Diagnosis of Sensor Faults in PMSM and Drive System Based on Structural Analysis

Abstract

This paper presents a model-based fault diagnosis method to detect sensor faults in permanent magnet synchronous motor (PMSM) drives based on structural analysis technique. The structural model is built based on the dynamic model of the PMSM in matrix form, including unknown variables, known variables, and faults. The Dulmage-Mendelsohn (DM) decomposition is applied to evaluate the redundancy of the model and obtain redundant testable sub-models. These testable redundant sub-models are used to form residuals to observe the system state, and distinguish between healthy and faulty conditions. This work investigates faults in eleven sensors in a PMSM drive, thus nine structured residuals are designed to detect and isolate the investigated faults, which are applied to the system at different time intervals. Finally, the effectiveness of the proposed diagnostic approach is experimentally validated on an in-house setup of inverter-fed PMSMs.