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Uncertainties in the error compensation of coordinate measuring machines.

机译:坐标测量机误差补偿的不确定性。

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摘要

Coordinate measuring machines (CMMs) are widely used in industry as accurate measuring devices of mechanical components. Most of these machines come with software algorithms to compensate for any residual errors that may be present in the machine. Mathematical models have been developed by metrology researchers that form the basis of these software algorithms. The research reported on herein is aimed at developing statistical models for estimating the uncertainties in the error compensation methodology. A kinematic model has been developed for a particular CMM to predict the errors due to geometric and kinematic error sources in the machine. This model has been used to error compensate the CMM. Three statistical techniques have been used to create uncertainty models of the error compensation methodology. These three models estimate the uncertainty in the error compensations implemented on the CMM. A Gaussian model, a model based on the bootstrap method, and a regression model have been developed. The Gaussian model assumes that the errors in the CMM are normally distributed, while the bootstrap method makes no assumptions pertaining to the distribution of these errors. The regression model is based on a conventional regression analysis of the error data. The error compensated CMM was tested using standard references and artifacts to validate the kinematic error model. The uncertainty estimates in the error compensations along three orthogonal trajectories of the probe tip are computed. It is found that the uncertainties computed by the bootstrap method are generally slightly smaller than those computed by the Gaussian model, both of these uncertainties being significantly larger than those computed by the regression method. The discrepancy between the bootstrap and the Gaussian model results indicates that the measurements of the errors in the motion of the linear axes of the CMM are not normally distributed. The measurements of the errors have a distribution which is slightly more peaked than what is expected from a normal distribution. The non-normalities in the distributions of these errors suggest that the bootstrap is a more appropriate technique for estimating uncertainties of the error compensations. The residual errors present in the three orthogonal trajectories of the probe tip, after incorporating the error compensations in these trajectories, were measured, and the total uncertainties in these measurements arising from the error compensation scheme and the measurement procedure are derived and displayed.
机译:坐标测量机(CMM)在工业中广泛用作机械部件的精确测量设备。这些机器中的大多数都带有软件算法,以补偿机器中可能存在的任何残留错误。计量研究人员已经开发了数学模型,这些模型构成了这些软件算法的基础。本文报道的研究旨在开发统计模型,以估计误差补偿方法中的不确定性。已经为特定的CMM开发了运动学模型,以预测由于机器中的几何和运动学误差源而引起的误差。该模型已用于对CMM进行误差补偿。已经使用三种统计技术来创建误差补偿方法的不确定性模型。这三个模型估计了在CMM上执行的误差补偿的不确定性。已经开发了高斯模型,基于引导方法的模型和回归模型。高斯模型假设CMM中的误差是正态分布的,而引导程序方法则不做任何与这些误差的分布有关的假设。回归模型基于误差数据的常规回归分析。使用标准参考和工件对经过误差补偿的CMM进行了测试,以验证运动学误差模型。计算沿着探针尖端的三个正交轨迹的误差补偿中的不确定性估计。发现通过自举方法计算的不确定性通常比通过高斯模型计算的不确定性略小,这两个不确定性都明显大于通过回归方法计算的不确定性。引导程序和高斯模型结果之间的差异表明,坐标测量机线性轴运动误差的测量值不呈正态分布。误差的测量结果具有比正态分布所期望的峰值略高的分布。这些误差分布的非正态性表明,自举是一种更合适的技术,用于估计误差补偿的不确定性。在将误差补偿合并到这些轨迹中后,测量存在于探头尖端的三个正交轨迹中的残留误差,然后得出并显示由于误差补偿方案和测量过程而导致的这些测量中的总不确定性。

著录项

  • 作者

    Dama, Rajiv.;

  • 作者单位

    The Pennsylvania State University.;

  • 授予单位 The Pennsylvania State University.;
  • 学科 Engineering Mechanical.;Statistics.;Engineering Industrial.
  • 学位 Ph.D.
  • 年度 1998
  • 页码 176 p.
  • 总页数 176
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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