蒙特卡罗模拟:一种评估复杂测量系统的工具

A. Harsch, C. Pruss, G. Baer, W. Osten
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引用次数: 3

摘要

在球面和自由曲面的测量中,缺少参考面是一个很大的挑战。测量系统的性能评估目前是通过循环测试来完成的。由于所用标本的真实形态尚不清楚,问题仍然存在:谁是正确的?在对倾斜波干涉仪的性能进行评估时,也会遇到这个问题。对于标定和测量都采用了复杂的算法。他们根据相移数据计算系统模型参数或表面误差。对不同结构或某些误差的影响进行分析评估是不可能的。GUM(测量不确定度表达指南)建议蒙特卡罗模拟作为不确定度评估的一种选择。它们适用于测量量与系统输入量之间的复杂关系。通过反复将输入量设置为给定范围内的随机值,并评估系统响应,可以生成统计相关数据。在这个贡献中,我们提出了一个基于蒙特卡罗的模拟环境,用于非零干涉测量的性能评估。利用所提出的仿真工具,可以进行虚拟实验,包括装置的标定。它们提供模拟测量数据-在倾斜波干涉仪模拟相位数据的情况下-考虑到许多可能的误差,如干涉仪误差,阶段误差和参考球体的误差。在此基础上,可以模拟给定样品的完整校准过程和测量。由于所有参数和误差都是已知的,因此可以将其结果与模拟真值进行比较,并可以对性能进行陈述。该工具也证明了有用的调查测量参数的影响,如样品的错位。
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Monte Carlo simulations: a tool to assess complex measurement systems
In the metrology of aspheres and freeforms, missing reference surfaces are a big challenge. The evaluation of the performance of measurement systems is currently done by round robin tests. Since the true form of the used specimens are unknown, the question still remains: who is right? This problem is also faced during the assessment of the performance of the Tilted Wave Interferometer. For both the calibration and measurement complex algorithms are applied. They calculate the system model parameters or the surface error from phaseshifting data. The analytical evaluation of different configurations or the influence of certain errors is impossible. The GUM (Guide to the Expression of Uncertainty in Measurement) proposes Monte Carlo simulations as an option for uncertainty evaluations. They are applicable for complex relationships between a measurand and the system’s input quantities. By repeatedly setting the input quantities to random values within a given range and evaluating the system response, statistically relevant data can be generated. In this contribution we present a Monte Carlo based simulation environment for the performance assessment of non-null interferometric measurements. By using the presented simulation tool, virtual experiments can be executed, including the calibration of the setup. They provide simulated measurement data - in the case of the Tilted Wave Interferometer simulated phase data – taking a number of possible errors, like interferometer errors, stage errors and errors of the reference spheres, into account. On this basis, complete calibration procedures and measurements on given samples can be simulated. Its result can be compared with the simulated truth, since all parameters and errors are known, and a statement about the performance can be made. This tool also proves useful for investigations on effects of measurement parameters such as misalignments of the sample.
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