Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables
This paper primarily discusses the measurement of partial discharge (PD) phenomena and clustering in the defect pattern of a cross-linked polyethylene power cable joint. First, a high-speed data acquisition and pretreatment were performed for PD electrical signals at a sampling rate of 20 MS/s. The...
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8733789/ |
| _version_ | 1818557547126194176 |
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| author | Feng-Chang Gu Her-Terng Yau Hung-Cheng Chen |
| author_facet | Feng-Chang Gu Her-Terng Yau Hung-Cheng Chen |
| author_sort | Feng-Chang Gu |
| collection | DOAJ |
| description | This paper primarily discusses the measurement of partial discharge (PD) phenomena and clustering in the defect pattern of a cross-linked polyethylene power cable joint. First, a high-speed data acquisition and pretreatment were performed for PD electrical signals at a sampling rate of 20 MS/s. The crucial characteristic signals were reversed to reduce the calculated amount of noise. A characteristic matrix was created according to the resulting dynamic error of chaos synchronization. The characteristic parameters were extracted using the fractal theory. Finally, the extension theory was used to develop a diagnostic system and anti-interference test. A comparison with the existing Hilbert-Huang transform (HHT) method revealed that the two characteristics extracted from the chaos synchronization results using the fractal theory were recognized at a higher pattern recognition rate by employing the extension theory. The proposed method can extract crucial information concerning PD as a defect in power cable joints. |
| first_indexed | 2024-12-14T00:00:56Z |
| format | Article |
| id | doaj.art-584fe4c813704e5ab9acb8575ca6713f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T00:00:56Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-584fe4c813704e5ab9acb8575ca6713f2022-12-21T23:26:20ZengIEEEIEEE Access2169-35362019-01-017761857619310.1109/ACCESS.2019.29218138733789Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power CablesFeng-Chang Gu0https://orcid.org/0000-0001-5465-3873Her-Terng Yau1https://orcid.org/0000-0002-1187-1771Hung-Cheng Chen2Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, TaiwanDepartment of Electrical Engineering, National Chin-Yi University of Technology, Taichung, TaiwanDepartment of Electrical Engineering, National Chin-Yi University of Technology, Taichung, TaiwanThis paper primarily discusses the measurement of partial discharge (PD) phenomena and clustering in the defect pattern of a cross-linked polyethylene power cable joint. First, a high-speed data acquisition and pretreatment were performed for PD electrical signals at a sampling rate of 20 MS/s. The crucial characteristic signals were reversed to reduce the calculated amount of noise. A characteristic matrix was created according to the resulting dynamic error of chaos synchronization. The characteristic parameters were extracted using the fractal theory. Finally, the extension theory was used to develop a diagnostic system and anti-interference test. A comparison with the existing Hilbert-Huang transform (HHT) method revealed that the two characteristics extracted from the chaos synchronization results using the fractal theory were recognized at a higher pattern recognition rate by employing the extension theory. The proposed method can extract crucial information concerning PD as a defect in power cable joints.https://ieeexplore.ieee.org/document/8733789/Chaos synchronizationextensionfractalHilbert–Huang transformpartial discharge |
| spellingShingle | Feng-Chang Gu Her-Terng Yau Hung-Cheng Chen Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables IEEE Access Chaos synchronization extension fractal Hilbert–Huang transform partial discharge |
| title | Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables |
| title_full | Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables |
| title_fullStr | Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables |
| title_full_unstemmed | Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables |
| title_short | Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables |
| title_sort | application of chaos synchronization technique and pattern clustering for diagnosis analysis of partial discharge in power cables |
| topic | Chaos synchronization extension fractal Hilbert–Huang transform partial discharge |
| url | https://ieeexplore.ieee.org/document/8733789/ |
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