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A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition
Timely and accurate identification of fault types at the early stage of minor faults is significant for cutting off fault evolution. In order to have a clear understanding of the pipeline robot’s own situation in the pipeline, this paper proposes a fault diagnosis system for pipeline robots based on...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104926/ https://www.ncbi.nlm.nih.gov/pubmed/35590965 http://dx.doi.org/10.3390/s22093275 |
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author | Cao, Hai Yu, Jinpeng Wang, Yu Zhang, Liang Kim, Jongwon |
author_facet | Cao, Hai Yu, Jinpeng Wang, Yu Zhang, Liang Kim, Jongwon |
author_sort | Cao, Hai |
collection | PubMed |
description | Timely and accurate identification of fault types at the early stage of minor faults is significant for cutting off fault evolution. In order to have a clear understanding of the pipeline robot’s own situation in the pipeline, this paper proposes a fault diagnosis system for pipeline robots based on sound signal recognition. This can effectively reduce the probability of serious faults such as shutdown and loss of control in the pipeline without affecting the safe operation of the pipeline robot, which is a key issue to improve the reliability of the pipeline robot. The system consists of a combination of three parts: hardware, software, and algorithm. On the one hand, Raspberry Pi is the core module, while on the other hand, it is also responsible for the data transmission between the various modules, including storing the original sound signals collected by the sensors and transmitting the diagnosis results to the upper computer software interface. The proposed system is validated on the dataset collected by the data experimentation platform. The experimental results show that the proposed fault prediction method obtains advanced results on this dataset, verifying the effectiveness and stability of the proposed fault diagnosis system for pipeline robots based on sound signal recognition. |
format | Online Article Text |
id | pubmed-9104926 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91049262022-05-14 A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition Cao, Hai Yu, Jinpeng Wang, Yu Zhang, Liang Kim, Jongwon Sensors (Basel) Article Timely and accurate identification of fault types at the early stage of minor faults is significant for cutting off fault evolution. In order to have a clear understanding of the pipeline robot’s own situation in the pipeline, this paper proposes a fault diagnosis system for pipeline robots based on sound signal recognition. This can effectively reduce the probability of serious faults such as shutdown and loss of control in the pipeline without affecting the safe operation of the pipeline robot, which is a key issue to improve the reliability of the pipeline robot. The system consists of a combination of three parts: hardware, software, and algorithm. On the one hand, Raspberry Pi is the core module, while on the other hand, it is also responsible for the data transmission between the various modules, including storing the original sound signals collected by the sensors and transmitting the diagnosis results to the upper computer software interface. The proposed system is validated on the dataset collected by the data experimentation platform. The experimental results show that the proposed fault prediction method obtains advanced results on this dataset, verifying the effectiveness and stability of the proposed fault diagnosis system for pipeline robots based on sound signal recognition. MDPI 2022-04-24 /pmc/articles/PMC9104926/ /pubmed/35590965 http://dx.doi.org/10.3390/s22093275 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 Cao, Hai Yu, Jinpeng Wang, Yu Zhang, Liang Kim, Jongwon A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition |
title | A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition |
title_full | A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition |
title_fullStr | A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition |
title_full_unstemmed | A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition |
title_short | A Fault Diagnosis System for a Pipeline Robot Based on Sound Signal Recognition |
title_sort | fault diagnosis system for a pipeline robot based on sound signal recognition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104926/ https://www.ncbi.nlm.nih.gov/pubmed/35590965 http://dx.doi.org/10.3390/s22093275 |
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