Zhang Zhonghao, Liu Haiying, Peng Guozheng, L. Jiaxin, Li Sun
{"title":"基于太赫兹波聚类分析的隧道电缆绝缘层监测研究","authors":"Zhang Zhonghao, Liu Haiying, Peng Guozheng, L. Jiaxin, Li Sun","doi":"10.1109/AEEES51875.2021.9403200","DOIUrl":null,"url":null,"abstract":"Internal defect of cable is seriously endangering the operation of power grid. To detect the defect in time, a THz(terahertz) detection method combined with clustering algorithm was proposed in this paper. To extract feature from the original waves, frequency domain features and PCA were obtained. Further, the correlation of a feature in different sample sets was analyzed through Mann-Whitney U test. According to effect of clustering, features filtered by Mann-Whitney U test show good classification performance. Based on the clustering method of terahertz wave, the inner defective and normal conditions of cable insulation can be classified quickly and accurately.","PeriodicalId":356667,"journal":{"name":"2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Monitoring of Tunnel Cable Insulation Layer Based on Terahertz Wave Clustering Analysis\",\"authors\":\"Zhang Zhonghao, Liu Haiying, Peng Guozheng, L. Jiaxin, Li Sun\",\"doi\":\"10.1109/AEEES51875.2021.9403200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Internal defect of cable is seriously endangering the operation of power grid. To detect the defect in time, a THz(terahertz) detection method combined with clustering algorithm was proposed in this paper. To extract feature from the original waves, frequency domain features and PCA were obtained. Further, the correlation of a feature in different sample sets was analyzed through Mann-Whitney U test. According to effect of clustering, features filtered by Mann-Whitney U test show good classification performance. Based on the clustering method of terahertz wave, the inner defective and normal conditions of cable insulation can be classified quickly and accurately.\",\"PeriodicalId\":356667,\"journal\":{\"name\":\"2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AEEES51875.2021.9403200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEEES51875.2021.9403200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Monitoring of Tunnel Cable Insulation Layer Based on Terahertz Wave Clustering Analysis
Internal defect of cable is seriously endangering the operation of power grid. To detect the defect in time, a THz(terahertz) detection method combined with clustering algorithm was proposed in this paper. To extract feature from the original waves, frequency domain features and PCA were obtained. Further, the correlation of a feature in different sample sets was analyzed through Mann-Whitney U test. According to effect of clustering, features filtered by Mann-Whitney U test show good classification performance. Based on the clustering method of terahertz wave, the inner defective and normal conditions of cable insulation can be classified quickly and accurately.