航空发动机传感器故障鲁棒检测方法

研究发动机传感器故障准确检测问题,现代航空发动机数字电子控制系统对传感器的可靠性要求日益提高。针对航空发动机结构复杂,又工作在高温和高压下,常规采用的传感器故障检测方法的准确性易受到建模误差与外界扰动的影响,造成漏报或误报。为了提高检测精度,提出建立航空发动机数控系统传感器未知输入故障模型,采用特征结构配置的方法,通过配置闭环系统左特征向量实现故障检测残差对不确定性因素的干扰解耦,降低扰动对故障诊断结果的影响。用某型涡扇发动机数控系统传感器故障数字仿真试验表明,所设计的方法对范数有界的不确定量可以实现干扰解耦,抑制干扰对故障检测的影响,改善检测算法的鲁棒性,提高检测结果的准确性,同时满足在线运算的实时性要求。提高了航空发动机的可靠性,保证了安全飞行。

Robust Fault Detection Method of Aircraft Engine Sensors

The requirement for reliability of the sensors is ever increasing in modern aero-engine digital electronic control system.The accuracy of conventional model-based sensor FD method is easily impressionable by modeling error and external disturbances,causing missing report and failures-to-predict.This paper constructed an unknown input fault model of the aero-engine digital control system sensor for solving this problem,using method based on characteristic structure configuration and configuring left feature vector of closed-loop system,so that the disturbance decoupling from fault detection residual to the uncertain factors could be realized,as well as the influence of the disturbance to the fault diagnosis result could be reduced.According to the simulation of the sensor in the digital electronic control system on one turbofan engine,the designed method can realize the disturbance decoupling of the norm-bounded uncertain factors,suppressing affection of the disturbance to the fault detection,improving robustness of the detection algorithm,advancing the accuracy of the test results.While this designed method can satisfy the needs of real-time requirement of online computing,and significantly improve the reliability of aero-engine in engineering application.