Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals
Recent studies have shown that wavelet transform can effectively be used for noise reduction in the context of partial discharge (PD) signal detection and classification. Several thresholding approaches for wavelet denoising have been reported in the literature. In this study, a novel wavelet thresh...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , |
| Format: | article |
| Published: |
2016
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/11073/16307 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513441216069632 |
|---|---|
| author | Hussein, Ramy |
| author2 | Shaban, Khaled Bashir El-Hag, Ayman |
| author2_role | author author |
| author_facet | Hussein, Ramy Shaban, Khaled Bashir El-Hag, Ayman |
| author_role | author |
| dc.creator.none.fl_str_mv | Hussein, Ramy Shaban, Khaled Bashir El-Hag, Ayman |
| dc.date.none.fl_str_mv | 2016-10 2018-11-04T08:59:38Z 2018-11-04T08:59:38Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | Hussein, Ramy, Khaled Bashir Shaban, and Ayman El-Hag. "Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals." IET Science, Measurement & Technology 10, no. 7 (2016): 813–822. 1751-8822 http://hdl.handle.net/11073/16307 10.1049/iet-smt.2016.0168 |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | Institution of Engineering and Technology |
| dc.relation.none.fl_str_mv | IET Science, Measurement & Technology http://dx.doi.org/10.1049/iet-smt.2016.0168 |
| dc.subject.none.fl_str_mv | Eestimation theory Partial discharge measurement Energy conservation Wavelet transforms Signal denoising |
| dc.title.none.fl_str_mv | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Recent studies have shown that wavelet transform can effectively be used for noise reduction in the context of partial discharge (PD) signal detection and classification. Several thresholding approaches for wavelet denoising have been reported in the literature. In this study, a novel wavelet threshold estimation method, named energy conservation-based thresholding (ECBT), is introduced. The proposed thresholding function is capable of conserving a significant portion of the original signal energy, while the threshold value is determined based on the relative difference between the original and noisy signal energies. The proposed method is first applied to PD signals contaminated with different levels of simulated noise. Results show that ECBT produces a denoised PD signal with higher signal-to-noise ratio (SNR) and less distortion than PDs produced by the existing wavelet methods. Then, ECBT is modified to address actual PD signals corrupted with real noise, where a robust SNR estimation method is derived to estimate the noise level embedded in the measured PD signals. The denoised PD signals indicate that the proposed method yields higher reduction in noise levels than other methods. |
| format | article |
| id | aus_1658cefcd3d073aa71b34be1224a18f4 |
| identifier_str_mv | Hussein, Ramy, Khaled Bashir Shaban, and Ayman El-Hag. "Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals." IET Science, Measurement & Technology 10, no. 7 (2016): 813–822. 1751-8822 10.1049/iet-smt.2016.0168 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/16307 |
| publishDate | 2016 |
| publisher.none.fl_str_mv | Institution of Engineering and Technology |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge SignalsHussein, RamyShaban, Khaled BashirEl-Hag, AymanEestimation theoryPartial discharge measurementEnergy conservationWavelet transformsSignal denoisingRecent studies have shown that wavelet transform can effectively be used for noise reduction in the context of partial discharge (PD) signal detection and classification. Several thresholding approaches for wavelet denoising have been reported in the literature. In this study, a novel wavelet threshold estimation method, named energy conservation-based thresholding (ECBT), is introduced. The proposed thresholding function is capable of conserving a significant portion of the original signal energy, while the threshold value is determined based on the relative difference between the original and noisy signal energies. The proposed method is first applied to PD signals contaminated with different levels of simulated noise. Results show that ECBT produces a denoised PD signal with higher signal-to-noise ratio (SNR) and less distortion than PDs produced by the existing wavelet methods. Then, ECBT is modified to address actual PD signals corrupted with real noise, where a robust SNR estimation method is derived to estimate the noise level embedded in the measured PD signals. The denoised PD signals indicate that the proposed method yields higher reduction in noise levels than other methods.Institution of Engineering and Technology2018-11-04T08:59:38Z2018-11-04T08:59:38Z2016-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfHussein, Ramy, Khaled Bashir Shaban, and Ayman El-Hag. "Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals." IET Science, Measurement & Technology 10, no. 7 (2016): 813–822.1751-8822http://hdl.handle.net/11073/1630710.1049/iet-smt.2016.0168en_USIET Science, Measurement & Technologyhttp://dx.doi.org/10.1049/iet-smt.2016.0168oai:repository.aus.edu:11073/163072024-08-22T12:16:35Z |
| spellingShingle | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals Hussein, Ramy Eestimation theory Partial discharge measurement Energy conservation Wavelet transforms Signal denoising |
| status_str | publishedVersion |
| title | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| title_full | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| title_fullStr | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| title_full_unstemmed | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| title_short | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| title_sort | Energy Conservation-based Thresholding for Effective Wavelet Denoising of Partial Discharge Signals |
| topic | Eestimation theory Partial discharge measurement Energy conservation Wavelet transforms Signal denoising |
| url | http://hdl.handle.net/11073/16307 |