Title :
Diagnosis of oil-insulated power apparatus by using neural network simulation
Author :
Vanegas, O. ; Mizuno, Y. ; Naito, K. ; Kamiya, T.
Author_Institution :
Nagoya Inst. of Technol., Japan
fDate :
6/1/1997 12:00:00 AM
Abstract :
One diagnostic process for oil-insulated power apparatus is based on the analysis of the chemical composition of gases evolved by the insulating oil. Normally this can be done only by a human expert. A considerable amount of information on the relation between chemical components and the faulty part of the power apparatus has been accumulated. This paper describes a neural network system which can be applied to existing diagnostic methods to enable analysis even by inexperienced engineers
Keywords :
chemical analysis; insulating oils; insulation testing; neural nets; power apparatus; power engineering computing; power transformer insulation; power transformer testing; chemical composition; diagnostic process; evolved gases; neural network simulation; oil chemical analysis; oil-insulated power apparatus; Chemical analysis; Chemical elements; Chemical processes; Chemical technology; Dielectrics and electrical insulation; Gas insulation; Gases; Neural networks; Oil insulation; Petroleum;
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
