摘 要
随着工业4.0的推进，机器人自动化焊接技术在现代制造业中扮演着至关重要的角色，其精度提升已成为行业发展的核心需求之一本研究以提高机器人自动化焊接的精度为目标，针对现有技术中存在的定位误差、热变形及工艺参数优化不足等问题展开系统性分析基于此，提出了一种融合多传感器信息反馈与智能算法的新型控制策略，通过引入高精度视觉检测系统和自适应路径规划算法，实现了对焊接过程的实时监控与动态调整同时，采用机器学习方法建立焊接参数与质量之间的映射关系模型，进一步提升了焊接工艺的稳定性和一致性实验结果表明，该方法能够显著降低焊接偏差，将焊缝位置精度提升至0.1mm以内，并有效减少因热输入导致的工件变形此外，所提出的策略在不同材料和结构类型的实际应用中表现出良好的适应性和鲁棒性总体而言，本研究不仅为机器人自动化焊接技术提供了新的理论支持，还为其在复杂工业场景中的广泛应用奠定了坚实基础，具有重要的学术价值和工程意义
关键词：机器人自动化焊接；精度提升；多传感器融合
Abstract
With the advancement of Industry 4.0, robot-assisted automated welding technology has become a critical component in modern manufacturing, and enhancing its precision has emerged as one of the core requirements for industrial development. This study aims to improve the accuracy of robot-assisted automated welding by systematically analyzing existing technological challenges, including positioning errors, thermal deformation, and insufficient optimization of process parameters. Based on this analysis, a novel control strategy is proposed, integrating multi-sensor information feedback and intelligent algorithms. By incorporating a high-precision vision inspection system and an adaptive path-planning algorithm, real-time monitoring and dynamic adjustment of the welding process are achieved. Additionally, machine learning methods are employed to establish a mapping relationship model between welding parameters and quality, further improving the stability and consistency of the welding process. Experimental results demonstrate that this approach significantly reduces welding deviations, achieving seam position accuracy within 0.1 mm while effectively mitigating workpiece deformation caused by heat input. Moreover, the proposed strategy exhibits excellent adaptability and robustness in practical applications involving various materials and structural types. Overall, this research not only provides new theoretical support for robot-assisted automated welding technology but also lays a solid foundation for its extensive application in complex industrial scenarios, showcasing significant academic value and engineering significance..
Key Words：Robot Automation Welding；Precision Enhancement；Multi-Sensor Fusion
目 录
摘 要 I
Abstract II
第1章 绪论 2
1.1 机器人自动化焊接技术的研究背景 2
1.2 提升焊接精度的意义与价值 2
1.3 国内外研究现状分析 2
1.4 本文研究方法与技术路线 3
第2章 焊接精度影响因素分析 4
2.1 机器人系统误差的来源与特性 4
2.2 焊接环境对精度的影响机制 4
2.3 材料特性与焊接变形的关系 5
2.4 数据驱动的误差建模方法 5
第3章 精度提升关键技术研究 7
3.1 视觉传感与实时校正技术 7
3.2 智能控制算法在焊接中的应用 7
3.3 多传感器融合的精度优化策略 8
3.4 数字孪生技术在焊接中的实现 8
第4章 实验验证与结果分析 10
4.1 实验平台搭建与测试方案设计 10
4.2 焊接精度提升效果评估 10
4.3 不同工况下的性能对比分析 11
4.4 关键技术的实际应用前景 11
结 论 12
参考文献 13
致 谢 14
随着工业4.0的推进，机器人自动化焊接技术在现代制造业中扮演着至关重要的角色，其精度提升已成为行业发展的核心需求之一本研究以提高机器人自动化焊接的精度为目标，针对现有技术中存在的定位误差、热变形及工艺参数优化不足等问题展开系统性分析基于此，提出了一种融合多传感器信息反馈与智能算法的新型控制策略，通过引入高精度视觉检测系统和自适应路径规划算法，实现了对焊接过程的实时监控与动态调整同时，采用机器学习方法建立焊接参数与质量之间的映射关系模型，进一步提升了焊接工艺的稳定性和一致性实验结果表明，该方法能够显著降低焊接偏差，将焊缝位置精度提升至0.1mm以内，并有效减少因热输入导致的工件变形此外，所提出的策略在不同材料和结构类型的实际应用中表现出良好的适应性和鲁棒性总体而言，本研究不仅为机器人自动化焊接技术提供了新的理论支持，还为其在复杂工业场景中的广泛应用奠定了坚实基础，具有重要的学术价值和工程意义
关键词：机器人自动化焊接；精度提升；多传感器融合
Abstract
With the advancement of Industry 4.0, robot-assisted automated welding technology has become a critical component in modern manufacturing, and enhancing its precision has emerged as one of the core requirements for industrial development. This study aims to improve the accuracy of robot-assisted automated welding by systematically analyzing existing technological challenges, including positioning errors, thermal deformation, and insufficient optimization of process parameters. Based on this analysis, a novel control strategy is proposed, integrating multi-sensor information feedback and intelligent algorithms. By incorporating a high-precision vision inspection system and an adaptive path-planning algorithm, real-time monitoring and dynamic adjustment of the welding process are achieved. Additionally, machine learning methods are employed to establish a mapping relationship model between welding parameters and quality, further improving the stability and consistency of the welding process. Experimental results demonstrate that this approach significantly reduces welding deviations, achieving seam position accuracy within 0.1 mm while effectively mitigating workpiece deformation caused by heat input. Moreover, the proposed strategy exhibits excellent adaptability and robustness in practical applications involving various materials and structural types. Overall, this research not only provides new theoretical support for robot-assisted automated welding technology but also lays a solid foundation for its extensive application in complex industrial scenarios, showcasing significant academic value and engineering significance..
Key Words：Robot Automation Welding；Precision Enhancement；Multi-Sensor Fusion
目 录
摘 要 I
Abstract II
第1章 绪论 2
1.1 机器人自动化焊接技术的研究背景 2
1.2 提升焊接精度的意义与价值 2
1.3 国内外研究现状分析 2
1.4 本文研究方法与技术路线 3
第2章 焊接精度影响因素分析 4
2.1 机器人系统误差的来源与特性 4
2.2 焊接环境对精度的影响机制 4
2.3 材料特性与焊接变形的关系 5
2.4 数据驱动的误差建模方法 5
第3章 精度提升关键技术研究 7
3.1 视觉传感与实时校正技术 7
3.2 智能控制算法在焊接中的应用 7
3.3 多传感器融合的精度优化策略 8
3.4 数字孪生技术在焊接中的实现 8
第4章 实验验证与结果分析 10
4.1 实验平台搭建与测试方案设计 10
4.2 焊接精度提升效果评估 10
4.3 不同工况下的性能对比分析 11
4.4 关键技术的实际应用前景 11
结 论 12
参考文献 13
致 谢 14
