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Dataset of single and double faults scenarios using vibration signals from a rotary machine

This dataset includes vibration sensor data from accelerometers located on the support bearings on a rotary machine designed as a fault simulator. Data collection for known faulty components include: bearing inner and outer raceway faults and bent shaft. 38 singles and double fault scenarios and a o...

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Detalles Bibliográficos
Autores principales: Marshall, Larry, Jensen, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10344648/
https://www.ncbi.nlm.nih.gov/pubmed/37456108
http://dx.doi.org/10.1016/j.dib.2023.109358
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author Marshall, Larry
Jensen, David
author_facet Marshall, Larry
Jensen, David
author_sort Marshall, Larry
collection PubMed
description This dataset includes vibration sensor data from accelerometers located on the support bearings on a rotary machine designed as a fault simulator. Data collection for known faulty components include: bearing inner and outer raceway faults and bent shaft. 38 singles and double fault scenarios and a one no fault scenario were collected at three different operating frequencies (shaft rpm). Data was collected for approximately 10 seconds per scenario at a rate of 6400 hertz. Data can be used for machine learning classification.
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spelling pubmed-103446482023-07-14 Dataset of single and double faults scenarios using vibration signals from a rotary machine Marshall, Larry Jensen, David Data Brief Data Article This dataset includes vibration sensor data from accelerometers located on the support bearings on a rotary machine designed as a fault simulator. Data collection for known faulty components include: bearing inner and outer raceway faults and bent shaft. 38 singles and double fault scenarios and a one no fault scenario were collected at three different operating frequencies (shaft rpm). Data was collected for approximately 10 seconds per scenario at a rate of 6400 hertz. Data can be used for machine learning classification. Elsevier 2023-07-04 /pmc/articles/PMC10344648/ /pubmed/37456108 http://dx.doi.org/10.1016/j.dib.2023.109358 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
Marshall, Larry
Jensen, David
Dataset of single and double faults scenarios using vibration signals from a rotary machine
title Dataset of single and double faults scenarios using vibration signals from a rotary machine
title_full Dataset of single and double faults scenarios using vibration signals from a rotary machine
title_fullStr Dataset of single and double faults scenarios using vibration signals from a rotary machine
title_full_unstemmed Dataset of single and double faults scenarios using vibration signals from a rotary machine
title_short Dataset of single and double faults scenarios using vibration signals from a rotary machine
title_sort dataset of single and double faults scenarios using vibration signals from a rotary machine
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10344648/
https://www.ncbi.nlm.nih.gov/pubmed/37456108
http://dx.doi.org/10.1016/j.dib.2023.109358
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