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Ball bearing vibration data for detecting and quantifying spall faults
Ball bearings are essential components of electromechanical systems, and their failures significantly affect the service lifetime of these systems. For highly reliable and safety-critical electromechanical systems in energy and aerospace sectors, early bearing fault detection and quantification are...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023968/ https://www.ncbi.nlm.nih.gov/pubmed/36942099 http://dx.doi.org/10.1016/j.dib.2023.109019 |
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author | Ismail, Mohamed A.A. Windelberg, Jens Bierig, Andreas Bravo, Iñaki Arnaiz, Aitor |
author_facet | Ismail, Mohamed A.A. Windelberg, Jens Bierig, Andreas Bravo, Iñaki Arnaiz, Aitor |
author_sort | Ismail, Mohamed A.A. |
collection | PubMed |
description | Ball bearings are essential components of electromechanical systems, and their failures significantly affect the service lifetime of these systems. For highly reliable and safety-critical electromechanical systems in energy and aerospace sectors, early bearing fault detection and quantification are crucial. The vibration measurements of bearing fatigue faults, i.e., spalls, are typically induced by multiple excitation mechanisms depending on the fault size and the operating conditions. This data article contains vibration datasets for faulty ball bearings, including the common vibration excitation mechanisms for various fault sizes and operating conditions. These faults are artificially seeded on bearing races by a precise machining process to emulate realistic fatigue faults. This data article is beneficial for better understanding the vibration signal characteristics under different fault sizes and for validating condition monitoring methods for various industrial and aerospace applications. |
format | Online Article Text |
id | pubmed-10023968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100239682023-03-19 Ball bearing vibration data for detecting and quantifying spall faults Ismail, Mohamed A.A. Windelberg, Jens Bierig, Andreas Bravo, Iñaki Arnaiz, Aitor Data Brief Data Article Ball bearings are essential components of electromechanical systems, and their failures significantly affect the service lifetime of these systems. For highly reliable and safety-critical electromechanical systems in energy and aerospace sectors, early bearing fault detection and quantification are crucial. The vibration measurements of bearing fatigue faults, i.e., spalls, are typically induced by multiple excitation mechanisms depending on the fault size and the operating conditions. This data article contains vibration datasets for faulty ball bearings, including the common vibration excitation mechanisms for various fault sizes and operating conditions. These faults are artificially seeded on bearing races by a precise machining process to emulate realistic fatigue faults. This data article is beneficial for better understanding the vibration signal characteristics under different fault sizes and for validating condition monitoring methods for various industrial and aerospace applications. Elsevier 2023-03-01 /pmc/articles/PMC10023968/ /pubmed/36942099 http://dx.doi.org/10.1016/j.dib.2023.109019 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Ismail, Mohamed A.A. Windelberg, Jens Bierig, Andreas Bravo, Iñaki Arnaiz, Aitor Ball bearing vibration data for detecting and quantifying spall faults |
title | Ball bearing vibration data for detecting and quantifying spall faults |
title_full | Ball bearing vibration data for detecting and quantifying spall faults |
title_fullStr | Ball bearing vibration data for detecting and quantifying spall faults |
title_full_unstemmed | Ball bearing vibration data for detecting and quantifying spall faults |
title_short | Ball bearing vibration data for detecting and quantifying spall faults |
title_sort | ball bearing vibration data for detecting and quantifying spall faults |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023968/ https://www.ncbi.nlm.nih.gov/pubmed/36942099 http://dx.doi.org/10.1016/j.dib.2023.109019 |
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