Influence of background noise on autocollimator measurement precision and method for uncertainty source elimination

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2024-10-28 DOI:10.1016/j.measurement.2024.116036

Renpu Li , Zhaoyang Wang , Junsen Yuan , Jiwen Cui , Andrei Kulikov , Igor Konyakhin , Yongrui Guo , Yujia Huo , Dandan Wen , Ke Di

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引用次数: 0

Abstract

Reflection phenomenon of internal optical structure surface of the autocollimator will cause background noise to interfere with its imaging and localization results, thus reducing the measurement precision. The non-working surface reflection of the beam splitter is the main factor causing this uncertainty source. Using a polarized beam splitter cube to replace the original beam splitter and combining with other polarization devices can effectively suppress the influence of this uncertainty source on the goniometric accuracy of the autocollimator. In this paper, through the comparison experiment with the benchmark instrument, it is found that after eliminating the noise, the measurement accuracy along the X and Y axes is improved from less than 5.26″ to better than 2.69″, the resolution is improved from 2″ to approximately 1″, and the uncertainty of the systematic measurement is improved from 5.67″ to approximately 3.43″.

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背景噪声对自动准直仪测量精度的影响及不确定源消除方法

自动准直仪内部光学结构表面的反射现象会导致背景噪声干扰其成像和定位结果，从而降低测量精度。分光镜的非工作表面反射是造成这种不确定性的主要因素。使用偏振分光器立方体替代原有的分光器，并与其他偏振装置相结合，可以有效抑制该不确定源对自动准直仪测角精度的影响。本文通过与基准仪器的对比实验发现，消除噪声后，沿 X 轴和 Y 轴的测量精度由小于 5.26″ 提高到优于 2.69″，分辨率由 2″ 提高到约 1″，系统测量不确定度由 5.67″ 提高到约 3.43″。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.