An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment
Partial Discharge (PD) diagnostic is an effective tool for condition monitoring of the high voltage equipment that provides an updated status of the dielectric insulation of the components. Reliability of the diagnostics depends on the quality of the PD measurement techniques and the processing of t...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2020
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| الوصول للمادة أونلاين: | https://dspace.auk.edu.kw/handle/11675/8229 https://www.tandfonline.com/doi/abs/10.1080/15325008.2020.1825554 |
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| _version_ | 1870679724528762880 |
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| author | Hussain, Ghulam |
| author2 | Ahmed, Zeeshan Shafiq, Muhammad Lehtonen, Matti Rashid, Zeeshan Zaher, Ashraf |
| author2_role | author author author author author |
| author_facet | Hussain, Ghulam Ahmed, Zeeshan Shafiq, Muhammad Lehtonen, Matti Rashid, Zeeshan Zaher, Ashraf |
| author_role | author |
| dc.creator.none.fl_str_mv | Hussain, Ghulam Ahmed, Zeeshan Shafiq, Muhammad Lehtonen, Matti Rashid, Zeeshan Zaher, Ashraf |
| dc.date.none.fl_str_mv | 2020-10-21 2021-12-22T08:28:05Z 2021-12-22T08:28:05Z |
| dc.identifier.none.fl_str_mv | Hussain, A., Ahmed, Z., Shafiq, M., Zaher, A., Rashid, Z., & Lehtonen, M. (2020). An adaptive denoising algorithm for online condition monitoring of high-voltage power equipment. Electric Power Components and Systems, 48(9-10), 1036-1048. https://doi.org/10.1080/15325008.2020.1825554 https://dspace.auk.edu.kw/handle/11675/8229 https://www.tandfonline.com/doi/abs/10.1080/15325008.2020.1825554 |
| dc.publisher.none.fl_str_mv | Taylor and Francis- Electric Power Components and Systems |
| dc.relation.none.fl_str_mv | College of Engineering and Applied Sciences |
| dc.title.none.fl_str_mv | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| dc.type.none.fl_str_mv | Journal Article Peer-Reviewed info:eu-repo/semantics/publishedVersion |
| description | Partial Discharge (PD) diagnostic is an effective tool for condition monitoring of the high voltage equipment that provides an updated status of the dielectric insulation of the components. Reliability of the diagnostics depends on the quality of the PD measurement techniques and the processing of the measured PD data. The online measured data suffer from various inaccuracies caused by external noise from various sources such as power electronic equipment, radio broadband signals and wireless communication, etc. Therefore, extraction of useful data from the on-site measurements is still a challenge. This article presents a discrete wavelet transform (DWT) based adaptive de-noising algorithm and evaluates its performance. Various decisive steps in applying DWT based de-noising on any signal, including selection of mother wavelet, number of levels in multiresolution decomposition and criteria for reconstruction of the de-noised signals are taken by the proposed algorithm and vary from one signal to another without a human intervention. Hence, the proposed technique is adaptive. The proposed solution can enhance the accuracy of the PD diagnostic for HV power components. |
| id | AUKR_daa352ea21cd46efdd6f400090e0a729 |
| identifier_str_mv | Hussain, A., Ahmed, Z., Shafiq, M., Zaher, A., Rashid, Z., & Lehtonen, M. (2020). An adaptive denoising algorithm for online condition monitoring of high-voltage power equipment. Electric Power Components and Systems, 48(9-10), 1036-1048. https://doi.org/10.1080/15325008.2020.1825554 |
| network_acronym_str | AUKR |
| network_name_str | AU Kuwait Rep |
| oai_identifier_str | oai:dspace.auk.edu.kw:11675/8229 |
| publishDate | 2020 |
| publisher.none.fl_str_mv | Taylor and Francis- Electric Power Components and Systems |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power EquipmentHussain, GhulamAhmed, ZeeshanShafiq, MuhammadLehtonen, MattiRashid, ZeeshanZaher, AshrafPartial Discharge (PD) diagnostic is an effective tool for condition monitoring of the high voltage equipment that provides an updated status of the dielectric insulation of the components. Reliability of the diagnostics depends on the quality of the PD measurement techniques and the processing of the measured PD data. The online measured data suffer from various inaccuracies caused by external noise from various sources such as power electronic equipment, radio broadband signals and wireless communication, etc. Therefore, extraction of useful data from the on-site measurements is still a challenge. This article presents a discrete wavelet transform (DWT) based adaptive de-noising algorithm and evaluates its performance. Various decisive steps in applying DWT based de-noising on any signal, including selection of mother wavelet, number of levels in multiresolution decomposition and criteria for reconstruction of the de-noised signals are taken by the proposed algorithm and vary from one signal to another without a human intervention. Hence, the proposed technique is adaptive. The proposed solution can enhance the accuracy of the PD diagnostic for HV power components.Taylor and Francis- Electric Power Components and Systems2021-12-22T08:28:05Z2021-12-22T08:28:05Z2020-10-21Journal ArticlePeer-Reviewedinfo:eu-repo/semantics/publishedVersionHussain, A., Ahmed, Z., Shafiq, M., Zaher, A., Rashid, Z., & Lehtonen, M. (2020). An adaptive denoising algorithm for online condition monitoring of high-voltage power equipment. Electric Power Components and Systems, 48(9-10), 1036-1048. https://doi.org/10.1080/15325008.2020.1825554https://dspace.auk.edu.kw/handle/11675/8229https://www.tandfonline.com/doi/abs/10.1080/15325008.2020.1825554College of Engineering and Applied Sciencesoai:dspace.auk.edu.kw:11675/82292022-01-17T09:13:57Z |
| spellingShingle | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment Hussain, Ghulam |
| status_str | publishedVersion |
| title | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| title_full | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| title_fullStr | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| title_full_unstemmed | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| title_short | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| title_sort | An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment |
| url | https://dspace.auk.edu.kw/handle/11675/8229 https://www.tandfonline.com/doi/abs/10.1080/15325008.2020.1825554 |