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Model-based control of surface integrity in hard turning

Model-based control of surface integrity in hard turning
基于模型的硬车削表面完整性控制
批准号:
401819829
负责人:
Professor Dr.-Ing. Thomas Bergs, since 7/2019
金额:
$0.0万
依托单位国家:
德国
项目类别:
Priority Programmes
财政年份:
2018
资助国家:
德国
项目状态:
已结题
起止时间:
2017-12-31 至 2021-12-31

项目摘要

项目成果

Professor Dr.-Ing. Thomas Bergs, since 7/2019的其他基金

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中文摘要
翻译
其目的是在使用CBN或硬质合金刀具车削调质42CrMo4钢(48 HRC,Rm = 1557 MPa)的过程中,对与生产相关的规定表面完整性属性进行直接和间接工艺监控。因此,材料将被研究的组件,其周边区域的属性显着影响功能。直接过程监测是指在过程中通过微磁涡流方法检测表面完整性。间接过程监测通过可用于工业环境的传感器进行,这些传感器在线记录过程中的温度和切削力分量,并根据模型得出当前表面完整性属性的结论。在该过程中,要监测晶粒尺寸分布、残余应力和相分数的边界区特性。首先,在第一个资助期内将实施一个可靠的监测系统,然后在第二个资助期内将该系统扩展到包括一项法规。由于可达性有限,无法在KHz和10 µm范围内以高空间和时间分辨率监测工业车削过程中的热和机械状态变量。然而,它可以以集成热电偶、声发射传感器、测力计和高温计的形式实现,用于选择性或整体监控状态变量。然而,不知道这些具有低时间和空间分辨率的状态变量的选择性或积分测量如何与整个切割区中的高分辨率状态变量相关。在模拟过程中研究这种相关性,该模拟过程近似于车削过程的条件,同时允许用于车削过程的面向应用的传感器技术以及高空间和时间分辨率传感器(高速相机)的可访问性。为了预测可在加工区域中测量的过程状态变量与引起金属边缘区域的修改的空间和时间分辨的状态变量之间的相关性,然后开发物理或经验模型。由于具有较高的空间和时间分辨率,应变和应变率场的DIC测量方法和温度场的热成像测量方法都被用于确定温度场。所开发的模型可以与面向应用的传感器结合使用,用于车削过程中间接控制表面性能,只要过程状态变量和边缘区域修改之间的关系是已知的。这也需要在类比过程中或通过有效的数值模拟来分析这种相关性。与此同时,微磁涡流测量方法用于模拟过程中,允许直接控制。
英文摘要
The aim is the combined direct and indirect process monitoring and control of defined production-related surface integrity properties during the turning of quenched and tempered 42CrMo4 steels (48 HRC, Rm = 1557 MPa) with CBn or carbide tools. Thus a material will be investigated for components whose peripheral zone properties significantly influence functionality. Direct process monitoring refers to the detection of the surface integrity properties via micromagnetic eddy current methods in the process. Indirect process monitoring is carried out via sensors that can be used in industrial environments, which record temperatures and cutting force components online in the process and allow conclusions to be drawn on current surface integrity properties based on models. During the process, the boundary zone properties of the grain size distribution, residual stresses and phase fractions are to be monitored. First of all, a reliable monitoring system will be implemented in the first funding period, which will then be extended to include a regulation in the second funding period. Due to limited accessibility, it is not possible to monitor the thermal and mechanical state variables in the industrial turning process with high spatial and time resolution in the KHz and 10 µm range. However, it can be achieved in the form of integrated thermocouples, acoustic emission sensors, dynamometers and pyrometers for selective or integral monitoring of state variables. However, it is not known how these selective or integral measurements of the state variables with low temporal and spatial resolution correlate with high-resolution state variables in the entire cutting zone. This correlation is investigated in an analogy process, which approximates the conditions of the turning process and at the same time permits accessibility for the application-oriented sensor technology for the turning process as well as high spatial and time resolution sensors (high-speed cameras). In order to predict the correlation between process state variables that can be measured in the machining zone and spatially and time-resolved state variables that cause a modification of the metal edge zone, physical or empirical models are then developed. For the high spatial and time resolution, both the DIC method for measuring strain and strain rate fields and thermography are used for determining temperature fields. The developed models can be used in conjunction with application-oriented sensors for the turning process to indirectly control the surface properties, as far as the relationship between process state variables and edge zone modification is known. This also requires the analysis of this correlation in the analogy process or by means of validated numerical simulations. Parallel to this, micromagnetic eddy current measurement methods are used in the analogy process, which permit direct control.
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Methodology for the highly iterative design of production process sequences
  • 批准号:
    410193563
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2018
  • 负责人:
    Professor Dr.-Ing. Thomas Bergs, since 7/2019
  • 依托单位:
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    403801854
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2018
  • 负责人:
    Professor Dr.-Ing. Thomas Bergs, since 7/2019
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    391202973
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2018
  • 负责人:
    Professor Dr.-Ing. Thomas Bergs, since 7/2019
  • 依托单位:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2017
  • 负责人:
    Professor Dr.-Ing. Thomas Bergs, since 7/2019
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