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Accurate measurement method for tube’s endpoints based on machine vision

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Abstract

Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube’s endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube’s endpoints based on machine vision is proposed. First, reflected light on tube’s surface can be removed by using photometric linearization. Then, based on the optimization model for the tube’s endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube’s endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint’s positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube’s endpoints without any surface treatment or any tools and can realize on line measurement.

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Authors and Affiliations

  1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China

    Shaoli Liu, Peng Jin, Jianhua Liu, Xiao Wang & Peng Sun

Authors
  1. Shaoli Liu
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  2. Peng Jin
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  3. Jianhua Liu
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  4. Xiao Wang
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  5. Peng Sun
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Corresponding author

Correspondence to Jianhua Liu.

Additional information

Supported by National Natural Science Foundation of China(Grant No. 51305031)

LU Shaoli, born in 1984, is currently a lecturer at Beijing Institute of Technology, China. She received her PhD degree from Tsinghua University, China, in 2012. Her main research interests include machine vision, on-line measurement, virtual assembly and image processing.

JIN Peng, born in 1987, is currently a PhD candidate at Beijing Institute of Technology, China. He received his master degree from North China Electricity Power University, China, in 2013. His research interests include machine vision and photogrammetry.

LIU Jianhua, born in 1977, is a professor, PhD advisor, and received his PhD degree in mechanical engineering from Beijing Institute of Technology, China. His scholastic interests include virtual assembly and machine vision. Now he has published over 60 research papers in virtual assembly.

WANG Xiao, born in 1989, is currently a PhD candidate at Beijing Institute of Technology, China. He received his bachelor degree from Beijing University of Chemical Technology, China, in 2014. His research interests include machine vision and photogrammetry.

SUN Peng, born in 1990, received his master degree from Beijing Institute of Technology, China, in 2015. His research interests include machine vision and photogrammetry.

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Liu, S., Jin, P., Liu, J. et al. Accurate measurement method for tube’s endpoints based on machine vision. Chin. J. Mech. Eng. 30, 152–163 (2017). https://doi.org/10.3901/CJME.2016.0516.066

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  • DOI: https://doi.org/10.3901/CJME.2016.0516.066

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