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Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation †
It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull distribution...
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/PMC9788098/ https://www.ncbi.nlm.nih.gov/pubmed/36560173 http://dx.doi.org/10.3390/s22249804 |
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author | Dong, Xianguang Jing, Zhen Dai, Yanjie Wang, Pingxin Chen, Zhen |
author_facet | Dong, Xianguang Jing, Zhen Dai, Yanjie Wang, Pingxin Chen, Zhen |
author_sort | Dong, Xianguang |
collection | PubMed |
description | It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull distribution with odds ratios, then the distribution parameters, failure prediction number, and confidence intervals of prediction number were calculated. A strategy of meter replacement and reserve were developed according to the prediction results. To avoid the uncertainty of prediction results due to the small amount of field data information, a Bayesian failure number prediction method was developed. The research results have value for making operation plans and reserve strategies for electricity meters. |
format | Online Article Text |
id | pubmed-9788098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97880982022-12-24 Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † Dong, Xianguang Jing, Zhen Dai, Yanjie Wang, Pingxin Chen, Zhen Sensors (Basel) Article It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull distribution with odds ratios, then the distribution parameters, failure prediction number, and confidence intervals of prediction number were calculated. A strategy of meter replacement and reserve were developed according to the prediction results. To avoid the uncertainty of prediction results due to the small amount of field data information, a Bayesian failure number prediction method was developed. The research results have value for making operation plans and reserve strategies for electricity meters. MDPI 2022-12-14 /pmc/articles/PMC9788098/ /pubmed/36560173 http://dx.doi.org/10.3390/s22249804 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 Dong, Xianguang Jing, Zhen Dai, Yanjie Wang, Pingxin Chen, Zhen Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † |
title | Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † |
title_full | Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † |
title_fullStr | Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † |
title_full_unstemmed | Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † |
title_short | Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation † |
title_sort | failure prediction and replacement strategies for smart electricity meters based on field failure observation † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788098/ https://www.ncbi.nlm.nih.gov/pubmed/36560173 http://dx.doi.org/10.3390/s22249804 |
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