DocumentCode :
3611527
Title :
Monitoring and identification of metal–oxide surge arrester conditions using multi-layer support vector machine
Author :
Khodsuz, Masume ; Mirzaie, Mohammad
Author_Institution :
Dept. of Electr. & Comput. Eng., Babol Univ. of Technol., Babol, Iran
Volume :
9
Issue :
16
fYear :
2015
Firstpage :
2501
Lastpage :
2508
Abstract :
Metal-oxide surge arresters (MOSAs) are essential equipments for power system protection and devices from lightning and switching transient overvoltages. Therefore, their operating condition and diagnosis are very important. In this study, a multi-layer support vector machine (SVM) classifier has been used for MOSA conditions monitoring based on experimental tests. Three features are extracted based on the test results for determining surge arresters operating conditions including clean virgin, ultraviolet (UV) aged clean surface, surface contaminations after and before UV housing ageing, and degraded varistors along active column. Then, the multi-layer SVM classifier is trained with the training samples, which are extracted by the above data processing. Finally, the five fault types of surge arresters are identified by this classifier. The test results show that the classifier has an excellent performance on training speed and reliability which confirm the high applicability of introduced features for correct diagnostic of surge arresters conditions.
Keywords :
arresters; condition monitoring; fault diagnosis; lightning protection; overvoltage protection; pattern classification; power engineering computing; power system protection; support vector machines; surface contamination; switching transients; varistors; MOSA conditions monitoring; UV housing ageing; fault type identification; lightning overvoltage; metal oxide surge arrester; multilayer SVM classifier; multilayer support vector machine; operating condition; power system devices; power system protection; reliability; surface contamination; switching transient overvoltage; ultraviolet aged clean surface; varistors;
fLanguage :
English
Journal_Title :
Generation, Transmission Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd.2015.0640
Filename :
7337589
Link To Document :
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