Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors
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| Format: | Artículo científico |
| Langue: | en |
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Universidad Nacional Autónoma de México
2015
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| _version_ | 1876475315353550848 |
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| author | D. Camarena-Martinez |
| author_facet | D. Camarena-Martinez |
| contents | Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors D. Camarena-Martinez R. Osornio-Rios R. J. Romero-Troncoso A. Garcia-Perez Ingeniería high multiple fault diagnosis induction motors Empirical mode decomposition Detection of failures in induction motors is one of the most important concerns in industry. An unexpected fault in the induction motors can cause a loss of financial resources and waste of time that most companies cannot afford. The contribution of this paper is a fusion of the Empirical Mode Decomposition (EMD) and Multiple Signal Classification (MUSIC) methodologies for detection of multiple combined faul ts which provides an accurate and effective strategy for the motor condition diagnosis. 2015 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47436895015 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.1 Vol.13 |
| format | Artículo científico |
| id | redalyc_47436895015 |
| institution | Redalyc |
| language | en |
| publishDate | 2015 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors D. Camarena-Martinez Ingeniería high multiple fault diagnosis induction motors Empirical mode decomposition Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors D. Camarena-Martinez R. Osornio-Rios R. J. Romero-Troncoso A. Garcia-Perez Ingeniería high multiple fault diagnosis induction motors Empirical mode decomposition Detection of failures in induction motors is one of the most important concerns in industry. An unexpected fault in the induction motors can cause a loss of financial resources and waste of time that most companies cannot afford. The contribution of this paper is a fusion of the Empirical Mode Decomposition (EMD) and Multiple Signal Classification (MUSIC) methodologies for detection of multiple combined faul ts which provides an accurate and effective strategy for the motor condition diagnosis. 2015 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47436895015 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.1 Vol.13 |
| title | Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors |
| topic | Ingeniería high multiple fault diagnosis induction motors Empirical mode decomposition |
| url | https://www.redalyc.org/articulo.oa?id=47436895015 |