Cart (Loading....) | Create Account
Close category search window
 

A novel approach to the classification of the transient phenomena in power transformers using combined wavelet transform and neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Mao, P.L. ; Dept. of Electron. & Electr. Eng., Bath Univ., UK ; Aggarwal, R.K.

The wavelet transform is a powerful tool in the analysis of the power transformer transient phenomena because of its ability to extract information from the transient signals simultaneously in both the time and frequency domain. This paper presents a novel technique for accurate discrimination between an internal fault and a magnetizing inrush current in the power transformer by combining wavelet transforms with neural networks. The wavelet transform is firstly applied to decompose the differential current signals of the power transformer into a series of detailed wavelet components. The spectral energies of the wavelet components are calculated and then employed to train a neural network to discriminate an internal fault from the magnetizing inrush current. The simulated results presented clearly show that the proposed technique can accurately discriminate between an internal fault and a magnetizing inrush current in power transformer protection

Published in:

Power Delivery, IEEE Transactions on  (Volume:16 ,  Issue: 4 )

Date of Publication:

Oct 2001

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.