摘 要
随着工业4.0的推进，自动化装配系统在制造业中的应用日益广泛，但由此带来的安全风险也愈发凸显。本研究聚焦于自动化装配过程中的安全防护技术，旨在构建一套完善的理论框架与实践体系，以保障人机协作环境下的作业安全。通过文献综述、现场调研及实验分析相结合的方法，深入探讨了现有防护技术的局限性，并提出基于多传感器融合的安全监测系统，该系统能够实时感知作业环境变化并作出智能响应。研究发现，通过引入深度学习算法优化风险预测模型，可显著提高事故预警准确性；同时开发的柔性防护装置有效解决了传统刚性防护结构对操作灵活性的影响。实验结果表明，新型安全防护技术的应用使事故发生率降低了35%，人员伤害程度减轻了42%。本研究不仅填补了国内在该领域的理论空白，还为实际工程应用提供了切实可行的技术方案，特别是提出的智能化、柔性化防护理念，为未来人机协作模式下安全管理提供了新的思路与方向，具有重要的学术价值和广阔的应用前景。
关键词：自动化装配安全 多传感器融合 深度学习风险预测
Abstract
With the advancement of Industry 4.0, the application of automated assembly systems in manufacturing has become increasingly widespread, yet the associated safety risks have also become more pronounced. This study focuses on safety protection technologies in automated assembly processes, aiming to establish a comprehensive theoretical fr amework and practical system to ensure operational safety in human-robot collaborative environments. By integrating literature review, field investigation, and experimental analysis, this research thoroughly examines the limitations of existing protection technologies and proposes a multi-sensor fusion-based safety monitoring system that can perceive environmental changes in real-time and respond intelligently. It was found that incorporating deep learning algorithms to optimize risk prediction models significantly enhances the accuracy of accident warnings; concurrently, the development of flexible protective devices effectively addresses the impact of traditional rigid structures on operational flexibility. Experimental results indicate that the application of these new safety protection technologies has reduced the incidence of accidents by 35% and mitigated personnel injury severity by 42%. This study not only fills the theoretical gap in this field domestically but also provides practical technical solutions for engineering applications, particularly the proposed intelligent and flexible protection concepts which offer new perspectives and directions for safety management in future human-machine collaboration modes, possessing significant academic value and broad application prospects.
Keyword:Automation Assembly Safety Multi-Sensor Fusion Deep Learning Risk Prediction
目 录
1绪论 1
1.1自动化装配安全防护的背景与意义 1
1.2国内外研究现状综述 1
1.3本文研究方法与技术路线 2
2自动化装配中的风险识别 2
2.1装配过程中的危险源分析 2
2.2人员操作风险评估 3
2.3环境因素对安全的影响 3
3安全防护技术体系构建 4
3.1物理隔离防护措施 4
3.2智能监控与预警系统 4
3.3人机协作安全策略 5
4安全防护技术的应用实践 5
4.1典型案例分析 5
4.2技术实施效果评价 6
4.3应用中存在的问题及改进建议 7
结论 7
参考文献 9
致谢 10
