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Communication Dans Un Congrès Année : 2014

Sensor Fault Detection for Aircraft Using a Single Kalman Filter and Hidden Markov Models

Résumé

This paper presents a new scheme for sensor fault detection and isolation. It uses a single Kalman filter and a Gaussian hidden Markov model for each of the monitored sensors. This combination is able to simultaneously detect single and multiple sensor faults, still guaranteeing optimal system state estimation. This algorithm also can run on systems with limited computational power. The efficiency of the approach is evaluated through simulation of an aircraft to detect airspeed and GPS sensor faults. The results show fast fault detection and low false-alarm rate.
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Dates et versions

hal-01301765 , version 1 (12-04-2016)

Identifiants

  • HAL Id : hal-01301765 , version 1

Citer

Rudin Konrad, Guillaume Ducard, Roland Y. Siegwart. Sensor Fault Detection for Aircraft Using a Single Kalman Filter and Hidden Markov Models. IEEE Multi-conference on Systems and Control, Oct 2014, Antibes, France. pp.991 - 996. ⟨hal-01301765⟩
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