A wavelet-based fault localization in transmission network

Author

Verma, Sushma ; Konar, Pratyay ; Chattopadhyay, Paramita

Author_Institution

Techno India Coll. of Technol., Kolkata, India

fYear

2011

fDate

28-30 Dec. 2011

Firstpage

1

Lastpage

5

Abstract

The proposed technique consists of a pre-processing unit based on Continuous Wavelet Transform (CWT) in combination with an Artificial Neural Networks (ANN). CWT acts as an extractor of distinctive features in the transient current signals at the sending and receiving end of the transmission line. This information is then fed to the ANN for detecting the fault type and location of fault. The results presented clearly indicate that the present technique is very fast, computationally efficient and intelligent enough to accurately identify three different types of fault (LG & LLG) and their locations.

Keywords

neural nets; power engineering computing; power transmission faults; power transmission lines; wavelet transforms; ANN; CWT; artificial neural networks; continuous wavelet transform; preprocessing unit; transient current signals; transmission line; transmission network; wavelet-based fault localization; Artificial neural networks; Continuous wavelet transforms; Educational institutions; Transient analysis; Wavelet analysis; Alternate Transient Program(ATP); Artificial Neural Network (ANN); Continuous Wavelet Transform (CWT); Fault location; Transmission line; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Energy, Automation, and Signal (ICEAS), 2011 International Conference on

Conference_Location

Bhubaneswar, Odisha

Print_ISBN

978-1-4673-0137-4

Type

conf

DOI

10.1109/ICEAS.2011.6147206

Filename

6147206