Title :
Development of remaining life assessment for oil-immersed transformer using structured neural networks
Author :
Matsui, Tetsuro ; Nakahara, Yasuo ; Nishiyama, Kazuo ; Urabe, Noboru ; Itoh, Masayoshi
Author_Institution :
Fuji Electr. Adv. Technol., Tokyo, Japan
Abstract :
Remaining Life of the oil-immersed transformer is decided due to deterioration of the winding insulation paper. The furfural method is conventionally used to estimate the remaining life. However, the results are obtained as wide ranges between upper and lower limits. Therefore, a more accurate estimation method has been expected. This paper proposes the remaining life assessment for oil-immersed transformer using structured neural networks and ensemble technique. The authors have estimated the remaining life using proposed method for 300 transformers or more. As a result, appropriate replacement time of transformer and appropriate maintenance scenario can be planned.
Keywords :
maintenance engineering; neural nets; power engineering computing; power transformer insulation; remaining life assessment; transformer oil; transformer windings; ensemble technique; oil-immersed transformer; remaining life assessment; structured neural network; transformer maintenance; transformer replacement; winding insulation paper deterioration; Cable insulation; Dielectrics and electrical insulation; Iron; Life estimation; Neural networks; Oil insulation; Petroleum; Power transformer insulation; Remaining life assessment; Wire; artificial neural network; average degree of polymerization; ensemble; furfural; oil-immersed transformer; remaining life assessment;
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3
