基于随机森林算法的智能电表故障诊断及寿命预测模型设计  

Fault Diagnosis and Life Prediction Model Design for Smart Electricity Meter Based on Random Forest Algorithn

作　　者：车玲[1] 黄勇华 姜林林 车恩羽 CHE Ling;HUANG Yong-hua;JIANG Lin-lin;CHE En-yu(School of Electronic Engineering and Information Technology,Nantong Vocational University,Nantong 226007,China;School of Computer and Information Science,Southwest University,Chongqing 400715,China)

机构地区：[1]南通职业大学电子信息工程学院,江苏南通226007 [2]西南大学计算机与信息科学学院,重庆400715

出　　处：《南通职业大学学报》2023年第4期86-90,共5页Journal of Nantong Vocational University

基　　金：2022年南通市职业技术教育学会教育研究课题(NTZJXH007);2019年南通职业大学校级项目(19KZ11)。

摘　　要：为及时发现并处理智能电表故障,延长其使用寿命,依据某地级市用电大数据进行数据挖掘和分析,基于随机森林(Random Forest,RF)算法建立智能电表故障诊断及寿命预测模型,并与其他模型进行实验比较。结果表明,构建的预测模型能实现智能电表的故障诊断与使用寿命预测,且有效性和准确性优于其他模型,具有工程应用价值。To identify the fault occurring in smart electricity meters and deal with it timely,data mining and analysis are carried out according to the big data of electricity consumption of the prefecture-level city,and a fault diagnosis and life prediction model is established using Random Forest(RF) algorithm.Comparative experiments are conducted with other models.The results show that the developed prediction model can be used to diagnose the fault and predict the service life of smart electricity meters,and its effectiveness and accuracy are better than other models.It is of application value in engineering.

关 键 词：智能电表 随机森林算法 故障诊断 寿命预测 

分 类 号：TM933.4[电气工程—电力电子与电力传动]