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Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor
This study presents a condition diagnosis system based on a ferrous particle sensor to estimate the durability of axles in construction equipment. Axles are mechanical devices that play the role of the differential gear in construction equipment that move with wheels and require high reliability. In...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962140/ https://www.ncbi.nlm.nih.gov/pubmed/36837053 http://dx.doi.org/10.3390/ma16041426 |
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author | Hong, Sung-Ho Jeon, Hong-Gyu |
author_facet | Hong, Sung-Ho Jeon, Hong-Gyu |
author_sort | Hong, Sung-Ho |
collection | PubMed |
description | This study presents a condition diagnosis system based on a ferrous particle sensor to estimate the durability of axles in construction equipment. Axles are mechanical devices that play the role of the differential gear in construction equipment that move with wheels and require high reliability. In the durability testing of new axles, failure identification and real-time diagnosis are required. One of the typical failure modes of an axle is increased ferrous-wear particles due to metal-to-metal contact. Therefore, a condition diagnostic program based on the ferrous particle sensor is developed and applied in the bench tests of axles. This program provides information on the amount of wear with respect to ferrous particles using a simple diagnostic algorithm. Additionally, it allows separation and storage of measured data that exceed the reference values; the system provides warnings using color, sound, and pop-up windows to facilitate diagnosis. In the two tests, the first case detected a failure, but in the other case, the sensor did not detect it even though a failure occurred. From the results of bench tests, it is confirmed that the sensor location is a critical factor. Therefore, a multi-physics-based analysis method is suggested for positioning the ferrous particle sensor. |
format | Online Article Text |
id | pubmed-9962140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99621402023-02-26 Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor Hong, Sung-Ho Jeon, Hong-Gyu Materials (Basel) Article This study presents a condition diagnosis system based on a ferrous particle sensor to estimate the durability of axles in construction equipment. Axles are mechanical devices that play the role of the differential gear in construction equipment that move with wheels and require high reliability. In the durability testing of new axles, failure identification and real-time diagnosis are required. One of the typical failure modes of an axle is increased ferrous-wear particles due to metal-to-metal contact. Therefore, a condition diagnostic program based on the ferrous particle sensor is developed and applied in the bench tests of axles. This program provides information on the amount of wear with respect to ferrous particles using a simple diagnostic algorithm. Additionally, it allows separation and storage of measured data that exceed the reference values; the system provides warnings using color, sound, and pop-up windows to facilitate diagnosis. In the two tests, the first case detected a failure, but in the other case, the sensor did not detect it even though a failure occurred. From the results of bench tests, it is confirmed that the sensor location is a critical factor. Therefore, a multi-physics-based analysis method is suggested for positioning the ferrous particle sensor. MDPI 2023-02-08 /pmc/articles/PMC9962140/ /pubmed/36837053 http://dx.doi.org/10.3390/ma16041426 Text en © 2023 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 Hong, Sung-Ho Jeon, Hong-Gyu Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor |
title | Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor |
title_full | Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor |
title_fullStr | Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor |
title_full_unstemmed | Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor |
title_short | Assessment of Condition Diagnosis System for Axles with Ferrous Particle Sensor |
title_sort | assessment of condition diagnosis system for axles with ferrous particle sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962140/ https://www.ncbi.nlm.nih.gov/pubmed/36837053 http://dx.doi.org/10.3390/ma16041426 |
work_keys_str_mv | AT hongsungho assessmentofconditiondiagnosissystemforaxleswithferrousparticlesensor AT jeonhonggyu assessmentofconditiondiagnosissystemforaxleswithferrousparticlesensor |