摘 要
随着制造业向智能化转型，机械电子工程作为智能制造的核心支撑技术面临新的挑战与机遇。本文旨在探讨面向智能制造的机械电子工程优化设计，以提升制造系统的灵活性、高效性和智能化水平。研究基于工业4.0理念，聚焦于机电一体化系统集成、智能感知与控制等关键技术领域，提出了一种融合多源异构数据的机电系统协同优化方法。通过建立涵盖设备层、控制层和信息层的多层次模型，实现了对复杂制造过程的精准建模与仿真。采用深度学习算法对生产数据进行分析挖掘，构建了自适应预测维护系统，有效降低了设备故障率。同时，引入数字孪生技术，实现了物理实体与虚拟模型的双向映射与交互，为实时监控和决策支持提供了依据。
关键词：智能制造 机电一体化系统集成 多源异构数据协同优化
Abstract
With the transformation of manufacturing industry to intelligent manufacturing, mechanical and electronic engineering, as the core supporting technology of intelligent manufacturing, is facing new challenges and opportunities. This paper aims to explore the optimal design of the electromechanical engineering for intelligent manufacturing to improve the flexibility, efficiency and intelligence level of the manufacturing system. Based on the concept of industry 4.0, focusing on key technology fields such as mechatronics system integration, intelligent perception and control, this paper, a collaborative optimization method of electromechanical system integrating multi-source heterogeneous data is proposed. By establishing a multi-level model covering the equipment layer, control layer and information layer, the accurate modeling and simulation of the complex manufacturing process are realized. Using the deep learning algorithm to analyze and mine the production data, and build an adaptive prediction and maintenance system, which effectively reduces the equipment failure rate. At the same time, the digital twin technology is introduced to realize the two-way mapping and interaction between physical entity and virtual model, which provides a basis for real-time monitoring and decision support.
Keyword:Intelligent Manufacturing Mechatronics System Integration Multi-source Heterogeneous Data Collaborative Optimization
目 录
1绪论 1
1.1面向智能制造的背景与意义 1
1.2机械电子工程优化设计的研究现状 1
1.3研究方法概述 1
2智能制造需求分析 2
2.1智能制造对机械电子的要求 2
2.2关键技术需求解析 3
2.3设计目标的确立 3
3优化设计理论与方法 4
3.1智能制造下的设计原则 4
3.2多学科优化方法应用 5
3.3系统集成与协同设计 5
4实施方案与案例研究 6
4.1典型应用场景选择 6
4.2方案设计与实现 7
4.3效果评估与改进建议 7
结论 8
参考文献 9
致谢 10
