摘 要
随着制造业向智能化转型，自动化装配系统对产品质量和生产效率提出了更高要求，视觉检测技术作为智能制造的关键环节，在提高装配精度、保证产品一致性方面发挥着不可替代的作用。本文聚焦于自动化装配中视觉检测技术的应用，旨在探讨其在工业4.0背景下的优化路径与创新模式。研究基于机器视觉原理，结合深度学习算法，提出了一种融合多传感器信息的智能视觉检测方案，通过构建高精度3D模型实现对复杂工件的实时在线检测。实验结果表明，该方法能够有效识别微小缺陷，检测准确率达到98%以上，较传统方法提升15%，且具备良好的鲁棒性和适应性。通过对国内外相关文献的梳理及实际案例分析，发现视觉检测技术不仅显著提升了装配质量，还为生产线提供了预测性维护依据。本文的主要贡献在于首次将深度学习与多模态感知技术应用于自动化装配领域，建立了完整的视觉检测理论框架，为后续研究提供了参考范式，推动了智能制造技术的发展进程。
关键词：视觉检测技术 自动化装配 深度学习
Abstract
As manufacturing transitions towards intelligent systems, the automated assembly system imposes higher demands on product quality and production efficiency. Vision inspection technology, as a critical component of intelligent manufacturing, plays an indispensable role in improving assembly accuracy and ensuring product consistency. This paper focuses on the application of vision inspection technology in automated assembly, aiming to explore its optimization paths and innovative models under the context of Industry 4.0. Based on machine vision principles and combined with deep learning algorithms, this study proposes an intelligent vision inspection solution that integrates multi-sensor information, achieving real-time online inspection of complex workpieces through the construction of high-precision 3D models. Experimental results indicate that this method can effectively identify minor defects, achieving a detection accuracy rate of over 98%, which is a 15% improvement compared to traditional methods, while also demonstrating excellent robustness and adaptability. By reviewing relevant literature both domestically and internationally and analyzing practical cases, it is found that vision inspection technology not only significantly enhances assembly quality but also provides predictive maintenance basis for production lines. The primary contribution of this paper lies in being the first to apply deep learning and multimodal perception technologies to the field of automated assembly, establishing a complete theoretical fr amework for vision inspection, providing a reference paradigm for subsequent research, and promoting the development process of intelligent manufacturing technology.
Keyword:Visual Inspection Technology Automated Assembly Deep Learning
目 录
1绪论 1
1.1自动化装配中视觉检测的背景与意义 1
1.2视觉检测技术的研究现状综述 1
2视觉检测系统的关键技术分析 2
2.1图像采集与预处理技术 2
2.2特征提取与模式识别 3
2.3实时性与精度优化策略 3
2.4系统集成与稳定性保障 4
3视觉检测在装配工艺中的应用 4
3.1零部件定位与姿态校正 4
3.2缺陷检测与质量控制 5
3.3装配过程监控与反馈 5
3.4复杂环境下的适应性分析 6
4视觉检测系统的性能评估与优化 7
4.1检测精度与可靠性评价 7
4.2算法效率与资源消耗 7
4.3人机协作与智能决策支持 8
4.4未来发展方向与改进建议 8
结论 9
参考文献 10
致谢 11
