计算机研究-基于计算机视觉的机械零部件检测系统.pdf资源-CSDN文库

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摘要

计算机视觉检测技术是计算机技术、光电信息技术、智能技术相结合的产物。计算

机视觉检测技术具有快速、非接触、柔性、智能和不受生理限制等优点。它是实现大

规模工业生产、极端环境下替代手工进行高速高精度产品检测的最优手段之一，被广

泛应用于各行业的现场监控、产品品质检测中。传统的机械零部件检测技术往往效率

低下，可靠性不高，速度慢，信息集成不方便。手工检测严重依赖个人的专业技能、

从业经验，不具有可复制性，再加上生理上的不可持续性，会导致产品检测中过程的

不稳定。最后还有及时有效地将检测数据进行集成都是催生计算机视觉零部件检测的

重要动机。

计算机视觉检测是建立从计算机视觉信息到产品属性信息间相映射的过程。从检测

性质和检测范围的角度来看，计算机视觉检测可以分为定量检测和定性检测两大类。

检测对象的尺寸信息是定量检测中最常见的一项检测内容，通过分析检测图像的特征

点，拟合线、面，从而提取产品尺寸参数。定量检测适用于属性为数量标志的检测，

定性检测适用于属性为品质标志的检测。计算机视觉检测在属性标志值的分类比较模

糊或分类需求不甚明确的情况下尤能体现它的优势，甚至能完成人类都无法完成的任

务。本文的主要工作内容有两部分：机械零部件的几何尺寸精确检测和工艺品质的分

类。

本文建立了一个基于计算机视觉的机械零部件检测模型，该模型综合运用了光学背

景的营造、金属表面发光处理、摄像机标定、双目立体成像、特征边缘轮廓提取和曲

面拟合，最后还有内孔径参数的计算等技术。固定座是汽车换挡机构中的一个重要零

件，该零件有一内孔径参数：空心圆柱轴心和空心圆锥轴心间的夹角。对该夹角的常

规检测方法或工作效率低下或测量精确度不够。利用本文构建的检测模型取得了较好

的研究预期。

本文的另一项工作是建立了利用图像分类技术进行工艺品质检测的模型。该模型包

含的技术有兴趣点的检测、兴趣点的描述、视觉词典的生成、工艺品质的模式识别等

内容。焊接工艺的品质分类是机械零部件加工工艺中重要的工作，焊接面的多变性决

定了焊接工艺品质分类的难度，运用计算机视觉进行定性检测可以在一定程度上提高

检测的效率和精度。

关键词：计算机视觉检测；尺寸检测；亚像素；工序检测；集成学习

Abstract

Computer vision inspection technology is the combination of computer technology,

optical information technology, AI technology. Computer vision inspection has the

advantages of non-contact, flexible, intelligent, and not subject to physical limitations. It is

the optimal means to achieve high-speed and high-precision product inspection on assemble

line or in extreme environments, which is widely used in various industries on-site

monitoring or product quality inspection.

The traditional mechanical parts inspection tool includes inspection ruler, inspection

tooling set, 3D coordinate machine, all these tools are often flexible not enough for the

reason of cost or design flaws. The more serious is that there is some inconsistent between

design space and test space. The whole process of traditional inspection tools is under

controlled by man. In a typical labor-intensive and capital-intensive machinery

manufacturing enterprises, inspection personnel, which often accounted for 20% or more for

whole one. And manual inspection deeply depends on the individual's professional skills,

experience, and is not replicable, coupled with the physical sustainability which often leads

to instability during the inspection. Finally, another motivation is to solve the difficulties in

order to integrate inspection information on CIMS.

Computer vision inspection is the mapping process from visual information to the

product quality attributes. From the view of content and scope, computer vision inspection

can be divided into two parts: quantitative measurement and qualitative check. Dimensions

size measurement is the top content by analyzing the image feature points, fitting a regular

line, surface, extract the dimensions information in quantitative measurement. Quantitative

measurement is suitable for number properties while qualitative check for quality label.

Computer vision inspection can be greatly shown to its advantage in the classification of

fuzzy attribute label or classification task is not clear. The main works are enumerated as

followed: the accurate 3D parameter size value and process quality label check.

In this paper, a mechanical parts measurement system are designed based on computer

vision detection model, which integrated illumination, camera calibration, binocular stereo

imaging, edge contour extraction and surface fitting, and finally to the inner hole parameter.

The holder is an important part of the auto transmission, of which the angle between an axis

of hole cylindrical and another axis of hole conical to be measurement. Traditional

measurements tools are often inefficient or insufficient accuracy. The system in this paper

achieved the expected results.

Another work is to establish process quality check system learned from image

摘要 ........................................................................................................................................................................ I

关键词 ............................................................................................................................................................ I

Abstract ................................................................................................................................................................. II

Key Words ................................................................................................................................................... III

目录 ..................................................................................................................................................................... IV

第一章绪论 ......................................................................................................................................................... 1

1.1 计算机视觉基本理论 ............................................................................................................................ 1

1.2 计算机视觉检测基本理论 .................................................................................................................... 2

1.3 计算机视觉检测技术现状与发展趋势................................................................................................. 3

1.3.1 计算机视觉检测技术产业应用综述 .......................................................................................... 3

1.3.2 计算机视觉检测技术的发展趋势 .............................................................................................. 5

1.4 本课题研究的内容 ................................................................................................................................ 6

第二章计算机视觉检测硬件构成与理论基础................................................................................................ 8

2.1 数字图像测量系统的构成及其测量原理 ............................................................................................. 8

2.2 光照系统 ................................................................................................................................................. 8

2.2.1 LED 光源属性 .............................................................................................................................. 8

2.2.2 光源照射方向 ............................................................................................................................. 9

2.2.3 光源的优化 ................................................................................................................................ 12

2.3 CCD 摄像机 .......................................................................................................................................... 13

2.4 镜头 ....................................................................................................................................................... 13

2.5 图像采集卡 ........................................................................................................................................... 14

2.6 集成学习方法 ...................................................................................................................................... 14

2.6.1 集成学习概念 ............................................................................................................................ 14

2.6.2 集成学习性能提高的原因........................................................................................................ 15

2.6.3 集成学习的应用 ....................................................................................................................... 16

2.7 本章小结 .............................................................................................................................................. 17

第三章机械零部件的空间参数精密测量 ..................................................................................................... 18

3.1 测量对象 ............................................................................................................................................... 18

3.2 测量装置 .............................................................................................................................................. 19

3.2.1 测量硬件 .................................................................................................................................... 19

3.2.2 表面反光处理 ........................................................................................................................... 20

3.2.3 软件系统开发集成 ................................................................................................................... 22

3.2.4 VC++ 6.0 与 Halcon 9.0 软件界面整合 .................................................................................... 24

3.2.5 VC++ 6.0 与 Matlab 2009b 软件界面整合 ............................................................................... 24

3.3 摄像机标定 .......................................................................................................................................... 25

3.3.1 摄像机标定的分类 ................................................................................................................... 25

3.3.2 摄像机的标定原理 ................................................................................................................... 26

3.3.3 本系统的标定实现 ................................................................................................................... 28

3.4 固定座的尺寸精密测量 ...................................................................................................................... 30

3.4.1 基于立体视觉的三维零件重建原理 ......................................................................................... 30

3.4.2 边缘轮廓检测方法 .................................................................................................................... 31

3.4.3 边缘特征点的提取 ................................................................................................................... 33

3.4.4 对应特殊点匹配 ....................................................................................................................... 35

3.4.5 孔径参数确定 ............................................................................................................................ 35

3.5 本章小结 .............................................................................................................................................. 36

第四章零件的自动识别与分类 ..................................................................................................................... 37

4.1 模式识别技术 ....................................................................................................................................... 37

4.1.1 模式识别原理 ............................................................................................................................ 37

4.1.2 模式识别的应用 ....................................................................................................................... 37

4.2 Bag-of-words 模型 ................................................................................................................................ 38

4.2.2 兴趣点检测 ............................................................................................................................... 40

4.2.3 描述子 ....................................................................................................................................... 42

4.2.4 Bag-of-words 产生视觉词汇本 ................................................................................................. 43

4.2.5 Bag-of-words 模型的分类 ......................................................................................................... 44

4.3 基于聚类集成的模式识别技术 .......................................................................................................... 44

4.4 工序品质图像的自动识别与分类实现 .............................................................................................. 45

4.4.1 视觉词汇本构造方法 ................................................................................................................ 45

4.4.2 实验过程 ................................................................................................................................... 47

4.4.3 实验结果分析 ........................................................................................................................... 48

4.5 本章小结 .............................................................................................................................................. 51

第五章总结与展望 ........................................................................................................................................... 52

5.1 全文工作总结 ...................................................................................................................................... 52

5.2 展望 ...................................................................................................................................................... 53

参考文献 ............................................................................................................................................................. 54

致谢 ..................................................................................................................................................................... 57