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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...

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Detalles Bibliográficos
Autores principales: Dong, Xianguang, Jing, Zhen, Dai, Yanjie, Wang, Pingxin, Chen, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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
Descripción
Sumario: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.