Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier
In this paper, a simple and efficient method for detection high impedance fault (HIF) on power distribution systems using an intelligent approach the probabilistic neural network (PNN) combined with wavelet transform technique is proposed. A high impedance fault has impedance enough high so that con...
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| Format: | Article |
| Language: | en |
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Little Lion Scientific Islamabad Pakistan
2013
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| Online Access: | http://eprints.utem.edu.my/id/eprint/6552/1/marizan%232.pdf http://eprints.utem.edu.my/id/eprint/6552/ http://www.jatit.org/volumes/Vol53No2/4Vol53No2.pdf |
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| author | Sulaiman, Marizan Ibrahim, Zulkifilie Tawafan, Adnan |
| author_facet | Sulaiman, Marizan Ibrahim, Zulkifilie Tawafan, Adnan |
| author_sort | Sulaiman, Marizan |
| building | UTEM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknikal Malaysia Melaka |
| content_source | UTEM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In this paper, a simple and efficient method for detection high impedance fault (HIF) on power distribution systems using an intelligent approach the probabilistic neural network (PNN) combined with wavelet transform technique is proposed. A high impedance fault has impedance enough high so that conventional overcurrent devices, like overcurrent relays and fuses, cannot detect it. While low impedance faults, which include comparatively large fault currents are easily detected by conventional overcurrent devices. Both frequency and time data are needed to get the exact information to classify and detect no fault from HIF. In the proposed method, DWT is used to extract feature of the no fault and HIF signals. The features extracted which comprise the energy of detail and approximate coefficients of the voltage, current and power signals calculated at a chosen level frequency are utilized to train and test the probabilistic neural network (PNN) for a precise classification of no fault from HIFs. |
| format | Article |
| id | my.utem.eprints-6552 |
| institution | Universiti Teknikal Malaysia Melaka |
| language | en |
| publishDate | 2013 |
| publisher | Little Lion Scientific Islamabad Pakistan |
| record_format | eprints |
| spelling | my.utem.eprints-65522022-01-28T16:24:01Z http://eprints.utem.edu.my/id/eprint/6552/ Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier Sulaiman, Marizan Ibrahim, Zulkifilie Tawafan, Adnan TK Electrical engineering. Electronics Nuclear engineering In this paper, a simple and efficient method for detection high impedance fault (HIF) on power distribution systems using an intelligent approach the probabilistic neural network (PNN) combined with wavelet transform technique is proposed. A high impedance fault has impedance enough high so that conventional overcurrent devices, like overcurrent relays and fuses, cannot detect it. While low impedance faults, which include comparatively large fault currents are easily detected by conventional overcurrent devices. Both frequency and time data are needed to get the exact information to classify and detect no fault from HIF. In the proposed method, DWT is used to extract feature of the no fault and HIF signals. The features extracted which comprise the energy of detail and approximate coefficients of the voltage, current and power signals calculated at a chosen level frequency are utilized to train and test the probabilistic neural network (PNN) for a precise classification of no fault from HIFs. Little Lion Scientific Islamabad Pakistan 2013-07 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/6552/1/marizan%232.pdf Sulaiman, Marizan and Ibrahim, Zulkifilie and Tawafan, Adnan (2013) Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier. Journal of Theoretical and Applied Information Technology, 53 (2). pp. 180-191. ISSN 1992-8645 http://www.jatit.org/volumes/Vol53No2/4Vol53No2.pdf |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Sulaiman, Marizan Ibrahim, Zulkifilie Tawafan, Adnan Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier |
| title | Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier |
| title_full | Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier |
| title_fullStr | Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier |
| title_full_unstemmed | Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier |
| title_short | Detection of High Impedance Fault Using a Probabilistic Neural-Network Classifier |
| title_sort | detection of high impedance fault using a probabilistic neural-network classifier |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utem.edu.my/id/eprint/6552/1/marizan%232.pdf http://eprints.utem.edu.my/id/eprint/6552/ http://www.jatit.org/volumes/Vol53No2/4Vol53No2.pdf |
| url_provider | http://eprints.utem.edu.my/ |