文献类型：期刊文献

英文题名：Transient thermal pattern separation and detection of conductive defects in composite insulators using eddy current pulsed thermography

作者：Tu, Yanxin[1];Mei, Hongwei[1];Liu, Lishuai[2];Shen, Zekai[1];Guo, Chenjun[1,3];Wang, Liming[1]

机构：[1]Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Engn Lab Power Equipment Reliabil Complicated Coa, Shenzhen 518055, Peoples R China;[2]East China Univ Sci & Technol, Sch Mech & Power Engn, Key Lab Pressure Syst & Safety MOE, Shanghai 200237, Peoples R China;[3]Elect Power Res Inst Yunnan Power Grid Co Ltd, Kunming 650214, Yunnan, Peoples R China

年份：2022

卷号：129

外文期刊名：NDT & E INTERNATIONAL

收录：;EI(收录号：20221712012207);WOS:【SCI-EXPANDED(收录号:WOS:000807742200001)】；

基金：Acknowledgements This work was supported by the National Natural Science Foundation of China under Grant 51977117 and 12104155.

语种：英文

外文关键词：Composite insulator; Conductive defects; Eddy current pulsed thermography; Transient thermal patterns

摘要：Composite insulators are prone to internal conductive defects owing to their long-term high-voltage operation and outdoor aging. In this study, a method based on eddy current pulsed thermography (ECPT) combined with feature extraction transform algorithms is proposed for transient thermal pattern separation and defect detection in composite insulators with internal conductive defects. The principles of this method, including electromagnetic heating, thermal diffusion, and transient thermal response extraction, are investigated. Conductive defects in insulators have unique thermal patterns that differ from those of non-conductive defects in conductive materials. In this study, the original transient thermal responses of conductive defects are analyzed and compared with those of non-conductive defects. The effectiveness of the transient thermal pattern separation of this method is verified through experimental studies. Different feature extraction transform methods are utilized and compared to separate different thermal transient patterns and perform quantitative evaluations. It is found that ECPT combined with feature extraction transform algorithms can provide a visual and effective method to detect internal conductive defects in composite insulators.