Multi-Fault Diagnosis of an Aero-Engine Control System Using Joint Sliding Mode Observers

被引:23
|
作者
Gou, Linfeng [1 ]
Shen, Yawen [1 ]
Zheng, Hua [1 ]
Zeng, Xianyi [1 ]
机构
[1] Northwestern Polytech Univ, Sch Power & Energy, Xian 710072, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷 / 08期
关键词
Aero-engine; control system; fault diagnosis; sliding mode observer; LITHIUM-ION BATTERIES; KALMAN FILTER; ATTITUDE STABILIZATION; ROBUST; DESIGN;
D O I
10.1109/ACCESS.2020.2964572
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An aero-engine is a complex aerodynamic thermal system, which can operate in extreme environments for long periods. It is crucial to diagnose any faults of the aero-engine control system accurately. At present, most aero-engine control system fault diagnosis schemes suffer from large interference, significant chattering, and lowestimation accuracy. To diagnose multi-faults of the control system effectively, we introduce and investigate a new fault diagnosis scheme in this paper, which uses joint sliding mode observers. First, we develop a mathematical model for multi-faults in the control system, which can describe actuator and sensor faults in detail. Then, we design the joint sliding mode observers for fault detection and isolation (FDI), using the sliding mode variable structure term to reduce the coupling effect. Finally, during the fault estimation process, we use a pseudo-sliding form to reduce the chattering problem and suppress the impact of interference, which leads to an accurate estimation of the multi-fault characteristics. The simulation results show that, the proposed scheme can effectively detect and isolate faults, which enables superior timeliness and accuracy compared to a conventional sliding mode observer scheme. During the process of fault estimation, the effect of chattering is reduced, which shows the advantages of strong sensitivity and high estimation accuracy.
引用
收藏
页码:10186 / 10197
页数:12
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