NDLI: An Evaluation of Alternative Techniques for Monitoring Insulator Pollution

Content Provider	IEEE Xplore Digital Library
Author	de Barros Bezerra, J.M. Lima, A.M.N. Deep, G.S. da Costa, E.G.
Copyright Year	1986
Abstract	Electrical utility companies are constantly seeking predictive techniques that indicate the appropriate moment for maintenance intervention, while aiming toward a continuous increase in service indices. This paper proposes the use of pattern-recognition techniques to build classifiers that diagnose the operational state of the insulation structure in an online application. Important results were achieved during the study, mainly related to the types of sensors and features that need to be applied during the diagnosis process. Ultrasound and current leakage sensors, very-high frequency antenna, and thermovision instruments were employed to acquire signals and images in order to construct recognition systems. A number of specific features were applied to verify their importance during the classification process. Features were obtained in the time, frequency, and wavelet domains. Two groups of pattern-recognition techniques were applied: linear (Fisher and Karhunen-Loeve) and nonlinear (artificial neural network). The results indicated that pollution deposit can be evaluated by the proposed techniques, especially when a combination of sensors is employed.
Sponsorship	IEEE Power Engineering Society
Starting Page	1773
Ending Page	1780
Page Count	8
File Size	1872542
File Format	PDF
ISSN	08858977
Volume Number	24
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monitoring Insulation Pollution Sensor phenomena and characterization Ultrasonic imaging Image sensors Sensor systems Thermal sensors Frequency Instruments pollution measurement High-voltage techniques pattern recognition
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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