摘 要
本研究针对机械制造过程中质量检测的需求，提出了一种基于机器视觉的质量检测方法。随着机器视觉技术的快速发展，其在工业自动化领域的应用日益广泛，本研究旨在通过机器视觉技术提升机械制造过程中的质量检测效率和准确性。研究方法上，我们采用了先进的图像处理算法和深度学习模型，对机械制造产品进行自动识别和缺陷检测。实验结果显示，该方法能够高效准确地识别出产品表面的缺陷，如裂纹、凹陷等，并实时反馈检测结果。相较于传统的人工检测方式，本研究提出的方法不仅提高了检测效率，还大大降低了漏检和误检率。
关键词：机器视觉质量检测；深度学习；机械制造
Abstract
In this paper, a quality inspection method based on machine vision is proposed to meet the requirement of quality inspection in machinery manufacturing. With the rapid development of machine vision technology, its application in the field of industrial automation is becoming more and more extensive. This study aims to improve the efficiency and accuracy of quality inspection in the machinery manufacturing process through machine vision technology. In terms of research methods, we use advanced image processing algorithms and deep learning models for automatic identification and defect detection of mechanical manufacturing products. The experimental results show that the method can identify the defects of the product surface efficiently and accurately, such as cracks, depressions, etc., and feedback the detection results in real time. Compared with the traditional manual detection method, the proposed method not only improves the detection efficiency, but also greatly reduces the rate of missed detection and false detection.
Key Words: Machine vision quality inspection; Deep learning; Machine building
目 录
第一章 绪 论 1
1.1 研究背景和意义 1
1.2 机器视觉在质量检测领域的应用现状 1
第二章 机器视觉技术基础 3
2.1 机器视觉原理简介 3
2.2 机器视觉系统组成 3
2.3 机器视觉在质量检测中的优势 4
2.4 机器视觉技术的发展趋势 5
第三章 机械制造质量检测方法与实现 6
3.1 传统质量检测方法与局限性 6
3.2 基于机器视觉的质量检测系统设计 6
3.3 图像采集与处理流程 7
第四章 实验验证与结果分析 8
4.1 实验平台搭建与数据采集 8
4.2 实验方法与步骤 8
4.3 实验结果与分析 9
结论 10
致 谢 11
参考文献 12
