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- W4362504581 abstract "In order to solve the problems of poor measurement stability and failure time of smart electricity meter in the process of life reliability analysis, this paper based on the least square method of regression analysis to estimate the parameters of Weibull distribution and accelerated life test model. The reliability index of smart electricity meter predicted by the new Weibull parameter estimation method is similar to that predicted by the point estimation method, but the reliability error of smart electricity meter predicted by the component stress method is large, indicating that there is an error between the actual operation of smart electricity meter and the predicted results in the design stage. The method proposed in this paper predicts the reliability of smart electricity meters under actual operation conditions, and predicts the correction factors of smart electricity meters' failure rate. The correction factors of various models are summarized to improve the reliability of smart electricity meters. In addition, the failure time before the smart meter is deduced and the failure rate of smart meter is more accurate." @default.
- W4362504581 created "2023-04-05" @default.
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- W4362504581 date "2022-01-01" @default.
- W4362504581 modified "2023-09-26" @default.
- W4362504581 title "Reliability prediction and evaluation model of smart electricity meter based on edge computing" @default.
- W4362504581 doi "https://doi.org/10.1049/icp.2022.2843" @default.
- W4362504581 hasPublicationYear "2022" @default.
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