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Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study
In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable w...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3926619/ https://www.ncbi.nlm.nih.gov/pubmed/24424467 http://dx.doi.org/10.3390/s140101372 |
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author | Qu, Yongzhi He, David Yoon, Jae Van Hecke, Brandon Bechhoefer, Eric Zhu, Junda |
author_facet | Qu, Yongzhi He, David Yoon, Jae Van Hecke, Brandon Bechhoefer, Eric Zhu, Junda |
author_sort | Qu, Yongzhi |
collection | PubMed |
description | In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative study for gearbox tooth damage level diagnostics using AE and vibration measurements, the first known attempt to compare the gearbox fault diagnostic performance of AE- and vibration analysis-based approaches using the same sampling rate. Partial tooth cut faults are seeded in a gearbox test rig and experimentally tested in a laboratory. Results have shown that the AE-based approach has the potential to differentiate gear tooth damage levels in comparison with the vibration-based approach. While vibration signals are easily affected by mechanical resonance, the AE signals show more stable performance. |
format | Online Article Text |
id | pubmed-3926619 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-39266192014-02-18 Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study Qu, Yongzhi He, David Yoon, Jae Van Hecke, Brandon Bechhoefer, Eric Zhu, Junda Sensors (Basel) Article In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative study for gearbox tooth damage level diagnostics using AE and vibration measurements, the first known attempt to compare the gearbox fault diagnostic performance of AE- and vibration analysis-based approaches using the same sampling rate. Partial tooth cut faults are seeded in a gearbox test rig and experimentally tested in a laboratory. Results have shown that the AE-based approach has the potential to differentiate gear tooth damage levels in comparison with the vibration-based approach. While vibration signals are easily affected by mechanical resonance, the AE signals show more stable performance. Molecular Diversity Preservation International (MDPI) 2014-01-14 /pmc/articles/PMC3926619/ /pubmed/24424467 http://dx.doi.org/10.3390/s140101372 Text en © 2014 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 license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Qu, Yongzhi He, David Yoon, Jae Van Hecke, Brandon Bechhoefer, Eric Zhu, Junda Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study |
title | Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study |
title_full | Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study |
title_fullStr | Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study |
title_full_unstemmed | Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study |
title_short | Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study |
title_sort | gearbox tooth cut fault diagnostics using acoustic emission and vibration sensors — a comparative study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3926619/ https://www.ncbi.nlm.nih.gov/pubmed/24424467 http://dx.doi.org/10.3390/s140101372 |
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