Online Detection and Classification of Rotor and Load Defects in PMSMs Based on Hall Sensor Measurements

Online monitoring and diagnostics of permanent magnet synchronous motors (PMSMs) is becoming important with the increasing demand in PMSM applications. Most of the research effort focuses on motor current signature analysis (MCSA) as it can provide remote, online monitoring at low cost. However, all types of defects that produce asymmetries in the PMSM rotor or load produce identical rotor rotational frequency components. This is a serious limitation when applying MCSA since it can produce false indications and degrade the sensitivity of fault detection. The requirement of complex time–frequency analysis techniques is another limitation of MCSA for applications with speed variations. In this paper, the feasibility of using analog Hall sensor signals to complement MCSA for detection and classification of rotor- and load-related defects is investigated. It is shown that Hall sensors installed in machines for initial rotor position estimation can be used with minimal hardware modifications to detect and classify signatures produced by the rotor and load for cases where MCSA fails, even during transient conditions. Experimental testing performed on an interior permanent magnet synchronous motor (IPMSM) under eccentricity, local demagnetization, and load unbalance conditions shows that the reliability and sensitivity of fault detection in PMSM systems can be improved at low added cost.