[1]纪 良,吴 巍,许春山,等.基于改进椭圆拟合与非线性支持向量机的配电设备螺栓带电检测[J].南京理工大学学报(自然科学版),2017,41(06):708.[doi:10.14177/j.cnki.32-1397n.2017.41.06.007]
 Ji Liang,Wu Wei,Xu Chunshan,et al.Online detection for bolts of power distribution equipments based onimproved ellipse fitting and nonlinear support vector machine[J].Journal of Nanjing University of Science and Technology,2017,41(06):708.[doi:10.14177/j.cnki.32-1397n.2017.41.06.007]
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基于改进椭圆拟合与非线性支持向量机的配电设备螺栓带电检测()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年06期
页码:
708
栏目:
出版日期:
2017-12-31

文章信息/Info

Title:
Online detection for bolts of power distribution equipments based onimproved ellipse fitting and nonlinear support vector machine
文章编号:
1005-9830(2017)06-0708-06
作者:
纪 良1吴 巍2许春山3苏鹏飞2赵 伟3
1.国网江苏省电力公司 常州供电公司,江苏 常州 213000; 2.南京理工大学 自动化学院,江苏 南京 210094; 3.亿嘉和科技股份有限公司,江苏 南京 210000
Author(s):
Ji Liang1Wu Wei2Xu Chunshan3Su Pengfei2Zhao 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
关键词:
椭圆拟合 支持向量机 配电设备 螺栓检测 带电检测 最小二乘法 随机采样原理
Keywords:
ellipse fitting support vector machine power distribution equipments bolt detection online detection least square method random sampling principle
分类号:
TP391.4
DOI:
10.14177/j.cnki.32-1397n.2017.41.06.007
摘要:
为在复杂的带电作业场景中准确地检测出螺栓,针对基于最小二乘法的传统椭圆拟合易受光照、环境和噪声影响的问题,综合利用最小二乘法、随机采样原理进行椭圆拟合。针对螺栓和椭圆形干扰物边缘形状相似的问题,采用基于非线性支持向量机(SVM)的分类方法对螺栓和干扰物进行分类。实验结果表明,该文方法能在存在椭圆形干扰物的情况下准确区分螺栓。
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.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-08-17 修回日期:2017-09-19
基金项目:江苏省重点研发计划项目(BE2017161); 江苏高校优势学科建设工程项目
作者简介:纪良(1980-),男,高级工程师,主要研究方向:带电作业技术,E-mail:jiliang@js.sgcc.com.cn; 通讯作者:吴巍(1992-),男,博士生,主要研究方向:图像处理与机器视觉,E-mail:115110001021@njust.edu.cn。
引文格式:纪良,吴巍,许春山,等.基于改进椭圆拟合与非线性支持向量机的配电设备螺栓带电检测[J].南京理工大学学报,2017,41(6):708-713.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-12-31