基于动态视觉标定的大尺寸钢板平面度在线检测方法

程颖; 秦浩森; 毕德学; 商腾达

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基于动态视觉标定的大尺寸钢板平面度在线检测方法

光学传感与测量 | 更新时间：2026-03-24

- 基于动态视觉标定的大尺寸钢板平面度在线检测方法
- An online detection method for the flatness of large-sized steel plates based on dynamic visual calibration
- 光学技术 2026年52卷第2期页码：230-235
- 作者机构：
  
  天津科技大学机械工程学院天津市轻工与食品机械装备集成设计与在线监控重点实验室，天津 300457
- 作者简介：
  
  程颖（1982— ），女，副教授，博士，从事光学自由曲面设计、机器视觉检测方面的研究。chengyingcd@163.com
  秦浩森（2000— ），男，硕士研究生，从事机器视觉检测方面的研究。15598750997@163.com
- 基金信息：
  
  国家自然科学基金项目资助(61705166);天津市教委科研计划项目(2017KJ019);天津市轻工与食品工程机械装备集成设计与在线监控重点实验室（天津科技大学）开放基金资助项目(2024LIMFE04);天津市计量科技项目(2024TJMT031)
- DOI：
  中图分类号： TP751.1;TG83
- 收稿：2025-10-22，
  
  修回：2025-12-26，
  
  纸质出版：2026-03-20
- 稿件说明：
移动端阅览
程颖,秦浩森,毕德学等.基于动态视觉标定的大尺寸钢板平面度在线检测方法[J].光学技术,2026,52(02):230-235.

CHENG Ying,QIN Haosen,BI Dexue,et al.An online detection method for the flatness of large-sized steel plates based on dynamic visual calibration[J].OPTICAL TECHNIQUE,2026,52(02):230-235.
程颖,秦浩森,毕德学等.基于动态视觉标定的大尺寸钢板平面度在线检测方法[J].光学技术,2026,52(02):230-235. DOI：

CHENG Ying,QIN Haosen,BI Dexue,et al.An online detection method for the flatness of large-sized steel plates based on dynamic visual calibration[J].OPTICAL TECHNIQUE,2026,52(02):230-235. DOI：

摘要

为了消除大尺寸钢板平面度动态高精度测量中，滚筒传输速度非均匀波动引发的扫描畸变及长期负载下滚筒引入的系统误差，构建了基于双目线激光与非编码视觉标记的运动补偿检测系统。核心创新是在钢板表面布设非编码视觉标记点，集成亚像素级角点追踪与速度矢量实时解算算法，实现钢板运动速度高精度动态标定，消除线扫描对机械传输速度稳定性的依赖。实验表明，系统在5Hz的采样频率下

平面度检测误差稳定在0.2mm以内；通过滚筒磨损仿真模型与实验验证，滚筒形变达6mm的极端工况，测量误差仍≤0.2mm，鲁棒性良好。三维点云处理中，最小二乘法拟合基准平面较主成分分析法，可将最终测量误差减低20％。方法为工业现场大尺寸板材动态、高精度、高鲁棒性在线检测提供了可靠的解决方案。

Abstract

To eliminate the scanning distortion caused by the non-uniform fluctuation of the roller transmission speed and the system error introduced by the rollers under long-term load in the dynamic high-precision measurement of the flatness of large-sized steel plates

a motion compensation detection system based on binocular line laser and non-coded visual markers was constructed. The core innovation lies in the deployment of non-coded visual marker points on the surface of the steel plate

integrating sub-pixel corner tracking and real-time speed vector calculation algorithms to achieve high-precision dynamic calibration of the steel plate's movement speed

thereby eliminating the dependence of line scanning on the stability of mechanical transmission speed. Experiments show that the system's flatness detection error is stable within 0.2mm at a sampling frequency of 5Hz. Through the simulation model of roller wear and experimental verification

even in the extreme condition where the roller deformation reaches 6mm

the measurement error is still ≤0.2mm

demonstrating good robustness. In the processing of three-dimensional point clouds

the least squares method for fitting the reference plane can reduce the final measurement error by 20% compared to the principal component analysis method. This method provides a reliable solution for the dynamic

high-precision

and highly robust online detection of large-sized plates in industrial fields.

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references

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