Hybrid Fault Detection and Isolation Techniques for Aircraft Inertial Measurement Sensors

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Kim, Seungkeun; Kim, Youdan; Park, Chan Gook; Jung, Insung
Issue Date
AIAA Guidance, Navigation, and Control Conference and Exhibit, 16-19 August 2004, Providence, Rhode Island
In this paper, a redundancy management system for aircraft is studied, and fault
detection and isolation algorithms of inertial sensor system are proposed. Contrary to the
conventional aircraft systems, UAV system cannot allow triple or quadruple hardware
redundancy due to the limitations on space and weight. In the UAV system with dual sensors,
it is very difficult to identify the faulty sensor. Also, conventional fault detection and
isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this
paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed,
which combines a parity equation approach with the wavelet based technique. Second,
analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI
method utilizing the threshold value and the confirmation time. To provide the reference
value for detecting the fault, residuals are calculated using the Extended Kalman filter. To
verify the effectiveness of the proposed FDI methods, numerical simulations are performed.
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Others_기계항공공학부
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