Cargando…

Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †

In this paper, a diagnostic procedure for rotor bar faults in induction motors is presented, based on the Hilbert and discrete wavelet transforms. The method is compared with other procedures with the same data, which are based on time–frequency analysis, frequency analysis and time domain. The resu...

Descripción completa

Detalles Bibliográficos
Autores principales: Sintoni, Michele, Macrelli, Elena, Bellini, Alberto, Bianchini, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866328/
https://www.ncbi.nlm.nih.gov/pubmed/36679843
http://dx.doi.org/10.3390/s23021046
_version_ 1784876063022645248
author Sintoni, Michele
Macrelli, Elena
Bellini, Alberto
Bianchini, Claudio
author_facet Sintoni, Michele
Macrelli, Elena
Bellini, Alberto
Bianchini, Claudio
author_sort Sintoni, Michele
collection PubMed
description In this paper, a diagnostic procedure for rotor bar faults in induction motors is presented, based on the Hilbert and discrete wavelet transforms. The method is compared with other procedures with the same data, which are based on time–frequency analysis, frequency analysis and time domain. The results show that this method improves the rotor fault detection in transient conditions. Variable speed drive applications are common in industry. However, traditional condition monitoring methods fail in time-varying conditions or with load oscillations. This method is based on the combined use of the Hilbert and discrete wavelet transforms, which compute the energy in a bandwidth corresponding to the maximum fault signature. Theoretical analysis, numerical simulation and experiments are presented, which confirm the enhanced performance of the proposed method with respect to prior solutions, especially in time-varying conditions. The comparison is based on quantitative analysis that helps in choosing the optimal trade-off between performance and (computational) cost.
format Online
Article
Text
id pubmed-9866328
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-98663282023-01-22 Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison † Sintoni, Michele Macrelli, Elena Bellini, Alberto Bianchini, Claudio Sensors (Basel) Article In this paper, a diagnostic procedure for rotor bar faults in induction motors is presented, based on the Hilbert and discrete wavelet transforms. The method is compared with other procedures with the same data, which are based on time–frequency analysis, frequency analysis and time domain. The results show that this method improves the rotor fault detection in transient conditions. Variable speed drive applications are common in industry. However, traditional condition monitoring methods fail in time-varying conditions or with load oscillations. This method is based on the combined use of the Hilbert and discrete wavelet transforms, which compute the energy in a bandwidth corresponding to the maximum fault signature. Theoretical analysis, numerical simulation and experiments are presented, which confirm the enhanced performance of the proposed method with respect to prior solutions, especially in time-varying conditions. The comparison is based on quantitative analysis that helps in choosing the optimal trade-off between performance and (computational) cost. MDPI 2023-01-16 /pmc/articles/PMC9866328/ /pubmed/36679843 http://dx.doi.org/10.3390/s23021046 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sintoni, Michele
Macrelli, Elena
Bellini, Alberto
Bianchini, Claudio
Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †
title Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †
title_full Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †
title_fullStr Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †
title_full_unstemmed Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †
title_short Condition Monitoring of Induction Machines: Quantitative Analysis and Comparison †
title_sort condition monitoring of induction machines: quantitative analysis and comparison †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866328/
https://www.ncbi.nlm.nih.gov/pubmed/36679843
http://dx.doi.org/10.3390/s23021046
work_keys_str_mv AT sintonimichele conditionmonitoringofinductionmachinesquantitativeanalysisandcomparison
AT macrellielena conditionmonitoringofinductionmachinesquantitativeanalysisandcomparison
AT bellinialberto conditionmonitoringofinductionmachinesquantitativeanalysisandcomparison
AT bianchiniclaudio conditionmonitoringofinductionmachinesquantitativeanalysisandcomparison