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Fault Detection of Planetary Gears Based on Signal Space Constellations

A new method to process the vibration signal acquired by an accelerometer placed in a planetary gearbox housing is proposed, which is useful to detect potential faults. The method is based on the phenomenological model and consists of the projection of the healthy vibration signals onto an orthonorm...

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Detalles Bibliográficos
Autores principales: Martincorena-Arraiza, Maite, De La Cruz Blas, Carlos A., Lopez-Martin, Antonio, Vicuña, Cristián Molina, Matías, Ignacio R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749641/
https://www.ncbi.nlm.nih.gov/pubmed/35009906
http://dx.doi.org/10.3390/s22010366
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author Martincorena-Arraiza, Maite
De La Cruz Blas, Carlos A.
Lopez-Martin, Antonio
Vicuña, Cristián Molina
Matías, Ignacio R.
author_facet Martincorena-Arraiza, Maite
De La Cruz Blas, Carlos A.
Lopez-Martin, Antonio
Vicuña, Cristián Molina
Matías, Ignacio R.
author_sort Martincorena-Arraiza, Maite
collection PubMed
description A new method to process the vibration signal acquired by an accelerometer placed in a planetary gearbox housing is proposed, which is useful to detect potential faults. The method is based on the phenomenological model and consists of the projection of the healthy vibration signals onto an orthonormal basis. Low pass components representation and Gram–Schmidt’s method are conveniently used to obtain such a basis. Thus, the measured signals can be represented by a set of scalars that provide information on the gear state. If these scalars are within a predefined range, then the gear can be diagnosed as correct; in the opposite case, it will require further evaluation. The method is validated using measured vibration signals obtained from a laboratory test bench.
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spelling pubmed-87496412022-01-12 Fault Detection of Planetary Gears Based on Signal Space Constellations Martincorena-Arraiza, Maite De La Cruz Blas, Carlos A. Lopez-Martin, Antonio Vicuña, Cristián Molina Matías, Ignacio R. Sensors (Basel) Article A new method to process the vibration signal acquired by an accelerometer placed in a planetary gearbox housing is proposed, which is useful to detect potential faults. The method is based on the phenomenological model and consists of the projection of the healthy vibration signals onto an orthonormal basis. Low pass components representation and Gram–Schmidt’s method are conveniently used to obtain such a basis. Thus, the measured signals can be represented by a set of scalars that provide information on the gear state. If these scalars are within a predefined range, then the gear can be diagnosed as correct; in the opposite case, it will require further evaluation. The method is validated using measured vibration signals obtained from a laboratory test bench. MDPI 2022-01-04 /pmc/articles/PMC8749641/ /pubmed/35009906 http://dx.doi.org/10.3390/s22010366 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Martincorena-Arraiza, Maite
De La Cruz Blas, Carlos A.
Lopez-Martin, Antonio
Vicuña, Cristián Molina
Matías, Ignacio R.
Fault Detection of Planetary Gears Based on Signal Space Constellations
title Fault Detection of Planetary Gears Based on Signal Space Constellations
title_full Fault Detection of Planetary Gears Based on Signal Space Constellations
title_fullStr Fault Detection of Planetary Gears Based on Signal Space Constellations
title_full_unstemmed Fault Detection of Planetary Gears Based on Signal Space Constellations
title_short Fault Detection of Planetary Gears Based on Signal Space Constellations
title_sort fault detection of planetary gears based on signal space constellations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749641/
https://www.ncbi.nlm.nih.gov/pubmed/35009906
http://dx.doi.org/10.3390/s22010366
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