摘要
随着工业制造向高精度、高效率方向发展，传统测量手段已难以满足复杂零件的精密检测需求，基于机器视觉的测量技术因其非接触、高效和自动化等优势受到广泛关注。本研究旨在探索一种结合机器视觉与误差补偿技术的精密测量方法，以提高测量精度和可靠性。研究首先构建了基于多摄像头协同工作的机器视觉测量系统，通过优化标定算法和图像处理技术，实现了对复杂几何特征零件的高精度三维重建。其次，针对系统固有误差和环境因素引起的偏差，提出了一种自适应误差补偿模型，该模型融合了神经网络预测与卡尔曼滤波算法，能够动态调整测量结果，显著降低系统误差。实验结果表明，所提出的测量与补偿方案在多种工况下均表现出优异的稳定性和精确性，测量精度较传统方法提升约30%。此外，本研究还开发了一套集成化软件平台，便于实际工程应用中的操作与维护。总体而言，本研究不仅为精密测量领域提供了新的技术路径，还为复杂零件的质量控制和智能制造奠定了重要基础，其创新点在于将视觉测量与智能补偿有机结合，有效解决了传统方法中精度不足的问题，具有较高的理论价值和应用前景。
关键词：机器视觉测量；误差补偿；精密测量；自适应模型；三维重建
Abstract
With the development of industrial manufacturing towards higher precision and efficiency, traditional measurement methods are increasingly unable to meet the demands of precise inspection for complex parts. Machine vision-based measurement technology has garnered significant attention due to its non-contact, efficient, and automated advantages. This study aims to explore a precision measurement method that integrates machine vision with error compensation techniques to enhance measurement accuracy and reliability. Initially, a machine vision measurement system based on multi-camera collaboration was constructed, and by optimizing calibration algorithms and image processing technologies, high-precision 3D reconstruction of parts with complex geometric features was achieved. Subsequently, an adaptive error compensation model was proposed to address deviations caused by inherent system errors and environmental factors. This model combines neural network prediction with Kalman filtering algorithms, enabling dynamic adjustment of measurement results and significantly reducing system errors. Experimental results indicate that the proposed measurement and compensation scheme demonstrates excellent stability and accuracy under various working conditions, with a measurement precision improvement of approximately 30% compared to traditional methods. Furthermore, an integrated software platform was developed in this study to facilitate operation and maintenance in practical engineering applications. Overall, this research not only provides a new technical approach for the field of precision measurement but also lays an important foundation for quality control of complex parts and smart manufacturing. Its innovation lies in the effective combination of visual measurement and intelligent compensation, successfully addressing the issue of insufficient accuracy in traditional methods and exhibiting substantial theoretical value and application potential.
Keywords：Machine Vision Measurement; Error Compensation; Precision Measurement; Adaptive Model; Three-Dimensional Reconstruction
目 录
摘要 I
Abstract II
一、绪论 1
(一) 研究背景与意义 1
(二) 国内外研究现状分析 1
(三) 本文研究方法概述 2
二、机器视觉测量原理与关键技术 2
(一) 机器视觉测量的基本原理 2
(二) 关键技术及其实现方法 3
(三) 测量系统误差来源分析 3
三、零件精密测量方法研究 4
(一) 高精度图像采集技术 4
(二) 特征点提取与匹配算法 4
(三) 数据处理与结果优化 5
四、误差补偿技术研究与应用 5
(一) 误差补偿理论基础 6
(二) 补偿模型的构建与验证 6
(三) 实验结果与性能评估 7
结 论 8
参考文献 9
