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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...
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/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. |
format | Online Article Text |
id | pubmed-10344648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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