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Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (S...

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Detalles Bibliográficos
Autores principales: Burriel-Valencia, Jordi, Puche-Panadero, Ruben, Martinez-Roman, Javier, Sapena-Bano, Angel, Pineda-Sanchez, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795768/
https://www.ncbi.nlm.nih.gov/pubmed/29316650
http://dx.doi.org/10.3390/s18010146
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author Burriel-Valencia, Jordi
Puche-Panadero, Ruben
Martinez-Roman, Javier
Sapena-Bano, Angel
Pineda-Sanchez, Manuel
author_facet Burriel-Valencia, Jordi
Puche-Panadero, Ruben
Martinez-Roman, Javier
Sapena-Bano, Angel
Pineda-Sanchez, Manuel
author_sort Burriel-Valencia, Jordi
collection PubMed
description The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources.
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spelling pubmed-57957682018-02-13 Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window Burriel-Valencia, Jordi Puche-Panadero, Ruben Martinez-Roman, Javier Sapena-Bano, Angel Pineda-Sanchez, Manuel Sensors (Basel) Article The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources. MDPI 2018-01-06 /pmc/articles/PMC5795768/ /pubmed/29316650 http://dx.doi.org/10.3390/s18010146 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Burriel-Valencia, Jordi
Puche-Panadero, Ruben
Martinez-Roman, Javier
Sapena-Bano, Angel
Pineda-Sanchez, Manuel
Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window
title Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window
title_full Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window
title_fullStr Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window
title_full_unstemmed Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window
title_short Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window
title_sort fault diagnosis of induction machines in a transient regime using current sensors with an optimized slepian window
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795768/
https://www.ncbi.nlm.nih.gov/pubmed/29316650
http://dx.doi.org/10.3390/s18010146
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