Detection of Partial Discharge Sources using Acoustic Sensor
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Significant Aspects of the book: In majority of the literature, multiple or more than one partial discharge sources are not considered. But, it is reported that multiple partial discharges occur at the same period of time in many PD cases. In most of the research works emphasis is not given on identification of multiple PD sources within the insulation system. In this book this gap has been bridged by identification and discrimination of multiple PD sources with reasonably good accuracy. To the best of knowledge of the author, the following are original contributions of the book: a) PD source ...
Significant Aspects of the book: In majority of the literature, multiple or more than one partial discharge sources are not considered. But, it is reported that multiple partial discharges occur at the same period of time in many PD cases. In most of the research works emphasis is not given on identification of multiple PD sources within the insulation system. In this book this gap has been bridged by identification and discrimination of multiple PD sources with reasonably good accuracy. To the best of knowledge of the author, the following are original contributions of the book: a) PD source identification has been done within the emulated real life power transformer in laboratory environment. b) Discrimination of single as well as multiple PD signals within the emulated transformer from "Multi sensor system". c) Development of a cross-wavelet transform (XWT) aided ensemble binary support vector machine (EB-SVM) based scheme for discrimination or localization of individual and multiple PD sources inside the emulated transformer using acoustic sensor.
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