Modelling of Partial Discharge Inception and Extinction Voltages Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Author

Kolev, N.P. ; Chalashkanov, N.M.

Author_Institution

Tech. Univ. of Sofia, Sofia

fYear

2007

fDate

8-13 July 2007

Firstpage

605

Lastpage

608

Abstract

In this paper is presented an adaptive neuro- fuzzy inference system (ANFIS) that is used for modeling of partial discharge inception and extinction voltages. The ANFIS structure is automatically generated and tuned in order to fit the available measurement data. As inputs of the adaptive neural network are used dielectric thickness, void depth and void diameter. The voids in the solid insulating materials are artificially created. Finally, estimation of the model error is given.

Keywords

electrical engineering computing; fuzzy neural nets; insulating materials; partial discharges; voids (solid); adaptive neural network; adaptive neuro-fuzzy inference system; dielectric thickness; extinction voltages; partial discharge inception; solid insulating materials; void depth; void diameter; Adaptive systems; Artificial neural networks; Dielectric materials; Dielectric measurements; Dielectrics and electrical insulation; Fuzzy systems; Partial discharge measurement; Partial discharges; Solids; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Solid Dielectrics, 2007. ICSD '07. IEEE International Conference on

Conference_Location

Winchester

Print_ISBN

1-4244-0750-8

Electronic_ISBN

1-4244-0751-6

Type

conf

DOI

10.1109/ICSD.2007.4290886

Filename

4290886