Probabilistic wavelet transform for partial discharge measurement of transformer

Seo, Junhyuck, Ma, Hui and Saha, Tapan (2015) Probabilistic wavelet transform for partial discharge measurement of transformer. IEEE Transactions on Dielectrics and Electrical Insulation, 22 2: 1105-1117. doi:10.1109/TDEI.2015.7076812

Author Seo, Junhyuck
Ma, Hui
Saha, Tapan
Title Probabilistic wavelet transform for partial discharge measurement of transformer
Journal name IEEE Transactions on Dielectrics and Electrical Insulation   Check publisher's open access policy
ISSN 1070-9878
Publication date 2015-04
Sub-type Article (original research)
DOI 10.1109/TDEI.2015.7076812
Open Access Status
Volume 22
Issue 2
Start page 1105
End page 1117
Total pages 13
Place of publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Collection year 2016
Language eng
Formatted abstract
Partial discharge (PD) measurement provides a means for online monitoring and diagnosis of transformers. However, extensive interferences and noise can significantly jeopardize the measured PD signals and cause ambiguity in PD measurement interpretation. Necessary PD signal de-noising techniques need to be adopted and wavelet transform is one of such techniques. Mother wavelet selection, decomposition level determination and thresholding are important processes for effective PD extraction using wavelet transform. Various methods have been proposed in the literature to improve the above processes of wavelet transform. In these methods a single threshold is normally adopted at each decomposition level and a binary decision is made to indicate whether an extracted signal is PD signal or noise. However, in online PD measurements it is difficult to find a threshold, which can be used for extracting only PD signals without including any noise. As such, the signals determined by a single threshold cannot be assured as PD signals with certainty. To address the limitations caused by the single thresholding method in wavelet transform for PD signals extraction, this paper proposes quantile based multi-scale thresholding method at each decomposition level, which can thus provide probability indexes for the extracted signals evaluating the likelihood of these signals to be PD signals. To evaluate the proposed method, PD measurements have been conducted on both experimental PD models and inservice transformers at substation. The results are provided in the paper.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Other title: "Wavelet-based Probabilistic Partial Discharge extraction and interpretation for Power Transformer".

NB: Incorrect DOI:10.1109/TDEI.2014.004236 listed on Paper.

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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Created: Mon, 13 Apr 2015, 19:12:35 EST by Dr Hui Ma on behalf of School of Information Technol and Elec Engineering