首页 | 本学科首页   官方微博 | 高级检索  
     检索      

线束端子压接后外观缺陷的视觉检测算法研究
引用本文:袁彬淦,钟铭恩,倪晶鑫.线束端子压接后外观缺陷的视觉检测算法研究[J].系统仿真学报,2022,34(5):1152-1159.
作者姓名:袁彬淦  钟铭恩  倪晶鑫
作者单位:厦门理工学院 福建省客车先进设计与制造重点实验室,福建  厦门  361024
基金项目:国家自然科学基金(51978592);福建省自然科学基金(2019J01859);厦门市科技计划(3502Z20183065)
摘    要:针对线束端子的缺陷检测效率低、漏检率高等问题,提出一种基于机器视觉的图像检测方法:分析线束端子3个主要部位的5种典型缺陷模式,并定义了缺陷评价参数;设计了定位基准拟合算法、待检部位自适应分割算法和缺陷特征参数计算方法;给出了各类外观缺陷的判断准则。实验结果表明,检测算法适用于各单类多类混合缺陷模式,综合漏检率和误检率较低,准确率和实时性较高,能够满足实际应用要求。

关 键 词:机器视觉  图像处理  线束  图像分割  缺陷检测  
收稿时间:2020-12-08

Research on Visual Inspection Algorithm of Crimping Appearance Defects for Wiring Harness Terminals
Bingan Yuan,Mingen Zhong,Jingxin Ni.Research on Visual Inspection Algorithm of Crimping Appearance Defects for Wiring Harness Terminals[J].Journal of System Simulation,2022,34(5):1152-1159.
Authors:Bingan Yuan  Mingen Zhong  Jingxin Ni
Institution:Fujian Key Laboratory of Bus Advanced Design and Manufacturing, Xia Men University of Technology, Xiamen 361024, China
Abstract:Aiming at the low efficiency and high missing rate of wiring harness terminals, an image detection method based on machine vision is proposed. The characteristic parameters of five typical defects in three main parts of wiring harness terminals are analyzed and defined. Tthe algorithms of extracting positioning datum, segmenting inspected-parts adaptively, extracting the defect features and calculating the characteristic parameters are designed respectively, and the defects criterions are given. The experimental results show that the algorithms are suitable for single defect and multi-class defects, both the miss detection rate and the false positiveness rate are low. The accuracy and real-time performance are high, and can meet the practical application requirements.
Keywords:machine vision  image processing  wire harness  image segmentation  defect detection  
点击此处可从《系统仿真学报》浏览原始摘要信息
点击此处可从《系统仿真学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号