A Hybrid Approach of Fault Inference and Fault Identification for Aircraft Fault Diagnosis
Logical inference based on a cockpit instruments fault tree (FT) sometimes cannot give a correct diagnosis of failures. In addition, in flight control systems (FCS), a fault identification method based on the multiple-model (MM) estimator cannot find the
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A Hybrid Approach of Fault Inference and Fault Identification for Aircraft Fault Diagnosis Xianhui Liu and Zhijuan Liu
Abstract Logical inference based on a cockpit instruments fault tree (FT) sometimes cannot give a correct diagnosis of failures. In addition, in flight control systems (FCS), a fault identification method based on the multiple-model (MM) estimator cannot find the basic fault cause. To deal with these problems, a hybrid approach which is capable of integrating inference and fault identification is proposed. In this approach, the event nodes of the FT which have correlations to the FCS are separated into modules. Each module corresponds to a fault mode. To use these correlations, the inference and MM method can share fault information. Simulation results show that the proposed diagnosis approach is helpful in detecting the root cause of failure and is more correct than single fault inference method.
Keywords Hybrid Fault diagnosis Cockpit instrumentation Logical inference Multiple-model
17.1 Introduction The cockpit instrumentation system plays an important role in human operation because it provides information with which the pilots operate the aircraft [1]. Therefore, an accurate fault diagnosis method in cockpit instrumentation systems
X. Liu (&) CAD Research Center, Tongji University, 200092 Shanghai, China e-mail: [email protected] Z. Liu (&) Department of Automation, Tsinghua University, 100084 Beijing, China e-mail: [email protected]
W. Lu et al. (eds.), Proceedings of the 2012 International Conference on Information Technology and Software Engineering, Lecture Notes in Electrical Engineering 211, DOI: 10.1007/978-3-642-34522-7_17, Springer-Verlag Berlin Heidelberg 2013
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is necessity for modern aircrafts. The fault tree (FT) [2] and intelligence inference [3] method are always used in cockpit instrumentation systems. Inferences based on FT sometimes cannot determine the faults. For instance, when the logical gate between the upper and lower nodes is ‘‘OR’’ in the FT, there is the possibility that the events in the lower node may all happen or the possibility that only one will happens if the event in the upper node happens. To ensure more correct diagnosis results, one has to use other information such as of the flight control system (FCS) fault information. In this paper, a hybrid fault diagnosis method is proposed which integrates cockpit instruments FT inference with the multiple-model (MM) [4] diagnosis method in FCS. MM method employs a bank of Kalman filters, each based on a failure model. A general aviation aircraft cockpit instrumentation system is given in NASA report [5, 6]. The MM method and the logical inference run simultaneously. The MM estimator can obtain the fault mode of FCS while the fault tree can obtain fault events. The fault modes of the MM estimator may have corresponding events in the cockpit instruments fault tree. Therefore, they can contact each other based on these event nodes and share fault information with
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