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Reseach Article

Improved Detection Sensitivity with Combined WPT and HHT for Power Transformer Winding Deformation Analysis

Published on July 2014 by M. Arivamudhan, S. Santhi, S. Abirami, G. Sugasini
Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering
Foundation of Computer Science USA
ETEIAC - Number 1
July 2014
Authors: M. Arivamudhan, S. Santhi, S. Abirami, G. Sugasini
3f37262f-49ab-4bc3-8a11-46dcc1e9b9e0

M. Arivamudhan, S. Santhi, S. Abirami, G. Sugasini . Improved Detection Sensitivity with Combined WPT and HHT for Power Transformer Winding Deformation Analysis. Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering. ETEIAC, 1 (July 2014), 5-9.

@article{
author = { M. Arivamudhan, S. Santhi, S. Abirami, G. Sugasini },
title = { Improved Detection Sensitivity with Combined WPT and HHT for Power Transformer Winding Deformation Analysis },
journal = { Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering },
issue_date = { July 2014 },
volume = { ETEIAC },
number = { 1 },
month = { July },
year = { 2014 },
issn = 0975-8887,
pages = { 5-9 },
numpages = 5,
url = { /proceedings/eteiac/number1/17327-1405/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering
%A M. Arivamudhan
%A S. Santhi
%A S. Abirami
%A G. Sugasini
%T Improved Detection Sensitivity with Combined WPT and HHT for Power Transformer Winding Deformation Analysis
%J Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering
%@ 0975-8887
%V ETEIAC
%N 1
%P 5-9
%D 2014
%I International Journal of Computer Applications
Abstract

The success of health monitoring and condition assessment of power transformers based on winding current signature analysis lies on proper extraction of features. The extraction of features in turn depends on appropriate signal processing methods. Fourier based signal analysis provides only frequency information and also suitable only for stationary signals. In this paper we present a combined Wavelet Packet Transform (WPT) and Hilbert Huang Transform (HHT) based time scale and time frequency analysis for the extraction of power transformer winding current features through an experimental study. The experimental work is based on short circuit test conducted on a 33 kV/11 kV, 10 MVA power transformer and axial winding deformation fault is introduced by loosening the bolts of winding structure. It is observed that Combined WPT and HHT offers better feature extraction strategy than analysis using HHT alone.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Transformer Wpt Hht Axial Deformation Feature Extraction Detection Sensitivity