摘要
随着工业自动化和智能制造技术的快速发展，零件尺寸精密测量已成为产品质量控制中的关键环节。传统接触式测量方法存在效率低、易损伤零件表面等问题，难以满足现代工业对高精度、非接触测量的需求。为此，本文设计并实现了一种基于机器视觉的零件尺寸精密测量系统，旨在通过非接触方式实现对复杂零件尺寸的高效、精确测量。该系统采用高分辨率工业相机获取零件图像，并结合图像预处理、边缘检测和亚像素定位算法提取目标特征点坐标，进而计算零件的关键尺寸参数。为提高测量精度，系统引入了镜头畸变校正模型和标定板辅助标定技术，有效补偿了光学成像误差。实验结果表明，该系统在测量范围内的精度可达微米级，且具有良好的稳定性和重复性。与传统测量方法相比，本研究提出的系统显著提升了测量效率，同时避免了接触式测量可能带来的零件损伤问题。此外，系统还具备灵活的扩展性，可适应多种零件类型和测量场景。本文的主要创新点在于将机器视觉技术与精密测量理论深度融合，提出了一种适用于复杂工业环境的高效测量解决方案，为智能制造领域的质量检测提供了新的技术路径。
关键词：机器视觉测量；非接触式测量；零件尺寸精密测量；亚像素定位；镜头畸变校正
Abstract
With the rapid development of industrial automation and smart manufacturing technologies, precise dimensional measurement of parts has become a critical component in quality control. Traditional contact-based measurement methods suffer from low efficiency and potential damage to part surfaces, making them inadequate for modern industrial demands of high-precision, non-contact measurements. To address these challenges, this paper designs and implements a machine vision-based system for precise dimensional measurement of parts, aiming to achieve efficient and accurate measurement of complex parts through non-contact means. The system employs high-resolution industrial cameras to capture part images and integrates image preprocessing, edge detection, and sub-pixel positioning algorithms to extract coordinates of target feature points, thereby calculating key dimensional parameters of the parts. To enhance measurement accuracy, the system incorporates a lens distortion correction model and calibration board-assisted calibration techniques, effectively compensating for optical imaging errors. Experimental results demonstrate that the system achieves micron-level accuracy within its measurement range, exhibiting excellent stability and repeatability. Compared with traditional measurement methods, the proposed system significantly improves measurement efficiency while avoiding potential part damage associated with contact-based measurements. Additionally, the system offers flexible scalability, accommodating various part types and measurement scenarios. The primary innovation of this study lies in the deep integration of machine vision technology with precision measurement theory, proposing an efficient measurement solution suitable for complex industrial environments and providing a new technical approach for quality inspection in the field of smart manufacturing.
Keywords：Machine Vision Measurement; Non-Contact Measurement; Precision Measurement Of Part Dimensions; Sub-Pixel Localization; Lens Distortion Correction
目 录
摘要 I
Abstract II
引言 1
一、系统需求分析与总体设计 1
(一) 零件尺寸测量需求分析 1
(二) 机器视觉技术选型 2
(三) 系统总体架构设计 2
二、图像采集与预处理 3
(一) 图像采集设备选型 3
(二) 图像预处理方法研究 4
(三) 图像质量评估与优化 4
三、尺寸测量算法设计 5
(一) 边缘检测算法研究 5
(二) 特征点提取与匹配 5
(三) 尺寸计算模型建立 6
四、系统集成与性能测试 7
(一) 系统硬件集成方案 7
(二) 测量精度验证实验 7
(三) 系统稳定性测试分析 8
结 论 9
参考文献 10
