基于UIO的航空发动机控制系统传感器故障诊断

覃道亮; 何皑; 孔祥兴; 王曦

基于UIO的航空发动机控制系统传感器故障诊断

北京航空航天大学能源与动力工程学院,北京 100191

基金项目: 航空科学基金(2009ZB51); 航空推进技术验证计划

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- 文章访问数: 1991
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- 被引次数: 0
出版历程
- 收稿日期: 2010-05-06
- 修回日期: 2010-09-07
- 刊出日期: 2011-06-28

UIO-based sensor fault diagnosis for aero-engine control systems

School of Jet Propulsion, Beijing University of Aeronautics and Astronautics,Beijing 100191,China

摘要

摘要: 研究了航空发动机控制系统传感器鲁棒故障检测与隔离问题,提出了一种克服不同干扰对控制系统诊断性能影响的方法.应用未知输入观测器(unknown input observer,简称UIO)理论来解耦航空发动机动态系统干扰,并针对控制系统传感器设计一族UIO,提取出一系列的传感器残差特征数据,通过分析残差队列的幅值特性,实现航空发动机控制系统传感器故障诊断.在高斯白噪声、模型工作点变化和非高斯噪声三类干扰下的数字仿真结果表明,不管何种干扰,UIO诊断方法均能检测和隔离出传感器故障,在诊断鲁棒性方面,要优于Kalman滤波器诊断算法.
- 未知输入观测器(UIO) /
- 航空发动机控制 /
- 传感器故障 /
- 故障诊断 /
- 残差生成
Abstract: The problem of sensor fault detection and isolation for aero-engine control systems was studied and an approach to overcome the impact of various disturbances on the performance in diagnosis of the control systems was proposed in this paper.This approach applied unknown input observer (UIO) theory to decouple the disturbance in the aero-engine dynamic model.Then,a bank of UIOs for the sensors in the control system were designed,and a series of residual features for the control system's sensors were extracted.By analyzing the characteristics of magnitudes in the queue of residuals,this paper accomplished the sensor-fault detection and isolation.Numerical simulation results with the disturbances of Gaussian white noise,a moderate change in the operating point of the engine,and non-Gaussian noise show that,the UIO-based method can effectively detect and isolate sensor faults irrespective of the class of the system disturbance,and outperform the Kalman filter-based algorithm in term of diagnosis robustness.
- unknown input observer (UIO) /
- aero-engine control /
- sensor fault /

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参考文献(16)

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