电测与仪表2024，Vol.61Issue(7)：197-203,7.DOI:10.19753/j.issn1001-1390.2024.07.028
基于voting集成的智能电能表故障多分类方法
Multi-classification method of smart electricity meter fault based on voting integration
摘要
Abstract
In order to improve the ability to accurately classify faults of smart electricity meters and help maintain-ers to quickly troubleshoot faults,this paper proposes a multi-classification method for smart electricity meter faults based on voting integration.This paper performs coding preprocessing for the actual fault data of smart electricity meters,screens the key influencing factors of fault classification of smart electricity meters based on the Pearson co-efficient method,and combines the SMOTE algorithm to solve the problem of data category imbalance,thereby es-tablishing the data set required for the model,and then,voting method is used for model fusion,combined with particle swarm optimization(PSO)to determine the weight of each base model.On this basis,a multi-classification method of smart electricity meter fault based on the XGBT+KNN+NB model is constructed.The actual test results show that the method proposed in this paper can effectively realize the rapid and accurate classification of the faults of the smart electricity meter.Compared with the existing methods,the fault classification accuracy,the recall rate and the F1-Score of the smart electricity meter have been significantly improved.关键词
智能电能表/故障分类/voting集成/粒子群寻优/多分类Key words
smart electricity meter/fault classification/voting integration/particle swarm optimization/multiple classification分类
动力与电气工程引用本文复制引用
肖宇,黄瑞,刘谋海,刘小平,袁明,高云鹏..基于voting集成的智能电能表故障多分类方法[J].电测与仪表,2024,61(7):197-203,7.基金项目
国家电网有限公司科技项目(5216AG20000D) （5216AG20000D）
