Design of Diagnosis System for Insulation Degradation by Using Neurofuzzy Model
Yigon Kim, Yang Hee Jung and Yong Chul Bae
Department of Electrical and Semiconductor Engineering, Yosu National. University, Korea
Insulation aging diagnosis provides early warning of electrical equipment defects that helps avoid loss from unexpected production line shutdown. Since relations of insulation aging and partial discharge dynamics are nonlinear, it is very difficult to provide early warning in electrical equipment. This paper suggests a new method for diagnosing insulation aging that measures partial discharge on-line from DAS(Data Acquisition System) and acquires 2D patterns from analyzing it using wavelets. Using this data, design of a neurofuzzy model that diagnoses electrical equipment is investigated. Validity of the new method is confirmed by numerical simulation.
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