NDLI: Fiber detecting of high voltage insulator contamination grades based on PSO-SVM

Content Provider	IEEE Xplore Digital Library
Author	Qing Zhang Shangbin Jiao Guo Xie
Copyright Year	2008
Description	Author affiliation: Dept. of Autom. & Inf. Eng., Xian Univ. of Technol., Xian (Qing Zhang; Shangbin Jiao; Guo Xie)
Abstract	A novel method that integrates fiber technology with support vector machine classifiers to detect the contamination grades of high voltage insulators is presented i n this paper. Based on laboratory simulation experiments of the contaminated silex sensor and insulator, under condition of the complicated nonlinear relationship between the luminous flux attenuation, the contamination grades of insulator, the environment humidity and ash density, the least squares support vector machine (LSSVM) pattern recognition model of detection of the contamination grades is constructed by means of particle swarm optimization (PSO) arithmetic to optimize the parameters of the model. The method takes advantages of the minimum structure risk of SVM and the quickly globally optimizing ability of particle swarm, and the mapping relation between the luminous flux attenuation, the environment humidity, ash density and contamination grades is built quickly by learning from sample data. Then the contamination grade of insulator online detecting system is developed based on the fiber technology. And the application effect proved the feasibility of the method.
Starting Page	774
Ending Page	777
File Size	485729
Page Count	4
File Format	PDF
ISBN	9781424438266
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	IEEE Consumer Electronics Society(CES)
Subject Keyword	Voltage Insulation Contamination Support vector machines Optical fiber sensors Attenuation Humidity Ash Particle swarm optimization Support vector machine classification
Content Type	Text
Resource Type	Article

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