FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe
Partial discharge (PD) is a common reason that causes electrical breakdown in high voltage underground XLPE cables. This paper proposes a concept of how to build an on-line, on-site system that is able to diagnose the severity of PD activities in XLPE cable as well as differentiate different types o...
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2023
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| author | Nguyen T.N.T. Chandan K.C. Ahmad B.A.G. Yap K.S. |
| author2 | 54584502600 |
| author_facet | 54584502600 Nguyen T.N.T. Chandan K.C. Ahmad B.A.G. Yap K.S. |
| author_sort | Nguyen T.N.T. |
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| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Partial discharge (PD) is a common reason that causes electrical breakdown in high voltage underground XLPE cables. This paper proposes a concept of how to build an on-line, on-site system that is able to diagnose the severity of PD activities in XLPE cable as well as differentiate different types of PD signals. The system consists of magnetic probes, low noise amplifier, 3GSPS analog to digital converter (ADC) and a field programmable gate array (FPGA) board. The energy of PD signals is used to assess the severity of PD activities and artificial neural network (ANN) is used to classify different types of PD waveforms. In addition, wavelet transform is used to clean the time-resolved input signals and statistical method is used to extract important features of PD signals to fetch into neural network. The training of ANN is done on personal computer. The prototype and results of the research is elaborated in this paper. � 2011 IEEE. |
| format | Conference paper |
| id | my.uniten.dspace-30424 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| record_format | dspace |
| spelling | my.uniten.dspace-304242023-12-29T15:47:41Z FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe Nguyen T.N.T. Chandan K.C. Ahmad B.A.G. Yap K.S. 54584502600 6701755282 56102167200 24448864400 FPGA magnetic probes neural network partial discharge statistical method wavelet transform Field programmable gate arrays (FPGA) Low noise amplifiers Neural networks Personal computers Probes Statistical methods Underground cables Wavelet transforms Analog to digital converters Discharge time Electrical breakdown FPGA implementations High voltage Input signal Magnetic probes Neural network classifier Onsite systems Time-resolved Wave forms XLPE cables Partial discharges Partial discharge (PD) is a common reason that causes electrical breakdown in high voltage underground XLPE cables. This paper proposes a concept of how to build an on-line, on-site system that is able to diagnose the severity of PD activities in XLPE cable as well as differentiate different types of PD signals. The system consists of magnetic probes, low noise amplifier, 3GSPS analog to digital converter (ADC) and a field programmable gate array (FPGA) board. The energy of PD signals is used to assess the severity of PD activities and artificial neural network (ANN) is used to classify different types of PD waveforms. In addition, wavelet transform is used to clean the time-resolved input signals and statistical method is used to extract important features of PD signals to fetch into neural network. The training of ANN is done on personal computer. The prototype and results of the research is elaborated in this paper. � 2011 IEEE. Final 2023-12-29T07:47:41Z 2023-12-29T07:47:41Z 2011 Conference paper 10.1109/APAP.2011.6180444 2-s2.0-84860689238 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84860689238&doi=10.1109%2fAPAP.2011.6180444&partnerID=40&md5=367d97167623d0975982902db8c5aafa https://irepository.uniten.edu.my/handle/123456789/30424 1 6180444 451 455 Scopus |
| spellingShingle | FPGA magnetic probes neural network partial discharge statistical method wavelet transform Field programmable gate arrays (FPGA) Low noise amplifiers Neural networks Personal computers Probes Statistical methods Underground cables Wavelet transforms Analog to digital converters Discharge time Electrical breakdown FPGA implementations High voltage Input signal Magnetic probes Neural network classifier Onsite systems Time-resolved Wave forms XLPE cables Partial discharges Nguyen T.N.T. Chandan K.C. Ahmad B.A.G. Yap K.S. FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| title | FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| title_full | FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| title_fullStr | FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| title_full_unstemmed | FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| title_short | FPGA implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| title_sort | fpga implementation of neural network classifier for partial discharge time resolved data from magnetic probe |
| topic | FPGA magnetic probes neural network partial discharge statistical method wavelet transform Field programmable gate arrays (FPGA) Low noise amplifiers Neural networks Personal computers Probes Statistical methods Underground cables Wavelet transforms Analog to digital converters Discharge time Electrical breakdown FPGA implementations High voltage Input signal Magnetic probes Neural network classifier Onsite systems Time-resolved Wave forms XLPE cables Partial discharges |
| url_provider | http://dspace.uniten.edu.my/ |