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Therefore, in this paper, a scheme of complete protection for fast, and accurate classification and detection of a fault in HVDC transmission line using support vector machine (SVM) is presented. In the proposed scheme, ac and dc side voltage and current at each converter station are measured and treated as the input of SVM binary classifier. For classification of fault, SVM module with multi-classification feature is used. For the normalization purposes of the signals, the standard deviation is used over half cycle before and after the occurrence of the fault. Features have been extracted through wavelet transform of predefined function for detection and classification of a fault. The proposed scheme is easy to use as it requires only one end data and a standard deviation over one cycle data.<\/jats:p>","DOI":"10.3233\/jifs-169782","type":"journal-article","created":{"date-parts":[[2018,7,27]],"date-time":"2018-07-27T19:27:39Z","timestamp":1532719659000},"page":"4977-4986","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Fault detection, classification in multiterminal HVDC transmission system with MC-SVM"],"prefix":"10.1177","volume":"35","author":[{"given":"Jay Prakash","family":"Keshri","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, India"}]},{"given":"Harpal","family":"Tiwari","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, India"}]}],"member":"179","published-online":{"date-parts":[[2018,7,24]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2009.2033078"},{"key":"e_1_3_1_3_2","doi-asserted-by":"crossref","unstructured":"NanayakkaraK. 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