Abstract
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 low estimation 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.
Highlights
An aero-engine is an aerodynamic thermal system that integrates technologies such as aircraft, electricity, gas, and fluid
To make up for the shortcomings of the conventional sliding mode observer, we design a more effective multifault diagnosis scheme for the aero-engine control system using joint sliding mode observers, which can describe all possible faults by multi-fault model
When multi-faults occur in the control system, we need to design joint sliding mode observers
Summary
An aero-engine is an aerodynamic thermal system that integrates technologies such as aircraft, electricity, gas, and fluid. To make better use of SMO for aeroengine control system fault diagnosis, the following problems need to be solved: 1) Existing control system fault models cannot describe multi-faults accurately; 2) Due to coupling between different faults [23], problems such as insensitive reaction, false positives and false negatives may occur during the fault diagnosis process; 3) The chattering problem of the sliding mode observer affects the estimation accuracy negatively [24]. To make up for the shortcomings of the conventional sliding mode observer, we design a more effective multifault diagnosis scheme for the aero-engine control system using joint sliding mode observers, which can describe all possible faults by multi-fault model. This method shows a strong fault identification and separation capability, and improves the estimation accuracy, which has the following advantages compared to the conventional sliding mode observer method:
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