POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK
In this paper, the power signal disturbances are detected using discrete wavelet transform (DWT) and categorized using neural networks. This paper presents a prototype of power quality disturbance recognition system. The prototype contains three main components. First a simulator is used to generate...
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Brunei Darussalam
2017-11-01
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| Series: | ASEAN Journal on Science and Technology for Development |
| Subjects: | |
| Online Access: | http://www.ajstd.org/index.php/ajstd/article/view/243 |
| _version_ | 1797331347787743232 |
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| author | S. Suja Jovitha Jerome |
| author_facet | S. Suja Jovitha Jerome |
| author_sort | S. Suja |
| collection | DOAJ |
| description | In this paper, the power signal disturbances are detected using discrete wavelet transform (DWT) and categorized using neural networks. This paper presents a prototype of power quality disturbance recognition system. The prototype contains three main components. First a simulator is used to generate power signal disturbances. The second component is a detector which uses the technique of DWT to detect the power signal disturbances. DWT is used to extract disturbance features in the power signal. The third component is neural network architecture to classify the power signal disturbances. |
| first_indexed | 2024-03-08T07:34:15Z |
| format | Article |
| id | doaj.art-6a1d12c8882e42c49c4d4b002dfd47df |
| institution | Directory Open Access Journal |
| issn | 0217-5460 2224-9028 |
| language | English |
| last_indexed | 2024-03-08T07:34:15Z |
| publishDate | 2017-11-01 |
| publisher | Universiti Brunei Darussalam |
| record_format | Article |
| series | ASEAN Journal on Science and Technology for Development |
| spelling | doaj.art-6a1d12c8882e42c49c4d4b002dfd47df2024-02-02T19:38:52ZengUniversiti Brunei DarussalamASEAN Journal on Science and Technology for Development0217-54602224-90282017-11-0125220521710.29037/ajstd.243238POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORKS. Suja0Jovitha Jerome1Coimbatore Institute of Technology. Coimbatore - 14, TNPSG College of Technology, Coimbatore - 4, TNIn this paper, the power signal disturbances are detected using discrete wavelet transform (DWT) and categorized using neural networks. This paper presents a prototype of power quality disturbance recognition system. The prototype contains three main components. First a simulator is used to generate power signal disturbances. The second component is a detector which uses the technique of DWT to detect the power signal disturbances. DWT is used to extract disturbance features in the power signal. The third component is neural network architecture to classify the power signal disturbances.http://www.ajstd.org/index.php/ajstd/article/view/243wavelet transformpower quality disturbancesprobabilistic neural networkmutiresolution analysis. |
| spellingShingle | S. Suja Jovitha Jerome POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK ASEAN Journal on Science and Technology for Development wavelet transform power quality disturbances probabilistic neural network mutiresolution analysis. |
| title | POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK |
| title_full | POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK |
| title_fullStr | POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK |
| title_full_unstemmed | POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK |
| title_short | POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK |
| title_sort | power signal disturbance classification using wavelet based neural network |
| topic | wavelet transform power quality disturbances probabilistic neural network mutiresolution analysis. |
| url | http://www.ajstd.org/index.php/ajstd/article/view/243 |
| work_keys_str_mv | AT ssuja powersignaldisturbanceclassificationusingwaveletbasedneuralnetwork AT jovithajerome powersignaldisturbanceclassificationusingwaveletbasedneuralnetwork |