Research on the geometric position error characteristics of the nanometer time-grating displacement sensor

Xu Ling; Zhaoxia Zhang; Junliang Dai; Tiantian Yuan

doi:10.1117/12.3036209

16 August 2024 Research on the geometric position error characteristics of the nanometer time-grating displacement sensor

Xu Ling, Zhaoxia Zhang, Junliang Dai, Tiantian Yuan

Author Affiliations +

Proceedings Volume 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024); 132302H (2024) https://doi.org/10.1117/12.3036209
Event: Third International Conference on Machine Vision, Automatic Identification and Detection, 2024, Kunming, China

Abstract

In order to create a kind of wide-ranged nano-grade accurate displacement measurement with low manufacturing costs, strong anti-interference capabilities and stable performance, the nanometer time-grating sensor based on AC electric field coupling has been researched. According to the working principle of the sensor, the effects of moving ruler and fixed ruler in the condition of various geometric position of nanometer on the accuracy of grating sensor has been researched. Firstly, through theoretical model analysis of the influence of geometric location to the sensor precision. Then, utilizing the air bearing linear guide of ultra-precision and high-precision six-dimension experiment mechanism to build an experiment platform and nano-grade sensors for precise quantitative experiments. The sensor geometry location parameter and error are obtained by using the theoretical model analysis combined with experiment. The experiments show that the nano-grade sensor range can measure 200mm,the accuracy can reach ±400 nm in geometric location deviation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xu Ling, Zhaoxia Zhang, Junliang Dai, and Tiantian Yuan "Research on the geometric position error characteristics of the nanometer time-grating displacement sensor", Proc. SPIE 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024), 132302H (16 August 2024); https://doi.org/10.1117/12.3036209

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available