王科,项恩新,曹伟东,徐肖伟,黄继盛,车雨轩.基于图像特征和深度森林的乙丙橡胶电缆绝缘老化状态识别[J].电测与仪表,2022,59(6):32-36. Wang Ke,Xiang Enxin,Cao Weidong,Xu Xiaowei,Huang Jisheng,Che Yuxuan.IIdentification of aging state of EPR cable insulation based on image feature and deep forest[J].Electrical Measurement & Instrumentation,2022,59(6):32-36.
基于图像特征和深度森林的乙丙橡胶电缆绝缘老化状态识别
IIdentification of aging state of EPR cable insulation based on image feature and deep forest
In order to identify the aging state of EPR cable insulation more accurately, a recognition method based on partial discharge image features and the deep forest is proposed. In this paper, EPR samples with different aging states are prepared, and a PD test platform is built. The PD spectra of EPR samples with different aging states are obtained through the test, and 19 characteristic parameters are extracted from the PD spectra. The samples with different aging degrees are identified by combining the deep forest network. The results show that, by combining the PD spectra characteristics Token and deep forest network can accurately identify the aging state of cable, and the recognition rate is better than other traditional classification algorithms. The combination of PD image features and the deep forest has a good engineering application prospect in cable insulation aging diagnosis.
