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An adaptive methodology for monitoring and controlling of precision machining and on-machine inspection.

机译：用于监视和控制精密加工和在机检查的自适应方法。

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摘要

In this research, an adaptive methodology for monitoring and controlling the accuracy of CNC machine tools in material removal and on-machine inspection was developed. A reference part based error modeling technique, robust search algorithms, and an adaptive thermal effect tracking method were proposed to extend the capability of a machine tool to sense and compensate for errors during a sequence of operations. The reference part based error modeling technique involves mathematical models and measurements closely related to real parts and therefore reduces the uncertainty in error estimation and compensation. Rigid body kinematics was used to derive the error models that correlate the resultant errors in the machine tool workspace to the imperfection and misalignment of position elements and workpieces. The derived error models are capable of decoupling the machine tool's position errors and workpiece misalignment.;To improve the robustness and effectiveness of the derived error models, robust search algorithms were developed to identify the appropriate measuring points, with respect to the designated tolerance, for arbitrary shapes of reference parts. The identified measurement points were least sensitive to measurement uncertainty and variation in load induced errors. The search algorithms utilize computer simulation with limited information abstracted from previous measurements. Thus, the measurement effort involved in error modeling has been significantly reduced. Experimental results demonstrate the feasibility and the effectiveness of the algorithms with desired accuracy.;An adaptive algorithm was developed to cope with the time-varying thermal effect on position accuracy of machine tools. A state observer was constructed to track and predict the thermal induced errors and continuously modify the coefficients of the error model. The state observer uses the information derived from a partial recalibration process as feedback to keep track of the machine tool error migration without interfering with the existing fixtures and parts. A full scale recalibration process can be conducted, after a part is finished, to fine tune the state estimation. As the error model coefficients are determined, the model can be used to correct the on-machine probing data or to generate the compensation signal for precision machining. Therefore, an adaptive environment was provided for error monitoring and controlling for precision machining and on-machine inspection.
机译：在这项研究中，开发了一种用于监测和控制数控机床在材料去除和在机检查中的准确性的自适应方法。提出了一种基于参考零件的误差建模技术，鲁棒搜索算法和自适应热效应跟踪方法，以扩展机床在一系列操作中感知和补偿误差的能力。基于参考零件的误差建模技术涉及与实际零件紧密相关的数学模型和测量，因此减少了误差估计和补偿中的不确定性。刚体运动学用于导出误差模型，该误差模型将机床工作空间中产生的误差与位置元素和工件的缺陷和未对准相关。导出的误差模型能够解耦机床的位置误差和工件不对中。为了提高导出的误差模型的鲁棒性和有效性，开发了鲁棒的搜索算法来针对指定的公差识别合适的测量点，以用于参考零件的任意形状。识别出的测量点对测量不确定性和负载引起的误差变化最不敏感。搜索算法利用计算机仿真，并从先前的测量中提取有限的信息。因此，大大减少了误差建模中涉及的测量工作。实验结果证明了该算法的可行性和有效性。提出了一种自适应算法来应对时变热效应对机床定位精度的影响。构造了状态观察器以跟踪和预测热引起的误差，并不断修改误差模型的系数。状态观察器使用从部分重新校准过程中获得的信息作为反馈，以在不干扰现有固定装置和零件的情况下跟踪机床误差的迁移。零件完成后，可以进行满量程重新校准过程，以微调状态估计。确定误差模型系数后，该模型可用于校正在机探测数据或生成用于精密加工的补偿信号。因此，提供了一种自适应环境，用于错误监视和控制以进行精密加工和在机检查。

著录项

  • 作者

    Mou, Jong-I.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Mechanical.;Engineering Industrial.
  • 学位 Ph.D.
  • 年度 1992
  • 页码 306 p.
  • 总页数 306
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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