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Application of Composite Spectrum in Agricultural Machines
Composite spectrum (CS) is a data-fusion technique that reduces the number of spectra to be analyzed, simplifying the analysis process for machine monitoring and fault detection. In this work, vibration signals from five components of a combine harvester (thresher, chopper, straw walkers, sieve box,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582267/ https://www.ncbi.nlm.nih.gov/pubmed/32993176 http://dx.doi.org/10.3390/s20195519 |
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author | Feijoo, Fernando Gomez-Gil, Francisco Javier Gomez-Gil, Jaime |
author_facet | Feijoo, Fernando Gomez-Gil, Francisco Javier Gomez-Gil, Jaime |
author_sort | Feijoo, Fernando |
collection | PubMed |
description | Composite spectrum (CS) is a data-fusion technique that reduces the number of spectra to be analyzed, simplifying the analysis process for machine monitoring and fault detection. In this work, vibration signals from five components of a combine harvester (thresher, chopper, straw walkers, sieve box, and engine) are obtained by placing four accelerometers along the combine-harvester chassis in non-optimal locations. Four individual spectra (one from each accelerometer) and three CS (non-coherent, coherent and poly-coherent spectra) from 18 cases are analyzed. The different cases result from the combination of three working conditions of the components—deactivated (off), balanced (healthy), and unbalanced (faulty)—and two speeds—idle and maximum revolutions per minute (RPM). The results showed that (i) the peaks can be identified in the four individual spectra that correspond to the rotational speeds of the five components in the analysis; (ii) the three formulations of the CS retain the relevant information from the individual spectra, thereby reducing the number of spectra required for monitoring and detecting rotating unbalances within a combine harvester; and, (iii) data noise reduction is observed in coherent and poly-coherent CS with respect to the non-coherent CS and the individual spectra. This study demonstrates that the rotating unbalances of various components within agricultural machines, can be detected with a reduced number of accelerometers located in non-optimal positions, and that it is feasible to simplify the monitoring with CS. Overall, the coherent CS may be the best composite spectra formulation in order to monitor and detect rotating unbalances in agricultural machines. |
format | Online Article Text |
id | pubmed-7582267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75822672020-10-28 Application of Composite Spectrum in Agricultural Machines Feijoo, Fernando Gomez-Gil, Francisco Javier Gomez-Gil, Jaime Sensors (Basel) Article Composite spectrum (CS) is a data-fusion technique that reduces the number of spectra to be analyzed, simplifying the analysis process for machine monitoring and fault detection. In this work, vibration signals from five components of a combine harvester (thresher, chopper, straw walkers, sieve box, and engine) are obtained by placing four accelerometers along the combine-harvester chassis in non-optimal locations. Four individual spectra (one from each accelerometer) and three CS (non-coherent, coherent and poly-coherent spectra) from 18 cases are analyzed. The different cases result from the combination of three working conditions of the components—deactivated (off), balanced (healthy), and unbalanced (faulty)—and two speeds—idle and maximum revolutions per minute (RPM). The results showed that (i) the peaks can be identified in the four individual spectra that correspond to the rotational speeds of the five components in the analysis; (ii) the three formulations of the CS retain the relevant information from the individual spectra, thereby reducing the number of spectra required for monitoring and detecting rotating unbalances within a combine harvester; and, (iii) data noise reduction is observed in coherent and poly-coherent CS with respect to the non-coherent CS and the individual spectra. This study demonstrates that the rotating unbalances of various components within agricultural machines, can be detected with a reduced number of accelerometers located in non-optimal positions, and that it is feasible to simplify the monitoring with CS. Overall, the coherent CS may be the best composite spectra formulation in order to monitor and detect rotating unbalances in agricultural machines. MDPI 2020-09-26 /pmc/articles/PMC7582267/ /pubmed/32993176 http://dx.doi.org/10.3390/s20195519 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Feijoo, Fernando Gomez-Gil, Francisco Javier Gomez-Gil, Jaime Application of Composite Spectrum in Agricultural Machines |
title | Application of Composite Spectrum in Agricultural Machines |
title_full | Application of Composite Spectrum in Agricultural Machines |
title_fullStr | Application of Composite Spectrum in Agricultural Machines |
title_full_unstemmed | Application of Composite Spectrum in Agricultural Machines |
title_short | Application of Composite Spectrum in Agricultural Machines |
title_sort | application of composite spectrum in agricultural machines |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582267/ https://www.ncbi.nlm.nih.gov/pubmed/32993176 http://dx.doi.org/10.3390/s20195519 |
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