System identification of permanent magnet machines and its applications to inter-turn fault detection

Permanent magnet machines are of high power density, high efficiency, small weight, and high reliability, and hence have found extensive applications. This paper employs system identification methods for stator winding fault detection and isolation, under noisy measurement data. Algorithms, estimation accuracy, and convergence properties are established. Simulation studies demonstrate the algorithms and their detection capability and reliability. Simulation results are used to illustrate potential usage of the methods.