NDLI: An expert system approach for transformer insulation diagnosis combining conventional diagnostic tests and PDC, RVM data

Content Provider	IEEE Xplore Digital Library
Author	Sarkar, S. Sharma, T. Baral, A. Chatterjee, B. Dey, D. Chakravorti, S.
Copyright Year	1994
Abstract	Search for a reliable and efficient insulation diagnostic tool has always been the interest of power utilities. Today a large number of methods are available that can be used for insulation condition monitoring. These methods include both traditional and newer techniques. However due to complex aging process of oil paper insulation under the influence of different types of stresses, insulation condition assessment is generally performed by experts after carefully evaluating different measurement data. Furthermore, measurement data are influenced by various factors (like conductive aging byproducts, furanic compounds, paper and oil-moisture) in addition to measurement error (if any). This makes prediction of insulation condition based on single type of measurement rather difficult. This paper presents an Expert System designed to perform insulation diagnosis. The Expert System considers measurement data obtained using both traditional and newer techniques in order to come to a definitive conclusion. The Expert System extracts insulation condition sensitive information from data obtained using different techniques and then uses these to devise an optimized insulation model. This optimized model is used to predict paper-moisture content and other insulation condition sensitive parameters. Since these values are predicted using optimized model, they are not dependent on a single type of measurement and hence are less likely to be affected by error of any specific measurement. The performance of the developed Expert System is first tested on a laboratory sample and then on several real life power transformers belonging to NTPC Ltd.
Sponsorship	National Natural Science Foundation of China (NSFC) Region Centre Ville de Tours Conseil General D'Indre et Loire ABB IEEE Sandia National Laboratories TOSHIBA
Starting Page	882
Ending Page	891
Page Count	10
File Size	1324319
File Format	PDF
ISSN	10709878
Volume Number	21
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temperature measurement Moisture Mathematical model Power transformer insulation Oil insulation Dielectric measurement paper moisture content Insulation diagnosis polarization current depolarization current return voltage measurement (RVM) central time constant (CTC) expert system (ES) tan delta oil moisture content
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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