A Method for Achieving Nanoscale Visual Positioning Measurement Based on Ultra-Precision Machining Microstructures.

Yihan Chen, Honglu Li, Zijian Zhu, Chenyang Zhao

Abstract read

In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

4 authors.

Yihan ChenSchool of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China.ORCID 0009-0003-1227-9205

Honglu LiSchool of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China.

Zijian ZhuSchool of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China.

Chenyang ZhaoSchool of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China.

Funding

CGN-HIT Advanced Nuclear and New Energy Research Institute 202205National Natural Science Foundation of China 52005135Young Elite Scientist Sponsorship Program By CAST YESS20210161

6 · The paper itself

Abstract

Microscopic visual measurement is one of the main methods used for precision measurements. The observation morphology and image registration algorithm used in the measurement directly affect the accuracy and speed of the measurement. This paper analyzes the influence of morphology on different image registration algorithms through the imaging process of surface morphology and finds that complex morphology has more features, which can improve the accuracy of image registration. Therefore, the surface microstructure of ultra-precision machining is an ideal observation object. In addition, by comparing and analyzing the measurement results of commonly used image registration algorithms, we adopt a method of using the high-speed SURF algorithm for rough measurement and then combining the robust template-matching algorithm with image interpolation for precise measurements. Finally, this method has a repeatability of approximately 54 nm when measuring a planar displacement of 25 μm.

Indexed as

image registration algorithmmicrostructureprecision measurement

Identifiers

PMID37512755

DOI10.3390/mi14071444

PMCPMC10385414

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.