Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis
Monitoring the degradation of insulation systems in high-voltage equipment relies on identifying physical, chemical, or electrical phenomena occurring during operation, with partial discharge (PD) activity recognized as a primary indicator of insulation system deterioration. This study introduces a...
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11048932/ |
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| author | Francisco de A. Oliveira Nascimento Rodrigo De A. Coelho George V. R. Xavier Pedro D. Alvim Almir C. Dos Santos Junior Hugerles S. Silva |
| author_facet | Francisco de A. Oliveira Nascimento Rodrigo De A. Coelho George V. R. Xavier Pedro D. Alvim Almir C. Dos Santos Junior Hugerles S. Silva |
| author_sort | Francisco de A. Oliveira Nascimento |
| collection | DOAJ |
| description | Monitoring the degradation of insulation systems in high-voltage equipment relies on identifying physical, chemical, or electrical phenomena occurring during operation, with partial discharge (PD) activity recognized as a primary indicator of insulation system deterioration. This study introduces a novel methodology for denoising, wavefront identification, and transient segmentation of PD signals collected in laboratory and substation settings using a printed monopole antenna (PMA) operating at ultra high-frequency (UHF). The proposed approach employs a shift-invariant wavelet denoising technique, where thresholds are estimated using the empirical Bayes method at each decomposition level of the wavelet transform. The denoised signal is subsequently processed through linear zero-phase filtering and post-processing steps to determine the start and end points of the PD event and to mitigate distortion effects introduced by denoising and other disturbances. The proposed methodology enables accurate identification of the first wavefront occurrence and segmentation of the PD event, offering enhanced precision for future studies on PD localization and classification. Experimental results showed substantial improvements in signal-to-noise ratio (SNR), high cross-correlation between the original and denoised signals, and a significant reduction in normalized mean squared error, confirming the robustness of the method under low-SNR conditions. |
| format | Article |
| id | doaj-art-b2bcbcccbd0e4085a26e9629fac998c9 |
| institution | Matheson Library |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b2bcbcccbd0e4085a26e9629fac998c92025-07-03T23:00:44ZengIEEEIEEE Access2169-35362025-01-011311160211161310.1109/ACCESS.2025.358263511048932Wavefront Detection and Event Segmentation Method for Partial Discharge Signal AnalysisFrancisco de A. Oliveira Nascimento0https://orcid.org/0000-0002-8217-1983Rodrigo De A. Coelho1George V. R. Xavier2Pedro D. Alvim3Almir C. Dos Santos Junior4https://orcid.org/0009-0000-7250-357XHugerles S. Silva5https://orcid.org/0000-0003-0165-5853Electrical Engineering Department, University of Brasília, Brasília, BrazilEngineering Department, Federal Rural University of the Semi-Arid Region, Caraúbas, Rio Grande do Norte, BrazilElectrical Engineering Department, Federal University of Sergipe, São Cristóvão, Sergipe, BrazilElectrical Engineering Department, University of Brasília, Brasília, BrazilElectrical Engineering Department, Federal University of Rondônia, Porto Velho, Rondônia, BrazilElectrical Engineering Department, University of Brasília, Brasília, BrazilMonitoring the degradation of insulation systems in high-voltage equipment relies on identifying physical, chemical, or electrical phenomena occurring during operation, with partial discharge (PD) activity recognized as a primary indicator of insulation system deterioration. This study introduces a novel methodology for denoising, wavefront identification, and transient segmentation of PD signals collected in laboratory and substation settings using a printed monopole antenna (PMA) operating at ultra high-frequency (UHF). The proposed approach employs a shift-invariant wavelet denoising technique, where thresholds are estimated using the empirical Bayes method at each decomposition level of the wavelet transform. The denoised signal is subsequently processed through linear zero-phase filtering and post-processing steps to determine the start and end points of the PD event and to mitigate distortion effects introduced by denoising and other disturbances. The proposed methodology enables accurate identification of the first wavefront occurrence and segmentation of the PD event, offering enhanced precision for future studies on PD localization and classification. Experimental results showed substantial improvements in signal-to-noise ratio (SNR), high cross-correlation between the original and denoised signals, and a significant reduction in normalized mean squared error, confirming the robustness of the method under low-SNR conditions.https://ieeexplore.ieee.org/document/11048932/Event segmentationpartial dischargesprinted monopole antennasUHF methodwavefront detection |
| spellingShingle | Francisco de A. Oliveira Nascimento Rodrigo De A. Coelho George V. R. Xavier Pedro D. Alvim Almir C. Dos Santos Junior Hugerles S. Silva Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis IEEE Access Event segmentation partial discharges printed monopole antennas UHF method wavefront detection |
| title | Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis |
| title_full | Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis |
| title_fullStr | Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis |
| title_full_unstemmed | Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis |
| title_short | Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis |
| title_sort | wavefront detection and event segmentation method for partial discharge signal analysis |
| topic | Event segmentation partial discharges printed monopole antennas UHF method wavefront detection |
| url | https://ieeexplore.ieee.org/document/11048932/ |
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