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首页> 外文期刊>Journal of the Chinese Society of Mechanical Engineers, Series C: Transactions of the Chinese Society of Mechanical Engineers >Measurement error reduction and sampling strategy design for automated inspection process
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Measurement error reduction and sampling strategy design for automated inspection process

机译：用于自动检查过程的测量误差减少和采样策略设计

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摘要

Many inspection processes are contaminated by various measurement error. One of the prominent sources for measurement errors is due to the imperfection of a measuring device and the compound effect of its imperfection with geometric characteristics of a measured feature. To ensure the quality and reliability of any inspection process, measurement errors need to be identified and reduced by minimizing the effect of the compound errors. If this can be done, the quality of collected data can be enhanced and a more meaningful analysis result can then be drawn. Meanwhile, to effectively conduct dimensional inspection in a computer-integrated manufacturing (CIM) environment there is also an urgent need to derive sampling strategy that can be used to specify a set of measuring points that lead to an accurate sampling while minimizing the sampling time and cost. In this paper, the issues of measurement error identification and reduction for machine calibration and dimension measurement are first discussed. Analytical models are derived to access and decouple the compound effect of both types of errors, and thus, reduce the measurement errors. Then, feature-based Hammersley sequence and stratified sampling method are used to derive the sampling strategy for various geometric feature surfaces that have specified measuring points.
机译：许多检查过程都受到各种测量误差的污染。测量误差的主要来源之一是由于测量设备的不完善以及其不完善与被测特征的几何特征的复合作用。为确保任何检查过程的质量和可靠性，需要通过最小化复合误差的影响来识别和减少测量误差。如果能够做到这一点，则可以提高收集数据的质量，然后得出更有意义的分析结果。同时，为了在计算机集成制造（CIM）环境中有效地进行尺寸检查，还迫切需要获得一种采样策略，该策略可用于指定一组测量点，这些测量点可导致准确的采样，同时最大程度地减少采样时间和成本。本文首先讨论了用于机器校准和尺寸测量的测量误差识别和减少问题。导出分析模型以访问和解耦两种类型的误差的复合效应，从而减少测量误差。然后，基于特征的Hammersley序列和分层采样方法被用来导出具有指定测量点的各种几何特征表面的采样策略。

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