|Table of Contents|

Online detection for bolts of power distribution equipments based onimproved ellipse fitting and nonlinear support vector machine(PDF)

《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年06期
Page:
708-
Research Field:
Publishing date:

Info

Title:
Online detection for bolts of power distribution equipments based onimproved ellipse fitting and nonlinear support vector machine
Author(s):
Ji Liang1; Wu Wei2; Xu Chunshan3; Su Pengfei2; Zhao Wei3
1.Changzhou Power Supply Company,State Grid Jiangsu Electric Power Company,Changzhou 213000,China; 2.School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China; 3.YIJIAHE Technology Co.,Ltd.,Nanjing 210000,China
Keywords:
ellipse fitting;  support vector machine;  power distribution equipments;  bolt detection;  online detection;  least square method;  random sampling principle
PACS:
TP391.4
DOI:
10.14177/j.cnki.32-1397n.2017.41.06.007
Abstract:
A novel ellipse fitting approach based on the least square method and random sampling principle is proposed to detect bolts in complex live working scenes and solve the problems of the effects of illumination,environment and noise on traditional ellipse fitting.A sorting method based on nonlinear support vector machine is proposed to classify bolts from distractors and solve the problem of alike edge of bolts and elliptical distractors.Experimental results show that,the proposed method can detect the bolts effectively and accurately from distractors.

References:

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Last Update: 2017-12-31