张家琦,郭帅,李国昌,陈颖,宋玮琼,关慧哲.基于多元大数据融合的智能电能表可靠性评估模型[J].电测与仪表,2023,60(1):167-173. Zhang Jiaqi,Guo Shuai,Li Guochang,Chen Ying,Song Weiqiong,Guan Huizhe.Reliability estimation model for smart meters based on multi-source big data fusion[J].Electrical Measurement & Instrumentation,2023,60(1):167-173.
基于多元大数据融合的智能电能表可靠性评估模型
Reliability estimation model for smart meters based on multi-source big data fusion
Smart meters are the basic unit of the power metering system and are widely deployed on the user side. Aiming at the problem of the difficulty of maintenance due to their large amount, a smart meter reliability estimation model based on multi-source big data fusion is proposed. In order to fully explore the useful information in the design, maintenance and operation data of the meter, the multi-source big data was merged and collatedto obtain the covariate data and the smart meter survival label that affect the smart meter’s life span. Based on the survival analysis theory, a cox proportional-hazards(CoxPH) model for the life cycle of a smart meter is established, and a deep neural network is used to characterize strongly non-linear correlation parameters to form a reliability estimation model for the smart meter. Based on the actual operation and maintenance data of smart meters of some city, the effectiveness of the proposed model was verified. Test results show that the proposed model, which provides subsidiarity for smart meter maintenance, can extimate reliability of the smart meter sucessfully based onits real-time running status.
