摘 要
随着智能制造技术的快速发展，智能化装配系统在现代工业生产中的应用日益广泛，其核心在于通过优化机械结构与控制算法实现高效、精准的协同作业。然而，传统装配系统的机械结构设计往往独立于控制系统，难以满足复杂工况下多目标优化的需求。为此，本文以智能化装配系统为研究对象，聚焦机械结构的协同优化问题，旨在提出一种集成机械设计与控制策略的优化方法。研究首先分析了智能化装配系统中机械结构的关键特性及其对整体性能的影响，并构建了基于多物理场耦合的数学模型。随后，采用遗传算法与有限元分析相结合的技术路径，实现了机械结构参数与运动控制参数的联合优化。实验结果表明，所提方法能够显著提升装配系统的精度与效率，同时降低能耗与故障率。具体而言，优化后的系统装配误差降低了约30%，运行能耗减少了25%。
关键词：智能化装配系统 机械结构优化 多物理场耦合
Abstract
With the rapid development of intelligent manufacturing technology, intelligent assembly system is increasingly widely used in modern industrial production. Its core lies in realizing efficient and accurate cooperative operation through the optimization of mechanical structure and control algorithm. However, the mechanical structure design of the traditional assembly system is often independent of the control system, which is difficult to meet the requirements of multi-ob jective optimization under complex working conditions. Therefore, this paper takes the intelligent assembly system, focuses on the collaborative optimization of mechanical structure, and aims to propose an optimization method of integrated mechanical design and control strategy. We first analyze the key characteristics of mechanical structure in intelligent assembly system, and construct a mathematical model based on multiple physical field coupling. Subsequently, a technical path combining genetic algorithm and finite element analysis was used to achieve the joint optimization of mechanical structural parameters and motion control parameters. The experimental results show that the proposed method can significantly improve the accuracy and efficiency of the assembly system, while reducing the energy consumption and failure rate. Specifically, the optimized system assembly error is reduced by about 30%, and the operating energy consumption is reduced by 25%.
Keyword:Intelligent Assembly System Mechanical Structure Optimization Multi-Physics Coupling
目 录
引言 1
1智能化装配系统概述 1
1.1装配系统智能化发展现状 1
1.2机械结构在装配中的作用分析 2
1.3协同优化的基本概念与意义 2
1.4研究目标与技术路线 2
2机械结构的性能需求分析 3
2.1装配任务对机械结构的要求 3
2.2动力学特性对协同优化的影响 3
2.3结构刚度与精度的关系研究 4
2.4材料选择与性能匹配分析 4
3协同优化的关键技术研究 5
3.1多学科优化方法的应用 5
3.2数据驱动的协同优化策略 5
3.3模型建立与仿真验证方法 5
3.4算法效率与计算复杂度分析 6
3.5不确定性因素的处理方法 6
4实验验证与案例分析 7
4.1实验平台的设计与搭建 7
4.2典型装配任务的优化实践 7
4.3优化效果的定量评估方法 7
4.4实际应用中的问题与挑战 8
结论 8
参考文献 10
致谢 11
