TY - GEN
T1 - Evaluation of statistical interpretation methods for frequency response analysis based winding fault detection of transformers
AU - Wesley, Neoh Khoo
AU - Bhandari, Saurabh
AU - Subramaniam, Aravinth
AU - Bagheri, Mehdi
AU - Panda, Sanjib Kumar
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/9
Y1 - 2017/1/9
N2 - Frequency Response Analysis (FRA) is an offline condition monitoring technique commonly used to diagnose the mechanical integrity of transformers. Due to high accuracy and sensitivity, FRA has become a common practice in the industry for assessment of winding health. However, interpretation of FRA measurements is still limited to analysis by field engineers relying entirely on their past experiences and expertise. In order to aid the FRA based Condition monitoring, this paper evaluates different statistical indicators, developing and collecting them on a single platform, namely an automated interpretation package for FRA signatures. A MATLAB based GUI has been developed to aid detection of transformer faults. Experimental verification consisting of inter-Turn short circuit fault studies on a 15 kVA cast-resin transformer to examine developed automated package has also been reported as part of this work.
AB - Frequency Response Analysis (FRA) is an offline condition monitoring technique commonly used to diagnose the mechanical integrity of transformers. Due to high accuracy and sensitivity, FRA has become a common practice in the industry for assessment of winding health. However, interpretation of FRA measurements is still limited to analysis by field engineers relying entirely on their past experiences and expertise. In order to aid the FRA based Condition monitoring, this paper evaluates different statistical indicators, developing and collecting them on a single platform, namely an automated interpretation package for FRA signatures. A MATLAB based GUI has been developed to aid detection of transformer faults. Experimental verification consisting of inter-Turn short circuit fault studies on a 15 kVA cast-resin transformer to examine developed automated package has also been reported as part of this work.
KW - Analysis Techniques
KW - Condition Monitoring
KW - Fault Diagnosis
KW - Frequency Response Analysis (FRA)
KW - Statistical Analysis
KW - Transformer
UR - http://www.scopus.com/inward/record.url?scp=85011876461&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85011876461&partnerID=8YFLogxK
U2 - 10.1109/ICSET.2016.7811753
DO - 10.1109/ICSET.2016.7811753
M3 - Conference contribution
AN - SCOPUS:85011876461
T3 - IEEE International Conference on Sustainable Energy Technologies, ICSET
SP - 36
EP - 41
BT - 2016 IEEE International Conference on Sustainable Energy Technologies, ICSET 2016
PB - IEEE Computer Society
T2 - 4th IEEE International Conference on Sustainable Energy Technologies, ICSET 2016
Y2 - 14 November 2016 through 16 November 2016
ER -
