Investigation of thermoelastic and dynamic phenomena for improved design and control of manufacturing and tribological systems

这项建议涉及两个主要问题；高性能的加工工艺，复杂激励下的微动磨损预测能力。这两个问题是相互关联的，因为加工表面的完整性控制着部件的摩擦学性能。提案由以下元素组成（E1 ~ E5）： ***E1。集成激光辅助加工，低温冷却和最小量润滑：目的是研究低温冷却（LiN），最小量润滑对刀具磨损，生产率的协同效应。激光辅助加工中的表面完整性。通过实验研究和工艺模拟确定优化工艺。* * * E2。使用常规和超磨料工具进行复合材料的间歇钻孔：基于对单个金刚石颗粒切割FRP复合材料的基本理解，开发了预测切削力模型。该模型将扩展到超磨料工具轨道钻进过程的预测和优化。在高频-低振幅状态下的振动辅助钻井也将使用常规工具进行研究。* * * E3。车削过程中刀具预失效的检测：目标是开发一个检测加工中意外刀具破损的系统。我们将对各种信号进行评估，并特别考虑在时域和频域使用不同的信号处理技术进行特征提取。将开发一个多传感器融合模型，用于与NC控制器的双向通信。* * * E4。加工残余应力和微观结构变化的预测：建立了一个二维有限元模型来预测加工残余应力（RS），假设切屑不形成节段。为了提高预测精度，提出了考虑切屑分割、刀面磨损和材料相变的影响。为了验证，将对传统加工和激光辅助加工进行斜切实验。* * * E5。伪随机激励下高温合金的微动磨损：基于钴基高温合金表面氧化物在550℃微动磨损中的作用实验，考虑接触凸度的空间和高度随机分布，建立了基于fe的摩擦温升模型。申请人的“广义微动磨损理论”将通过考虑：(a)摩擦加热引起的裂纹萌生和扩展，(b)氧化动力学和(c)随机激励的影响来扩展；这方面以前没有被研究过。**

This proposal deals with two major issues; high performance machining processes, and predictive capability for fretting wear under complex excitation. These two issues are interrelated, since the integrity of machined surfaces control the tribological behaviour of the component. The proposal consists of the following elements (E1 to E5): ***E1. Integrated Laser Assisted Machining, Cryogenic Cooling and Minimum Quantity Lubrication: The objective is to investigate the synergetic effect of cryogenic cooling (LiN), minimum quantity lubrication on tool wear, productivity. and surface integrity in laser-assisted machining. Process optimized will defined through experimental investigation and process simulation. ***E2. Intermittent Drilling of Composites using Conventional and Superabrasive Tools: A predictive cutting force model was developed, based on a fundamental understanding of FRP composites cutting by a single diamond grain. The model will be extended to predict and optimize the orbital drilling process using superabrasive tools. Vibration-assisted drilling at high frequency-low amplitude regime will also be investigated using conventional tools. ***E3. Detection of Tool Pre-Failure in Turning Processes: The objective is to develop a system to detect unexpected tool breakage in machining. Various signals will be evaluated and special consideration will be given to feature extraction using different signal processing techniques in the time and frequency domains. A multi-sensor fusion model will be developed for 2-way communication with the NC controller. ***E4. Prediction of Machining-Induced Residual Stresses and Micro-structural Changes: A 2D FE model was developed to predict machining-induced residual stress (RS), assuming non-segmental chip formation. To improve prediction accuracy, it is proposed to consider the effects of chip segmentation, flank tool wear, and material phase transformation. For validation, oblique cutting experiments will be conducted for conventional and laser-assisted machining. ***E5. High Temperature Fretting Wear of Superalloys under Pseudo Random Excitation: Following the experiments on the role of surface oxide in fretting wear of cobalt-based superalloys at 550oC, a FE-based model was developed to estimate friction-induced temperature rise, considering the spatial and height random distributions of contact asperities. The applicant's `generalized fretting wear theory', will be extended by considering the effect of: (a) crack initiation and propagation due to frictional heating, (b) oxidation kinetics, and (c) random excitation; an aspect that has not been investigated before. **