Title :
Study on the Transformer Solid Insulation Aging Diagnosis Method
Author :
Mu Xueyun ; Yang Qiping ; Wang Jun ; Xu Danfeng
Author_Institution :
Sch. of Electr. Power & Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
Abstract :
This paper state that several different methods of oil transformer solid insulation aging are described and the dissolved gas in oil contents (including CO, CO2 and furfural) are analyzed. The appreciation of ANN in transformers diagnosis solid insulation aging is introduced. The feasibility and effectiveness of ANN for transformer insulation aging diagnosis are explained by some examples.
Keywords :
ageing; neural nets; power engineering computing; transformer insulation; artificial neural nets; dissolved gas; oil contents; transformer solid insulation aging diagnosis; Aging; Dielectrics and electrical insulation; Gas insulation; Oil insulation; Petroleum; Plastic insulation; Polymers; Power transformer insulation; Power transformers; Solids;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
DOI :
10.1109/APPEEC.2010.5449352
