Hybrid method on signal de-noising and representation for online partial discharge monitoring of power transformers at substations

Chan, Jeffery C., Ma, Hui and Saha, Tapan K. (2015) Hybrid method on signal de-noising and representation for online partial discharge monitoring of power transformers at substations. IET Science, Measurement and Technology, 9 7: 890-899. doi:10.1049/iet-smt.2014.0358


Author Chan, Jeffery C.
Ma, Hui
Saha, Tapan K.
Title Hybrid method on signal de-noising and representation for online partial discharge monitoring of power transformers at substations
Journal name IET Science, Measurement and Technology   Check publisher's open access policy
ISSN 1751-8822
1751-8830
Publication date 2015-06-18
Year available 2015
Sub-type Article (original research)
DOI 10.1049/iet-smt.2014.0358
Open Access Status Not Open Access
Volume 9
Issue 7
Start page 890
End page 899
Total pages 10
Place of publication Stevenage, Herts, United Kingdom
Publisher The Institution of Engineering and Technology
Language eng
Formatted abstract
To ensure reliable operations of power transformers, online condition monitoring needs to be performed. However, extensive noise can be coupled into measured signals and cause ambiguities in evaluating transformers’ conditions. This study proposes a hybrid method, which combines pre-whitening and blind equalisation for de-noising the signals obtained from online partial discharge (PD) measurements of transformers. A measured signal is first gone through a pre-whitening process for initial noise reduction and then processed by blind equalisation. Finally, an equalised signal that can reveal PD source in a transformer is converted to a kurtogram for an accurate PD pattern representation. The proposed method has been applied to signals obtained from laboratory experiments and online measurements of transformers at substations. Results show that the method can effectively de-noise PD signals contaminated by severe noise and consistently represent PD patterns induced by different PD sources.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 5 times in Thomson Reuters Web of Science Article | Citations
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Created: Wed, 24 Jun 2015, 22:40:57 EST by Dr Hui Ma on behalf of School of Information Technol and Elec Engineering