Diagnosis of oil-insulated power apparatus by using neural network simulation

Autor: Katsuhiko Naito, T. Kamiya, O. Vanegas, Yukio Mizuno
Rok vydání: 1997
Předmět:
Zdroj: IEEE Transactions on Dielectrics and Electrical Insulation. 4:290-299
ISSN: 1070-9878
Popis: 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.
Databáze: OpenAIRE