The diagnosis of induction machine faults is commonly carried out by means of Motor Current Signature Analysis (MCSA), i.e., by classical spectrum analysis of the input currents. Specifically in case of broken bars, the amplitude of the left sideband component of a phase current is monitored in order to sense its signature. However MCSA has some drawbacks that are still under investigation. The main concern is that an efficient frequency transformation cannot be made under speed–varying condition, since slip and speed vary and so does the left sideband frequency. In this paper, an advanced use of the Discrete Wavelet Transform (DWT) is proposed to overcome the limitation of the classical approaches based on Fourier Analysis (FA). Experimental and simulation results show the validity of the developed approach, leading to an effective diagnosis method for broken bars in induction machines.

Advanced Diagnosis of Broken Bar Fault in Induction Machines by Using Discrete Wavelet Transform Under Time-Varying Condition

GRITLI, YASSER;ROSSI, CLAUDIO;ZARRI, LUCA;FILIPPETTI, FIORENZO;CASADEI, DOMENICO;STEFANI, ANDREA
2011

Abstract

The diagnosis of induction machine faults is commonly carried out by means of Motor Current Signature Analysis (MCSA), i.e., by classical spectrum analysis of the input currents. Specifically in case of broken bars, the amplitude of the left sideband component of a phase current is monitored in order to sense its signature. However MCSA has some drawbacks that are still under investigation. The main concern is that an efficient frequency transformation cannot be made under speed–varying condition, since slip and speed vary and so does the left sideband frequency. In this paper, an advanced use of the Discrete Wavelet Transform (DWT) is proposed to overcome the limitation of the classical approaches based on Fourier Analysis (FA). Experimental and simulation results show the validity of the developed approach, leading to an effective diagnosis method for broken bars in induction machines.
IEEE International Electric Machines And Drives Conference
424
429
Y. Gritli; C. Rossi; L. Zarri; F. Filippetti; A. Chatti; D. Casadei; A. Stefani
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/106932
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