Power Quality Disturbances Detection and Classification Rule-Based Decision Tree

dc.contributor.advisorZaro, Fouad
dc.contributor.authorZaro, Fouad
dc.date.accessioned2021-06-17T11:17:26Z
dc.date.accessioned2022-05-22T08:55:27Z
dc.date.available2021-06-17T11:17:26Z
dc.date.available2022-05-22T08:55:27Z
dc.date.issued2021-03-30
dc.description.abstractIn this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (Stransform) and rule-based decision tree (DT) according to IEEE standards. The proposed technique based on the extracted features of the PQ events signals, which are extracted from the time-frequency analysis. Several PQ disturbances are considered with simple and complex disturbances to include spike, flicker, oscillatory transient, impulsive transient, and notch. The performance and robustness of the proposed technique for the recognition of PQ disturbances have been demonstrated through the results of the various disturbances. By comparing the performance of the proposed technique with other reported studies it was distinguished results under noiseless and noisy conditions.en_US
dc.identifier.citationF. R. Zaro, "Power Quality Disturbances Detection and Classification Rule-Based Decision Tree", International Journal of Engineering Science and Application, Vol.5, No.1, pp. 1-6, March 2021.en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/8343
dc.language.isoenen_US
dc.publisherINTERNATIONAL JOURNAL of ENGINEERING SCIENCE AND APPLICATIONen_US
dc.subjectPower Qualityen_US
dc.subjectRule-based decision treeen_US
dc.subjectFeature extractionen_US
dc.titlePower Quality Disturbances Detection and Classification Rule-Based Decision Treeen_US
dc.typeArticleen_US

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