张建文,王曼,解浩,严家明,张寰宇.基于随机森林的油纸绝缘老化阶段评估[J].电测与仪表,2018,55(9):121-125. Zhang Jianwen,Wang Man,Xie Hao,Yan Jiaming,Zhang Huanyu.Aging Stage Evaluation of Oil - paper Insulation Based on Random Forest[J].Electrical Measurement & Instrumentation,2018,55(9):121-125.
基于随机森林的油纸绝缘老化阶段评估
Aging Stage Evaluation of Oil - paper Insulation Based on Random Forest
This paper proposes the diagnostic method which is based on EMD-SVD feature extraction and random forest classifier in order to more accurately assess the transformer oil paper insulation aging stage. The paper Set up the experimental platform to collect air gap defect samples of different thermal aging stages partial discharge signals and obtained partial discharge signal characteristics after denoising processing and EMD-SVD feature extraction. The EMD-SVD feature are diagnosed by random forest classifier with the traditional BP neural network classifier and support vector machine respectively, and the results show that random forest classifier recognition result is superior to the traditional classifier. Compared with the traditional classifier, random forest classifier classification ability is better for EMD-SVD characteristics classification. The paper demonstrates that the EMD-SVD features combined with random forest classifier applied in oil paper insulation thermal aging phase recognition effect is better.
