基于机器视觉的PCB 光板缺陷检测技术研究

本文将机器视觉技术应用到 PCB 光板的缺陷检测中，实现 PCB 光板的自动 缺陷检测。在研究机器视觉技术的基础上，针对 PCB 光板上的几种常见几何缺 陷类型，制定 PCB 光板缺陷检测系统总体方案，讨论视觉检测系统工作原理， 为 PCB 光板视觉检测系统搭建硬件平台：包括照明系统、图像采集系统、以及 控制台系统；重点针对采集的 PCB 光板图像讨论视觉检测算法并进行仿真实验， 包括图像预处理、分割、描述、数学形态学、模式识别等方法，着重根据 PCB 设计规则运用数学形态学及模式识别方法完成自动检测识别；最后根据视觉检 测算法设计系统软件，对 PCB 光板完成缺陷的检测与识别。
学位论文
题目 英文 题目
基于机器视觉的 PCB 光板缺陷检测技术研究 Research of Machine Vision Based
Defect Detection Techniques on PCB
研究生姓名
胡文娟
姓 名 刘泉 指导教师
单位名称 信息工程学院
职称 教 授 邮 编 430070
申请学位级别 硕士 学科专业名称 通信与信息系统
对包含不同缺陷的 PCB 光板图像进行实验，结果证明本文的 PCB 光板缺陷 检测系统能够对 PCB 光板上的短路、断路、毛刺、缺损四种主要缺陷做出有效 的检测、定位与识别。
关键字：印刷电路板(PCB)；机器视觉；数学形态学；模式识别
I
武汉理工大学硕士学位论文
Abstract
Printed Circuit Board, a kind of information carrier which integrates varieties of electronic devices, has popular applications in electronic fields nowadays. With the rapid development of manufacture techniques, electronic product tends to lighter, thinner and smaller, and PCB turns to have more layers and higher density, which makes quality detection of PCB become more difficult. Traditional detection methods can not satisfy the large production for inaccurate, slow and long time detection, then how to realize automated defect detection of PCB becomes a hot topic in semiconductor industry.
论文提交日期 2007 年 4 月 论文答辩日期 2007 年 5 月
学位授予单位 武汉理工大学 学位授予日期
答辩委员会主席 陈 伟 评阅人
周祖德
李方敏
2007 年 4 月
武汉理工大学硕士学位论文
摘要
印刷电路板(PCB)是集成各种电子元器件的信息载体，在电子领域中有着广 泛的应用。随着技术的不断发展和工艺水平的不断提高，电子产品趋于更轻、 更薄、更小，PCB 朝着层数更多、密度更高的方向发展，这使得 PCB 的质量检 验成为一件非常困难的工作。传统的人工检测方法容易漏检、检测速度慢、检 测时间长，已经不能满足生产的需要，如何更有效的实现 PCB 的自动缺陷检测， 成为半导体工业领域一个热门问题。
机器视觉检测技术，集电子学、光电探测、图像处理和计算机技术于一身， 是精密测试技术领域内最具有发展潜力的新技术。机器视觉系统，一般采用 CCD 或 CMOS 摄像机摄取待检测目标并转化为数字信号，再采用先进的计算机硬件 与软件技术对数字图像信号进行处理，从而得到所需要的各种目标图像特征值， 并由此实现零件识别或缺陷检测等多种功能。然后再根据其结果显示图像，输 出数据，由反馈信息引导执行机构完成位置调整、好坏筛选等自动化流程。将 机器视觉引入到工业检测中，具有非接触、速度快、柔性好等突出优点，在现 代制造业中有着重要的应用前景。
第 2 章 PCB 光板视觉检测系统总体设计································································7 2.1 问题的提出····································································································7 2.2 检测系统工作原理························································································7 2.3 照明系统设计································································································8 2.4 PCB 图像采集系统设计 ················································································9 2.4.1 CCD 摄像机························································································10 2.4.2 图像采集卡························································································12 2.5 控制台设计··································································································13 2.6 本章小结 ·····································································································14
Pattern Recognition
III
武汉理工大学硕士学位论文
目录
第 1 章 绪 论 ···········································································································1 1.1 机器视觉检测技术综述 ················································································1 1.2 PCB 光板视觉检测技术发展状况及分析 ·····················································3 1.3 课题的来源、目的及意义 ············································································5 1.4 本文主要研究内容及组织结构 ····································································6
PCB
基
于
机
器
视 觉
（申请工学硕士学位论文）
的
光
板
缺
陷
检 测 技
基于机器视觉的 PCB 光板缺陷
术
研 究
检测技术研究
胡 文 娟
培 养 单 位 ：信息工程学院
ຫໍສະໝຸດ Baidu
学 科 专 业 ：通信与信息系统
研 究 生 ：胡文娟
武
汉
指 导 教 师 ：刘 泉 教 授
理
工
大
学
2007 年 4 月
分类号 UDC
密级 学校代码 10497
Experimental results demonstrate that though the PCB defect detection system described in this paper, four types of defects including short circuit, open circuit,
II
武汉理工大学硕士学位论文
protuberance and concavity on PCB can be effectively detected, located and recognized. Keywords: Printed Circuit Board(PCB); Machine Vision; Mathematical Morphology;
Machine vision technology, which combines electronics, photoelectric detection, image processing and computer technology into oneself, is a potential new technology in industrial detection field. Machine vision system, usually obtains digital image signals of detected object by CCD or CMOS camera, then processes the digital image signals to get characteristic values by adopting advanced computer hardware and software techniques, and accomplishes workpiece recognition or defect detection accordingly. Based on the results, the system displays the images, exports the data and sends out instructions to control corresponding equipment to act such as location adjusting and quality filtering according to feedback information.
Machine vision technology is applied into automated PCB defect detection in this paper. On the basis of studying machine vision technology, we design the whole scheme of PCB defect detection system towards several simple geometric defects on PCB, discuss the principle of the system, and establish hardware platform for the system, including illuminating unit, image acquisition unit and control unit. Then, we discuss and design the foremost vision detection algorithm towards PCB image, including image pre-processing, segmentation, description, mathematical morphology, and pattern recognition, while the key is to accomplish defect detection using mathematical morphology and pattern recognition based on PCB design rules. Finally, we design system software according to the vision detection algorithm to realize defect detection and recognition on PCB.