摘 要
机械传动系统作为现代工业设备的核心组成部分，其运行效率与可靠性直接影响整体生产效能。然而，摩擦、磨损及疲劳损伤是导致传动部件失效的主要原因，而润滑技术在缓解这些问题中起着关键作用。本研究以提升机械传动系统的寿命和性能为目标，深入探讨了润滑技术的优化策略及其对寿命预测的影响。通过结合实验分析与数值模拟，研究建立了基于表面粗糙度、载荷分布和温度场的多因素润滑模型，并提出了改进的磨损评估方法。同时，引入人工智能算法对传动系统寿命进行精准预测，实现了从传统经验估算向数据驱动预测的转变。研究表明，优化后的润滑方案可显著降低摩擦系数并延缓磨损进程，从而将传动部件的使用寿命提高约25%。此外，所开发的寿命预测模型具有较高的准确性和适应性，能够为实际工程应用提供可靠指导。本研究的创新点在于综合考虑了润滑状态与材料特性之间的耦合关系，并首次将深度学习技术应用于复杂工况下的寿命预测问题，为机械传动系统的高效运维提供了新的理论依据和技术支持。研究成果不仅有助于推动润滑技术的发展，也为相关领域的工程实践提供了重要参考价值。
关键词：机械传动系统；润滑技术优化；磨损评估
Abstract: Mechanical transmission systems, as a core component of modern industrial equipment, directly influence overall production efficiency through their operational efficiency and reliability. However, friction, wear, and fatigue damage are the primary causes of failure in transmission components, where lubrication technology plays a critical role in mitigating these issues. This study aims to enhance the lifespan and performance of mechanical transmission systems by thoroughly investigating optimization strategies for lubrication technology and their impact on lifespan prediction. By integrating experimental analysis with numerical simulation, a multi-factor lubrication model based on surface roughness, load distribution, and temperature field was established, along with an improved method for wear assessment. Additionally, artificial intelligence algorithms were introduced to achieve precise predictions of the transmission system's lifespan, facilitating a transition from traditional empirical estimation to data-driven forecasting. The research demonstrates that the optimized lubrication scheme significantly reduces the friction coefficient and slows down the wear process, thereby increasing the service life of transmission components by approximately 25%. Moreover, the developed lifespan prediction model exhibits high accuracy and adaptability, providing reliable guidance for practical engineering applications. The innovation of this study lies in comprehensively considering the coupling relationship between lubrication conditions and material properties, while being the first to apply deep learning technology to lifespan prediction under complex operating conditions, offering new theoretical foundations and technical support for the efficient operation and maintenance of mechanical transmission systems. The research findings not only contribute to the advancement of lubrication technology but also provide significant reference value for engineering practices in related fields.
Keywords: Mechanical Transmission System; Lubrication Technology Optimization; Wear Assessment
目 录
1绪论 1
1.1机械传动系统润滑技术的研究背景 1
1.2润滑技术与寿命预测研究的意义 1
1.3国内外研究现状分析 1
1.4本文研究方法与技术路线 2
2润滑技术对机械传动系统性能的影响 2
2.1润滑剂类型及其作用机制 2
2.2润滑膜形成原理与特性分析 3
2.3不同工况下的润滑效果评估 3
2.4润滑技术对磨损行为的改善 4
2.5润滑技术优化的关键因素 4
3机械传动系统寿命预测理论与方法 5
3.1寿命预测的基本概念与框架 5
3.2基于摩擦学的寿命预测模型 5
3.3数据驱动的寿命预测方法 6
3.4影响寿命预测精度的因素分析 6
3.5寿命预测技术的实际应用案例 7
4润滑技术与寿命预测的耦合关系研究 7
4.1润滑条件对寿命预测的影响机制 7
4.2基于润滑状态的寿命预测模型构建 8
4.3实验验证与数据分析方法 8
4.4润滑技术改进对寿命预测结果的提升 9
4.5耦合关系研究的未来发展方向 9
结论 11
参考文献 12
致 谢 13
