DocumentCode :
2097581
Title :
Evaluation of electrical insulation using genetically evolved artificial neural nets
Author :
Wahidabanu, R.S.D. ; Selvam, M. A Panneer ; Udayakumar, K.
Author_Institution :
Anna Univ., Madras, India
fYear :
1997
fDate :
22-25 Sep 1997
Firstpage :
279
Lastpage :
282
Abstract :
The degree of electrical insulation degradation depends strongly on the insulation´s defects. Different types of insulation defects generate different partial discharge (PD) patterns. The correlation that exists between a defect and its pattern is identified and recognized by popular artificial neural nets (ANN) as they significantly improve the recognition of complex patterns in noisy data. An evolutionary design concept is used to realize such an ANN, to avoid the problem of stagnation, and satisfactory results are obtained
Keywords :
automatic test software; data acquisition; electric breakdown; insulation testing; neural nets; partial discharges; pattern recognition; breakdown testing; complex pattern recognition; electrical insulation; evolutionary design concept; genetically-evolved artificial neural nets; insulation defects; noisy data; partial discharge; testing automation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Insulation Conference, 1997, and Electrical Manufacturing & Coil Winding Conference. Proceedings
Conference_Location :
Rosemont, IL
ISSN :
0362-2479
Print_ISBN :
0-7803-3959-2
Type :
conf
DOI :
10.1109/EEIC.1997.651095
Filename :
651095
Link To Document :
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