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On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance

Connections are critical elements in power systems, exhibiting higher failure probability. Power connectors are considered secondary simple devices in power systems despite their key role, since a failure in one such element can lead to major issues. Thus, it is of vital interest to develop predicti...

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Detalles Bibliográficos
Autores principales: Riba, Jordi-Roger, Gómez-Pau, Álvaro, Martínez, Jimmy, Moreno-Eguilaz, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198314/
https://www.ncbi.nlm.nih.gov/pubmed/34072163
http://dx.doi.org/10.3390/s21113739
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author Riba, Jordi-Roger
Gómez-Pau, Álvaro
Martínez, Jimmy
Moreno-Eguilaz, Manuel
author_facet Riba, Jordi-Roger
Gómez-Pau, Álvaro
Martínez, Jimmy
Moreno-Eguilaz, Manuel
author_sort Riba, Jordi-Roger
collection PubMed
description Connections are critical elements in power systems, exhibiting higher failure probability. Power connectors are considered secondary simple devices in power systems despite their key role, since a failure in one such element can lead to major issues. Thus, it is of vital interest to develop predictive maintenance approaches to minimize these issues. This paper proposes an on-line method to determine the remaining useful life (RUL) of power connectors. It is based on a simple and accurate model of the degradation with time of the electrical resistance of the connector, which only has two parameters, whose values are identified from on-line acquired data (voltage drop across the connector, electric current and temperature). The accuracy of the model presented in this paper is compared with the widely applied autoregressive integrated moving average model (ARIMA), showing enhanced performance. Next, a criterion to determine the RUL is proposed, which is based on the inflection point of the expression describing the electrical resistance degradation. This strategy allows determination of when the connector must be replaced, thus easing predictive maintenance tasks. Experimental results from seven connectors show the potential and viability of the suggested method, which can be applied to many other devices.
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spelling pubmed-81983142021-06-14 On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance Riba, Jordi-Roger Gómez-Pau, Álvaro Martínez, Jimmy Moreno-Eguilaz, Manuel Sensors (Basel) Article Connections are critical elements in power systems, exhibiting higher failure probability. Power connectors are considered secondary simple devices in power systems despite their key role, since a failure in one such element can lead to major issues. Thus, it is of vital interest to develop predictive maintenance approaches to minimize these issues. This paper proposes an on-line method to determine the remaining useful life (RUL) of power connectors. It is based on a simple and accurate model of the degradation with time of the electrical resistance of the connector, which only has two parameters, whose values are identified from on-line acquired data (voltage drop across the connector, electric current and temperature). The accuracy of the model presented in this paper is compared with the widely applied autoregressive integrated moving average model (ARIMA), showing enhanced performance. Next, a criterion to determine the RUL is proposed, which is based on the inflection point of the expression describing the electrical resistance degradation. This strategy allows determination of when the connector must be replaced, thus easing predictive maintenance tasks. Experimental results from seven connectors show the potential and viability of the suggested method, which can be applied to many other devices. MDPI 2021-05-27 /pmc/articles/PMC8198314/ /pubmed/34072163 http://dx.doi.org/10.3390/s21113739 Text en © 2021 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
Riba, Jordi-Roger
Gómez-Pau, Álvaro
Martínez, Jimmy
Moreno-Eguilaz, Manuel
On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
title On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
title_full On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
title_fullStr On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
title_full_unstemmed On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
title_short On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
title_sort on-line remaining useful life estimation of power connectors focused on predictive maintenance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8198314/
https://www.ncbi.nlm.nih.gov/pubmed/34072163
http://dx.doi.org/10.3390/s21113739
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