A Hybrid Support Vector Fuzzy Inference System for the Classification of Leakage Current Waveforms Portraying Discharges

被引:6
作者
Theofilatos, Konstantinos [1 ]
Pylarinos, Dionisios [2 ]
Likothanassis, Spiros [1 ]
Melidis, Damianos [1 ]
Siderakis, Kiriakos [3 ]
Thalassinakis, Emmanuel [4 ]
Mavroudi, Seferina [5 ]
机构
[1] Univ Patras, Dept Comp Engn & Informat, Pattern Recognit Lab, GR-26110 Patras, Greece
[2] PPC HEDNO, Iraklion, Greece
[3] Technol Educ Inst Crete, Sch Appl Technol, Elect Engn Dept, Iraklion, Greece
[4] Publ Power Corp HEDNO, Iraklion, Greece
[5] Technol Educ Inst Patras, Sch Sci Hlth & Care, Dept Social Work, Patras, Greece
关键词
leakage current; insulators; field; discharges; feature selection; classification; fuzzy logic; genetic algorithms; support vector machines; SILICONE-RUBBER; FREQUENCY-CHARACTERISTICS; FLASHOVER PROCESS; INSULATORS; VOLTAGE; PERFORMANCE; RTV;
D O I
10.1080/15325008.2013.853217
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Several techniques have been applied on leakage current waveforms in order to extract information regarding electrical activity on high-voltage insulators. However, a fully representative value is yet to be defined. In this article, a hybrid support vector fuzzy inference system is introduced as a classification tool. The system incorporates fuzzy logic, genetic algorithms, and support vector machines. Apart from the classification accuracy achieved, the system also produces a set of fuzzy rules under which the classification is made, allowing a further insight of the process. A comparison is made to other classification tools previously applied on the same data set.
引用
收藏
页码:180 / 189
页数:10
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