An introduction to fault diagnosis of permanent magnet synchronous machines in master's degree courses

被引:4
作者
Riba Ruiz, Jordi-Roger [1 ,2 ]
Garcia Espinosa, Antonio [2 ]
Romeral, Luis [2 ]
Antonio Ortega, Juan [2 ]
机构
[1] Univ Politecn Cataluna, Escola Ingn Igualada, E-08028 Barcelona, Spain
[2] Univ Politecn Cataluna, Dept Elect Engn, E-08028 Barcelona, Spain
关键词
computed-assisted learning; fault diagnosis; wavelet; time-frequency methods; permanent magnet motors; NONSTATIONARY CONDITIONS; DYNAMIC ECCENTRICITY; WAVELET TRANSFORM; MOTORS; SIGNAL; TOOL;
D O I
10.1002/cae.20479
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (c) 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 21: 349359, 2013; View this article online at wileyonlinelibrary.com; DOI 10.1002/cae.20479
引用
收藏
页码:349 / 359
页数:11
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