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A machine vision–based radial circular runout measurement method

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Abstract

In order to overcome the disadvantages of contact measurement, time-consuming in traditional radial circular runout measurement, a non-contact measurement method based on machine vision technology is proposed in this paper. Using the image template matching and sub-pixel edge extraction techniques, the fine edge information of measured region is obtained. The rand sample consistency (RANSAC) algorithm is performed to filter the noise of edge data. Then, the least squares method is used for the parallel line fitting of two edges of measured region, and the reference axis of the shaft is gotten. The distance of measured point to the reference axis is defined as the radius at this rotating position, and the radius fluctuation at different rotational positions is the radial circular runout. The proposed method also allows random rotation of the measured shaft during the measuring process, and the high-precision-assisted rotation equipment is not essential, which enhances the convenience of the measuring equipment.

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Funding

This work was financially supported by the Guangxi Key Research and Development Program (grant no. AB22035048), Guangxi Natural Science Foundation (no. 2018JA170110), and Guangxi Science and Technology Base and Special Talents Program (2018AD19077).

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Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, 541004, China

    Wenjie Li, Fuquan Li, Zhansi Jiang, Haijian Wang, Yang Huang & Xingyu Gao

  2. Zhuhai Huaya Machinery Technology Limited Company, 519060, Zhuhai, 519000, China

    Wenjie Li, Meikuan Huang & Tengfei Li

  3. Guangxi Technological College of Machinery and Electricity, Nanning, 530007, China

    Qiaoxin Liang

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  1. Wenjie Li
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  2. Fuquan Li
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Correspondence to Xingyu Gao.

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Li, W., Li, F., Jiang, Z. et al. A machine vision–based radial circular runout measurement method. Int J Adv Manuf Technol 126, 3949–3958 (2023). https://doi.org/10.1007/s00170-023-11383-4

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