Aplicaciones de wavelets en la detección de fallas de máquinas de inducción

Translated title of the contribution: Applications of wavelets in induction machine fault detection

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

This paper presents a new wavelet-based algorithm for three-phase induction machine fault detection. This new method uses the standard deviation of wavelet coefficients, obtained from n-level decomposition of each phase voltage and current, to identify single-phasing faults or unbalanced stator resistance faults in induction machines. The proposed algorithm can operate independent of the operational frequency, fault type and loading conditions. Results show that this algorithm has better detection response than the Fourier transform-based techniques.

Original languageSpanish
Pages (from-to)158-164
Number of pages7
JournalIngeniare
Volume18
Issue number2
DOIs
StatePublished - Jan 1 2010

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Fault detection
Stators
Fourier transforms
Decomposition
Electric potential

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

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title = "Aplicaciones de wavelets en la detecci{\'o}n de fallas de m{\'a}quinas de inducci{\'o}n",
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Aplicaciones de wavelets en la detección de fallas de máquinas de inducción. / Schmitt, Erick; Idowu, Peter; Morales, Aldo W.

In: Ingeniare, Vol. 18, No. 2, 01.01.2010, p. 158-164.

Research output: Contribution to journalArticle

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AB - This paper presents a new wavelet-based algorithm for three-phase induction machine fault detection. This new method uses the standard deviation of wavelet coefficients, obtained from n-level decomposition of each phase voltage and current, to identify single-phasing faults or unbalanced stator resistance faults in induction machines. The proposed algorithm can operate independent of the operational frequency, fault type and loading conditions. Results show that this algorithm has better detection response than the Fourier transform-based techniques.

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