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Sensor Fault Diagnosis for Improving the Availability of Electrical Drives

Abstract : The paper describes a Fault Detection and Diagnosis structure of mechanical and current sensors faults of a Permanent Magnet Synchronous Machine (PMSM) drive. The method is based on two interconnected observers: an Extended Kalman Filter (EKF) and a Model Reference Adaptive System (MRAS) observer. The EKF, thanks to its optimality is designed to estimate the position in case of mechanical sensor fault and despite sensor current fault. The MRAS estimates the phase currents using the actual position and speed. The computation and sort of the residuals (difference between measured and estimated values) allows the fault isolation. The structure is evaluated on a 1.1 kW test bed with mechanical and phase current sensor faults. The experimental results are so far promising with the capability of detection and diagnosis of the proposed structure.
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Contributor : Thierry Leblanc <>
Submitted on : Friday, January 17, 2014 - 3:10:14 PM
Last modification on : Monday, December 14, 2020 - 12:28:40 PM



Sidath Diao, Demba Diallo, Zaatar Makni, Claude Marchand, Jean-Francois Bisson. Sensor Fault Diagnosis for Improving the Availability of Electrical Drives. IECON 2013, Nov 2013, Vienne, Austria. pp.3108 - 3113, ⟨10.1109/IECON.2013.6699625⟩. ⟨hal-00932687⟩



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