A novel technique to discriminate inrush and fault in a single-phase transformer
by S.R. Paraskar, M.A. Beg, G.M. Dhole, M.K. Khedkar
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 3, No. 1, 2010

Abstract: This paper presents an algorithm based on a combination of Discrete Wavelet Transforms (DWTs) and Feed-Forward Artificial Neural Network (FFANN) to discriminate magnetising inrush from interturn fault. Interturn faults are staged on custom-built transformer. DWT is used for feature extraction from the differential current during magnetising inrush and interturn faults and FFANN is used to discriminate magnetising inrush from interturn fault. An online algorithm is tested successfully on the custom-built transformer. It is found that the proposed method gives satisfactory results, and may be useful in the development of modern differential relay for transformer protection scheme.

Online publication date: Fri, 13-Aug-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Signal and Imaging Systems Engineering (IJSISE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com