智能制造中机器视觉技术的应用与优化
摘 要
随着制造业向智能化转型，机器视觉技术作为智能制造系统的关键组成部分，发挥着不可替代的作用。本研究聚焦于机器视觉技术在智能制造中的应用与优化，旨在深入探讨其在提高生产效率、产品质量及实现智能决策方面的潜力。通过对国内外相关文献的系统梳理，结合实际工业应用场景，采用理论分析与实证研究相结合的方法，重点研究了机器视觉技术在缺陷检测、产品装配、机器人引导等环节的应用效果，并针对现有技术局限性提出基于深度学习的优化方案。研究结果表明，优化后的机器视觉系统能够显著提升检测精度和速度，降低误检率，在复杂环境下仍能保持稳定性能。特别是在微小缺陷识别和多视角目标定位方面取得突破性进展，为解决传统方法难以应对的问题提供了新思路。
关键词：机器视觉技术 智能制造 缺陷检测
Abstract
With the transformation of the manufacturing industry to intelligence, machine vision technology, as a key part of the intelligent manufacturing system, plays an irreplaceable role. This study focuses on the application and optimization of machine vision technology in intelligent manufacturing, and aims to deeply explore its potential in improving production efficiency, product quality and realizing intelligent decision-making. Through the system of relevant literature at home and abroad, combined with the actual industrial application scenario, using the combination of theoretical analysis and empirical research method, focusing on the machine vision technology in defect detection, product assembly, robot guide application effect, and in view of the existing technology limitations are put forward based on deep learning optimization scheme. The results show that the optimized machine vision system can significantly improve the detection accuracy and speed, reduce the rate of false detection, and maintain stable performance in complex environment. In particular, the breakthrough has been made in small defect identification and multi-perspective target positioning, which provides new ideas for solving the problems that are difficult to solve with traditional methods.
Keyword:Machine Vision Technology Intelligent Manufacturing Defect Detection
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法与技术路线 1
2机器视觉在智能制造中的应用领域 2
2.1质量检测中的应用 2
2.2智能装配中的应用 3
2.3物流分拣中的应用 3
3机器视觉技术的关键要素分析 4
3.1图像采集技术优化 4
3.2图像处理算法改进 4
3.3视觉系统集成方案 5
4机器视觉系统的性能提升策略 5
4.1精度提升方法研究 6
4.2实时性优化措施 6
4.3系统稳定性保障 7
结论 7
参考文献 9
致谢 10
摘 要
随着制造业向智能化转型，机器视觉技术作为智能制造系统的关键组成部分，发挥着不可替代的作用。本研究聚焦于机器视觉技术在智能制造中的应用与优化，旨在深入探讨其在提高生产效率、产品质量及实现智能决策方面的潜力。通过对国内外相关文献的系统梳理，结合实际工业应用场景，采用理论分析与实证研究相结合的方法，重点研究了机器视觉技术在缺陷检测、产品装配、机器人引导等环节的应用效果，并针对现有技术局限性提出基于深度学习的优化方案。研究结果表明，优化后的机器视觉系统能够显著提升检测精度和速度，降低误检率，在复杂环境下仍能保持稳定性能。特别是在微小缺陷识别和多视角目标定位方面取得突破性进展，为解决传统方法难以应对的问题提供了新思路。
关键词：机器视觉技术 智能制造 缺陷检测
Abstract
With the transformation of the manufacturing industry to intelligence, machine vision technology, as a key part of the intelligent manufacturing system, plays an irreplaceable role. This study focuses on the application and optimization of machine vision technology in intelligent manufacturing, and aims to deeply explore its potential in improving production efficiency, product quality and realizing intelligent decision-making. Through the system of relevant literature at home and abroad, combined with the actual industrial application scenario, using the combination of theoretical analysis and empirical research method, focusing on the machine vision technology in defect detection, product assembly, robot guide application effect, and in view of the existing technology limitations are put forward based on deep learning optimization scheme. The results show that the optimized machine vision system can significantly improve the detection accuracy and speed, reduce the rate of false detection, and maintain stable performance in complex environment. In particular, the breakthrough has been made in small defect identification and multi-perspective target positioning, which provides new ideas for solving the problems that are difficult to solve with traditional methods.
Keyword:Machine Vision Technology Intelligent Manufacturing Defect Detection
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法与技术路线 1
2机器视觉在智能制造中的应用领域 2
2.1质量检测中的应用 2
2.2智能装配中的应用 3
2.3物流分拣中的应用 3
3机器视觉技术的关键要素分析 4
3.1图像采集技术优化 4
3.2图像处理算法改进 4
3.3视觉系统集成方案 5
4机器视觉系统的性能提升策略 5
4.1精度提升方法研究 6
4.2实时性优化措施 6
4.3系统稳定性保障 7
结论 7
参考文献 9
致谢 10
