A neural network based method for the diagnosis of ageing insulators

Author

Bashir, N. ; Ahmad, H.

Author_Institution

Fac. of Electr. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia

Volume

1

fYear

2009

fDate

4-6 Oct. 2009

Firstpage

41

Lastpage

46

Abstract

This work attempts to apply an artificial neural network in order to diagnose ageing transmission line insulators. The insulator leakage current harmonic components are used as the input variables of the artificial neural network. The data used to train the network and test its performance is derived from experimental measurements carried out in artificial climatic chamber. The experimental result and neural network simulation results are presented accordingly. This novel method of ANN application can be viable in online diagnosis of insulators in service and lifespan estimation yielding efficient and effective predictive maintenance practices for power utilities in a cheap and less time-consuming manner.

Keywords

ageing; ceramic insulators; insulator contamination; leakage currents; maintenance engineering; neural nets; power engineering computing; ANN application; ageing insulators; artificial climatic chamber; artificial neural network; insulator leakage current harmonic components; lifespan estimation; online diagnosis; power utilities; predictive maintenance; transmission line insulators; Aging; Artificial neural networks; Input variables; Insulation; Leakage current; Life estimation; Neural networks; Power transmission lines; Testing; Transmission line measurements; Artificial Neural Network; ageing; ceramic insulator; harmonics;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics & Applications, 2009. ISIEA 2009. IEEE Symposium on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-4681-0

Electronic_ISBN

978-1-4244-4683-4

Type

conf

DOI

10.1109/ISIEA.2009.5356499

Filename

5356499