Abstract
The measurement of hot rolled steel plates is an important part of steel-plate production lines. A structured light vision system for online measurement of steel-plate width is developed in this paper. A camera plane calibration algorithm is proposed to transform pixel points into 3D coordinate points, and an adaptive image processing range algorithm is proposed to improve the accuracy and speed of laser stripe image center extraction. The gray-gravity method is also improved according to the width range of steel plates produced by a production line. The distortion points in the image are identified, and the actual width of the board is measured. An experimental platform is built, the results of which show that the structured light vision system developed in this paper and the proposed laser stripe center extraction algorithm can provide accurate real-time online detection of steel-plate width.
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Funding
This research was funded by the National Key R&D Program of China for Robot Project (grant no. 2018YFB1308700), the Shanxi Provincial Key Core Technologies and Common Technology Special Projects (grant no. 2020XXX009), the Shanxi Provincial Special Project of Scientific and Technological Cooperation and Exchange (grant no. 202104041101031), Taiyuan University of Science and Technology Graduate Innovation Project (grant no. BY2022011), the Fund Program for the Scientific Activities of Selected Returned Reseas Professionals in Shanxi Province (grant no. 20220028).
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Li, Z., Qi, S., Zhang, M. et al. A Structured Light Vision Sensor for Online Measurement of Steel-Plate Width. Russ J Nondestruct Test 59, 601–610 (2023). https://doi.org/10.1134/S1061830923700407
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DOI: https://doi.org/10.1134/S1061830923700407