NDLI: Leak detection for self-contained fluid-filled cables using regression analysis

Content Provider	IEEE Xplore Digital Library
Author	Hao, L. Lewin, P.L. Swingler, S.G. Bradley, C.
Copyright Year	2010
Description	Author affiliation: National Grid, Warwick, UK (Bradley, C.) \|\| The Tony Davies High Voltage Laboratory, School of Electronics and Computer Science, University of Southampton, UK (Hao, L.; Lewin, P.L.; Swingler, S.G.)
Abstract	This paper investigates the methodology of the machine learning technique, namely the Support Vector Machine to assess the condition of fluid-filled high voltage cables based on thermal, pressure and load current information. Field data from a healthy circuit containing pressure, temperature and load current information have been obtained. The data structure has been investigated and a feasible algorithm to restructure the data for further analysis is proposed. The post-processing technique using Support Vector Machine Regression to predict oil pressure in the system is demonstrated. Results obtained using the regression analysis in this paper are very promising. Based on this method, an expert system could give early warning with better sensitivity than the existing system for the cable circuit and implementation of this approach can be achieved without taking the circuit out of service.
Starting Page	1
Ending Page	5
File Size	768983
Page Count	5
File Format	PDF
ISBN	9781424462988
ISSN	1089084X
e-ISBN	9781424463015
DOI	10.1109/ELINSL.2010.5549818
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Leak detection Cables Regression analysis Circuits Support vector machines Machine learning Voltage Thermal loading Temperature Data structures data mining fluid filled cable oil leak detection support vector machine regression analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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