Surface flatness measurement of medium-thick plate based on Laser point cloud

被引:0
作者
Shi, Hao [1 ]
Deng, Gaoxu [1 ]
Li, Zhengnan [1 ]
Wang, Rongjun [1 ]
Ma, Lidong [1 ,2 ]
机构
[1] College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan
[2] Shanxi Key Laboratory of Intelligent Technology and System for Heavy Duty Equipment Operation, Taiyuan University of Science and Technology, Taiyuan
来源
Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2024年 / 32卷 / 16期
关键词
correlation mapping; flatness; gaussian fitting; Laser point cloud; plate shape detection;
D O I
10.37188/OPE.20243216.2464
中图分类号
学科分类号
摘要
In the metallurgical industry,medium and thick plate is one of the main products,and its flat⁃ ness is an important index to evaluate the quality of steel plate. The pressure leveling field also relies on manual measurement,which cannot accurately characterize the flatness of the plate. In order to improve the accuracy and efficiency of detection,a flatness measurement method based on machine vision was proposed. Based on the high-precision three-dimensional visual scanning technology,combined with the Gaussian fitting algorithm,the Gaussian coefficient was used to construct the eigenvalue,and the mapping relationship between the Gaussian eigenvalue and the actual bending height of the plate was established. The reference plane was constructed,and the distance between the point cloud coordinate value and the reference plane was calculated. The RGB color model was used to draw the shape cloud diagram. On this basis,the position of the pressure leveling pad was given. Experimental results indicate that the calculation error of the proposed method is not greater than 0. 3 mm,which can realize the measurement of the central bulge or the edge warping steel plate. At the same time,the shape cloud diagram reflects the shape distribution and the position of the plate. This measurement method can accurately measure the bending of medium-thick plates and provide data support for pressure leveling. © 2024 Chinese Academy of Sciences. All rights reserved.
引用
收藏
页码:2464 / 2473
页数:9
相关论文
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