•  
  •  
 

Keywords

stage failure rate, cumulative failure rate, batch life prediction, fault data analysis

Abstract

The traditional method is based on Weibull distribution fitting, which does not consider the difference of different circuit modules in the smart meter affected by different external stress, and lacks the influence of different stress factors on the life of the smart meter. So, an intelligent meter life prediction method based on adaptive weighting coefficient is proposed in the paper, which realizes an improvement of the whole meter prediction algorithm . This method starts from the historical data of product failure, finds out the relationship between the stress and the historical original failure rate, and obtains the stress adjustment coefficient K and the weighting coefficient R based on the historical original failure rate respectively. The stress adjustment coefficient K and the weighting coefficient R is utilized to modify the obtained predicted failure rate and achieve higher accuracy. The case study shows that this method can reduce the miscalculation rate of remaining life of batch electric energy meters, In the actual application process, the proposed method can provide the useful information for purchasing electric energy meters in advance for batch rotation, and avoid largescale failure of electric energy meters.

DOI

10.19781/j.issn.16739140.2020.03.013

First Page

99

Last Page

106

Download

Share

COinS