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Sovan Dalai

Researcher at Jadavpur University

Publications -  99
Citations -  822

Sovan Dalai is an academic researcher from Jadavpur University. The author has contributed to research in topics: Dielectric & Insulator (electricity). The author has an hindex of 12, co-authored 77 publications receiving 472 citations. Previous affiliations of Sovan Dalai include Techno India University.

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A method for the localization of partial discharge sources using partial discharge pulse information from acoustic emissions

TL;DR: In this paper, an approach for the estimation of partial discharge (PD) is presented based on the source-filter model of acoustic theory, which extracts an estimation of the excitation source (PD pulse) by isolating it from the acoustic response of the tank-oil system.
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A deep learning framework using convolution neural network for classification of impulse fault patterns in transformers with increased accuracy

TL;DR: The paper presents a method using deep learning framework based on convolution neural network, for identification and localization of faults of transformer winding under impulse test, and shows that the proposed method outperforms the existing methods significantly.
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Rough-Set-Based Feature Selection and Classification for Power Quality Sensing Device Employing Correlation Techniques

TL;DR: A stand-alone module, employing microcontroller-based embedded system, is devised for efficiently sensing power quality disturbances in real time for in situ applications and shows that the accuracy of the proposed scheme is comparable to that obtained in offline analysis using a computer.
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Diagnosis of Power Quality Events Based on Detrended Fluctuation Analysis

TL;DR: Implementation of the proposed technique shows the effectiveness in differentiating PQ events distinctly without much involving conventional analytical tools that result in minimum computational burden as compared to the existing methods.
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Wavelet Kernel-Based Convolutional Neural Network for Localization of Partial Discharge Sources Within a Power Apparatus

TL;DR: A new convolutional neural network (CNN) topology using wavelet kernels to detect and discriminate single or multiple partial discharge locations in high voltage power apparatus with increased accuracy is presented.