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首页> 外文期刊>Journal of Mechanical Science and Technology >A novel geometric error modeling optimization approach based on error sensitivity analysis for multi-axis precise motion system
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A novel geometric error modeling optimization approach based on error sensitivity analysis for multi-axis precise motion system

机译:一种基于多轴精确运动系统误差灵敏度分析的新型几何误差建模优化方法

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摘要

In this paper, a novel error modeling approach for multi-DOF precise motion platform (MPMP) based on the error sensitivity analysis (ESA) is introduced. Sensitivity analysis (SA) is widely adopted for finding the essential parameters in system in mathematical way. This paper leads an error sensitivity analysis based on Monte Carlo thought into geometric error model. Through comparing the variance between the set of evaluated error and corresponding orientation deviations, a sensitive order with several sensitive levels can be developed. Conventional error modeling method only concentrates the systematic accuracy, while calculation efficiency is also important. Thus, this error modeling optimization approach based on sensitivity analysis is beneficial for the high-accuracy and high-quantity manufacture environments, which is more precise and effective. It also can save the computational volume for the calculation in error model. A case study of the new error modeling optimization procedure for six-axis stage in the alignment in optoelectronic packaging system (OPS) is carried out. The time-consumed results indicate that the optimized error model can not only keep high-accuracy requirement, but also improve the computational efficiency, which is informative and effective for MPMP motion control. For large number working situation, the optimized error model is available as well.
机译:本文介绍了一种基于误差灵敏度分析(ESA)的多-COF精确运动平台(MPMP)的新型误差建模方法。广泛采用敏感性分析(SA)以在数学方式中寻找系统的基本参数。本文引导了基于Monte Carlo思想到几何误差模型的误差敏感性分析。通过比较评估误差集和相应的方向偏差集之间的差异,可以开发具有多个敏感级别的敏感顺序。传统的误差建模方法仅集中系统准确性,而计算效率也很重要。因此,基于灵敏度分析的这种误差建模优化方法是有利于高精度和高量的制造环境,这更精确且有效。它还可以节省误差模型计算的计算量。执行了光电包装系统(OPS)对准六轴阶段新误差建模优化过程的案例研究。耗时的结果表明,优化的误差模型不仅可以保持高精度要求,而且还可以提高计算效率,这对于MPMP运动控制是一种信息性和有效的。对于大量工作情况,还提供了优化的错误模型。

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