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Arijit Baral

As seen in: IET Science, Measurement & Technology
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Articles

IET Digital Library: A Neural Network based methodology to study Effects of Oil Properties on Induction Period Evaluated from Response of Oil-Paper Insulation Employing mineral oil, ester and mixture

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By Saurabh Dutta, Arijit Baral, Chandra Banerjee, Biswendu Chatterjee
| The IET Digital Library
Home > Journals & magazines > IET Science, Measurement & Technology > E-First > Article A Neural Network based methodology to study Effects of Oil Properties on Induction Period Evaluated from Response of Oil-Paper Insulation Employing mineral oil, ester and mixture Recommend Title Publication to library You must fill out fields marked with: * Librarian details Your details Why are you recommending this title?
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IET Science, Measurement & Technology

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By deepak mishra, Arijit Baral, Sivaji Chakravorti, Nasirul Haque
| IET Science, Measurement & Technology Verified
SO is a symbolic gas that can indicate the insulation status of SF insulation electrical equipment. Its accurate quantitative measurement is of the great significance for the judgement of the type and severity of faults inside the insulation equipment. For this reason, a detection system of trace SO based on ultraviolet (UV) spectrometry was presented.
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Estimation of Paper-Moisture in Transformer Insulation Employing Dielectric Spectroscopy Data

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By Alok Prasanna Kumar, Hari Charan Verma, Arijit Baral, Arpan Pradhan
| The IET Digital Library
Estimation of Paper-Moisture in Transformer Insulation Employing Dielectric Spectroscopy Data Estimation of Paper-Moisture in Transformer Insulation Employing Dielectric Spectroscopy Data For access to this article, please select a purchase option: <?xml version="1.0" encoding="UTF-8"?><EVENT><EVENTLOG><PORTALID>iet</PORTALID><SESSIONID>4i6l1srqlk67s.x-iet-live-01</SESSIONID><USERAGENT>Mozilla/5.0 (compatible; MuckRack/1.0;...
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