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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Nattapong Praditphol | en_US |
| dc.contributor.author | Suttichai Premrudeepreechacharn | en_US |
| dc.date.accessioned | 2018-09-10T03:16:55Z | - |
| dc.date.available | 2018-09-10T03:16:55Z | - |
| dc.date.issued | 2009-12-01 | en_US |
| dc.identifier.other | 2-s2.0-77954795856 | en_US |
| dc.identifier.other | 10.1109/NAPS.2009.5483982 | en_US |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77954795856&origin=inward | en_US |
| dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/59536 | - |
| dc.description.abstract | This paper presents a classification faults in electrical power systems. To improve the electric power quality, sources of disturbances must be known and controlled. Power quality disturbance waveform recognition is often troublesome because it involves a broad range of disturbance categories or classes. This is a study of fault events classification using wavelet transformation and expert rule base. Rule base is obtained for using to classify the power quality problems. The combined wavelet transformation with expert rule is able to classify all 4 types of fault events correctly. | en_US |
| dc.subject | Energy | en_US |
| dc.title | Classification fault events using wavelet transform and expert rules | en_US |
| dc.type | Conference Proceeding | en_US |
| article.title.sourcetitle | 41st North American Power Symposium, NAPS 2009 | en_US |
| article.stream.affiliations | Chiang Mai University | en_US |
| Appears in Collections: | CMUL: Journal Articles | |
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