Early fault detection and diagnosis of high-performance electric motors has been an active area of research for the past two decades. This work presents a practical session that facilitates instructing students in this field. To meet this objective, fault diagnostic methods based on the Fourier transform and the wavelet transform are successfully applied by means of processing and examining the frequency content of the stator currents acquired from healthy and faulty permanent magnet synchronous machines (PMSMs). The goal of this practical lab is to introduce Master’s degree students to the topic of fault detection by covering both stationary and nonstationary operating conditions of the motor under study. The Technical University of Catalonia (UPC) has successfully incorporated the learning methodology proposed in this paper in a practical session of an electronic engineering course. The effectiveness of the proposed practical lab has been assessed using the results of a satisfaction questionnaire answered by students involved in the course.

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