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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...

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Autores principales: Ismail, Mohamed A.A., Windelberg, Jens, Bierig, Andreas, Bravo, Iñaki, Arnaiz, Aitor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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.
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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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