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：高性能加工工艺和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行为。该方案包含以下元素(e1到e5)：*e1。集成激光辅助加工、低温冷却和微量润滑：目的是研究低温冷却和微量润滑对刀具磨损和生产率的协同效应。以及激光辅助加工中的表面完整性。工艺优化将通过实验研究和工艺模拟来确定。*E2。使用常规和超硬磨料刀具间歇钻削复合材料：基于对单一金刚石颗粒切割FRP复合材料的基本了解，开发了一个预测切削力模型。该模型将被扩展到预测和优化使用超硬磨料工具的轨道钻削过程。还将使用常规工具研究高频-低振幅区域的振动辅助钻井。*E3。车削过程中刀具预失效的检测：目标是开发一种检测加工过程中意外刀具破损的系统。将评估各种信号，并将特别考虑在时间和频率域使用不同的信号处理技术进行特征提取。将开发一种多传感器融合模型，用于与NC控制器进行双向通信。*E4。加工残余应力和微观结构变化的预测：在假设切屑形成不分段的情况下，建立了预测加工残余应力(RS)的二维有限元模型。为了提高预测精度，建议考虑切屑分割、后刀面刀具磨损和材料相变的影响。为了验证，将对常规加工和激光辅助加工进行斜切削实验。*E5。高温合金在伪随机激励下的高温微动磨损研究：在550oC条件下，研究了表面氧化物在钴基高温合金微动磨损中的作用，建立了基于有限元的摩擦温升计算模型，该模型考虑了接触粗糙度在空间和高度上的随机分布。申请人的“广义微动磨损理论”将通过考虑以下因素的影响加以扩展：(A)摩擦加热引起的裂纹萌生和扩展；(B)氧化动力学；以及(C)随机激励；这是以前从未研究过的一个方面。

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. **