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- W4311494354 abstract "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." @default.
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- W4311494354 date "2022-12-14" @default.
- W4311494354 modified "2023-09-26" @default.
- W4311494354 title "Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation" @default.
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- W4311494354 doi "https://doi.org/10.3390/s22249804" @default.
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