位移传感器故障和热式流量计故障。该方案结构简单,不需要大量的调试技术,提高了故障检测精度,具有工程应用前景。

To establish a fault diagnosis method for the main fuel metering device,a Quick Access Record⁃er(QAR)data-based modeling approach was proposed for estimating fuel metering parameters.A fault diagnosis scheme for the main fuel metering device was given by combining fuel metering parameter residuals with the work⁃ing principle of hydraulic mechanical control device.A fuel metering valve position(FMVP)estimation model was designed using system identification,whose estimation accuracy and dynamic response speed were improved using a model order reduction strategy.Furthermore,a fuel flow(FF)estimation model was presented by polyno⁃mial fitting.The results showed that the estimated residuals of the established FMVP model do not exceed±2%,and the residuals of the FF model do not exceed±5%.The proposed method can effectively diagnose faults in the fuel metering valve,the linear variable differential transformer displacement sensor,and the thermal flowmeter.The proposed scheme has a simple structure and does not require extensive debugging techniques,and offers higher detection accuracy as well as promising engineering application prospects.