Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence
This paper describes the combination of discrete wavelet transforms (DWT) and artificial intelligence (AI), which are efficient techniques to identify the type of inrush current, analyze the origin and possible cause on the capacitor bank switching. The experiment setup used to verify the proposed t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2018-04-01
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| Series: | Open Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/phys-2018-0016 |
| _version_ | 1819117013306441728 |
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| author | Patcharoen Theerasak Yoomak Suntiti Ngaopitakkul Atthapol Pothisarn Chaichan |
| author_facet | Patcharoen Theerasak Yoomak Suntiti Ngaopitakkul Atthapol Pothisarn Chaichan |
| author_sort | Patcharoen Theerasak |
| collection | DOAJ |
| description | This paper describes the combination of discrete wavelet transforms (DWT) and artificial intelligence (AI), which are efficient techniques to identify the type of inrush current, analyze the origin and possible cause on the capacitor bank switching. The experiment setup used to verify the proposed techniques can be detected and classified the transient inrush current from normal capacitor rated current. The discrete wavelet transforms are used to detect and classify the inrush current. Then, output from wavelet is acted as input of fuzzy inference system for discriminating the type of switching transient inrush current. The proposed technique shows enhanced performance with a discrimination accuracy of 90.57%. Both simulation study and experimental results are quite satisfactory with providing the high accuracy and reliability which can be developed and implemented into a numerical overcurrent (50/51) and unbalanced current (60C) protection relay for an application of shunt capacitor bank protection in the future. |
| first_indexed | 2024-12-22T05:26:14Z |
| format | Article |
| id | doaj.art-73ce7ead30e14722b1157061adc2a995 |
| institution | Directory Open Access Journal |
| issn | 2391-5471 |
| language | English |
| last_indexed | 2024-12-22T05:26:14Z |
| publishDate | 2018-04-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Physics |
| spelling | doaj.art-73ce7ead30e14722b1157061adc2a9952022-12-21T18:37:34ZengDe GruyterOpen Physics2391-54712018-04-011619310410.1515/phys-2018-0016phys-2018-0016Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligencePatcharoen Theerasak0Yoomak Suntiti1Ngaopitakkul Atthapol2Pothisarn Chaichan3Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok10520, ThailandFaculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok10520, ThailandFaculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok10520, ThailandFaculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok10520, ThailandThis paper describes the combination of discrete wavelet transforms (DWT) and artificial intelligence (AI), which are efficient techniques to identify the type of inrush current, analyze the origin and possible cause on the capacitor bank switching. The experiment setup used to verify the proposed techniques can be detected and classified the transient inrush current from normal capacitor rated current. The discrete wavelet transforms are used to detect and classify the inrush current. Then, output from wavelet is acted as input of fuzzy inference system for discriminating the type of switching transient inrush current. The proposed technique shows enhanced performance with a discrimination accuracy of 90.57%. Both simulation study and experimental results are quite satisfactory with providing the high accuracy and reliability which can be developed and implemented into a numerical overcurrent (50/51) and unbalanced current (60C) protection relay for an application of shunt capacitor bank protection in the future.https://doi.org/10.1515/phys-2018-0016capacitor switching transientinrush currentback-to-back capacitor switchingisolated capacitor switchingdiscrete wavelet transformfuzzy inference system88.80.f-84.60.ve |
| spellingShingle | Patcharoen Theerasak Yoomak Suntiti Ngaopitakkul Atthapol Pothisarn Chaichan Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence Open Physics capacitor switching transient inrush current back-to-back capacitor switching isolated capacitor switching discrete wavelet transform fuzzy inference system 88.80.f- 84.60.ve |
| title | Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence |
| title_full | Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence |
| title_fullStr | Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence |
| title_full_unstemmed | Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence |
| title_short | Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence |
| title_sort | simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence |
| topic | capacitor switching transient inrush current back-to-back capacitor switching isolated capacitor switching discrete wavelet transform fuzzy inference system 88.80.f- 84.60.ve |
| url | https://doi.org/10.1515/phys-2018-0016 |
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