引用本文: 马宝, 马晓宝, 兰媛, 任玉成, 刘云飞, 马彦芝, 王荣军, 江连运. 基于结构光视觉的翘曲板材智能化压平建模研究[J]. 工程科学学报.
Modeling Research on Intelligent Flattening Leveling of Warped Plate Based on Structured Light Vision[J]. Chinese Journal of Engineering.
 Citation: Modeling Research on Intelligent Flattening Leveling of Warped Plate Based on Structured Light Vision[J]. Chinese Journal of Engineering.

## Modeling Research on Intelligent Flattening Leveling of Warped Plate Based on Structured Light Vision

• 摘要: 为提高中厚板压平质量和效率，实现压平过程智能化，本文采用机器视觉代替人工识别，实现对翘曲板材轮廓的精确识别，对点云识别和压平过程的相关工艺参数进行了建模研究。采用结构光相机获取翘曲板材点云数据，进行点云分割、点云去噪和点云精简等预处理，利用最小二乘法拟合重构了翘曲板材的三维曲面。根据三点弯曲矫平理论及微分几何的曲面理论，计算了三维曲面的翘曲曲率，优化确定了垫铁支点位置，得到了压下力和压下位移，实现金属板智能化压平过程的建模，进一步采用有限元法和实验进行了验证。理论和实验对比显示，重构的三维曲面与实际结果吻合，基于重构三维曲面数据计算的压平力与实测结果偏差大约为2.21%，初始平直度17.2 mm.m-1压平矫直后减小为3.28 mm.m-1，计算比较准确，方法可行，为中厚板压平智能化控制提供了理论模型。

Abstract: To improve the flattening leveling quality and efficiency for heavy plates and achieve intelligent flattening process, machine vision is used instead of manual recognition to achieve accurate recognition of the contour of warped plates in this article, and modeling research is conducted on the relevant process parameters of point cloud recognition and flattening process. A structured light camera was applied to obtain the point cloud data of the three-dimensional profile of warped heavy plates, and the point cloud data was preprocessed, such as denoising, segmentation and simplification. The three-dimensional surface of the warped plate was reconstructed by least square method. According to the three-point bending leveling theory and surface theory in differential geometry, the curvature of three-dimensional warped plate was calculated. Not only the fulcrum positions were optimized, but also the screw-down force and displacement were calculated, realizing the modeling for the intelligent flattening leveling of heavy plate. It was further verified by finite element method and experiments. The comparison between theories and experiments shows that the reconstructed three-dimensional surface is consistent with the actual warped heavy plate. The deviation between the calculated screw-down force based on the reconstructed three-dimensional surface and the measured force is about 2.21%, and the initial unevenness of 17.2 mm.m-1 is reduced to 3.28 mm.m-1, indicating the modelling is relatively accurate. This method is feasible and provides a theoretical model for intelligent flattening leveling of heavy plates.

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