Support Vector Machine for Discrimination Between Fault and Magnetizing Inrush Current in Power Transformer
نویسندگان
چکیده
منابع مشابه
Support Vector Machine for Discrimination Between Fault and Magnetizing Inrush Current in Power Transformer
This study presents a novel technique based on Support Vector Machine (SVM) for the classification of transient phenomena in power transformer. The SVM is a powerful method for statistical classification of data. The input data to this SVM for training comprises fault current and magnetizing inrush current. SVM classifier produces significant accuracy for classification of transient phenomena i...
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Transformer protection is critical issue in power system as the issue lies in the accurate and rapid discrimination of magnetizing inrush current from internal fault current. Artificial neural network has been proposed and has demonstrated the capability of solving the transformer monitoring and fault detection problem using an inexpensive, reliable, and noninvasive procedure. This paper gives ...
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one of the major problems that may occur in the differential protection systems of power transformers is mal-operation of the protection relays in sake of internal fault detection, because of similarity between this current and inrush current. this paper presents a novel approach for discriminating inrush current from internal fault in power transformers based on improved gravitational search a...
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This paper presents the application of the fuzzy-neuro method toinvestigate transformer inrush current. Recently, the frequency environment ofpower systems has been made more complicated and the magnitude of the secondharmonic in inrush current has been decreased because of the improvement of caststeel. Therefore, traditional approaches will likely mal-operate in the case ofmagnetizing inrush w...
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ژورنال
عنوان ژورنال: Journal of Computer Science
سال: 2007
ISSN: 1549-3636
DOI: 10.3844/jcssp.2007.894.897