Study on a method for evaluating geometric tolerances based on monocular rotational vision

WU Enqi; YU Guibang; LI Qi; LU Ding

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Study on a method for evaluating geometric tolerances based on monocular rotational vision

Optical Sensing and Measurement | 更新时间：2026-07-23

- Study on a method for evaluating geometric tolerances based on monocular rotational vision
- OPTICAL TECHNIQUE Vol. 52, Issue 4, Pages: 452-458(2026)
- 作者机构：
  
  上海理工大学机械工程学院，上海 200093
- 作者简介：
- 基金信息：
- DOI：
  CLC： TH74
- Received：12 April 2026，
  
  Revised：2026-05-26，
  
  Accepted：08 June 2026，
  
  Online First：23 July 2026，
  
  Published：20 July 2026
- 稿件说明：
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吴恩启,于贵邦,刘琪等.基于单目旋转视觉的几何公差评定方法研究[J].光学技术,2026,52(04):452-458.

WU Enqi,YU Guibang,LI Qi,et al.Study on a method for evaluating geometric tolerances based on monocular rotational vision[J].OPTICAL TECHNIQUE,2026,52(04):452-458.
吴恩启,于贵邦,刘琪等.基于单目旋转视觉的几何公差评定方法研究[J].光学技术,2026,52(04):452-458. DOI：

WU Enqi,YU Guibang,LI Qi,et al.Study on a method for evaluating geometric tolerances based on monocular rotational vision[J].OPTICAL TECHNIQUE,2026,52(04):452-458. DOI：

摘要

针对单目相机在几何公差测量中面临的深度信息缺失与抗噪能力弱等问题，提出了一种基于单目旋转视觉结构的几何公差综合测量系统。在算法层面，为突破工业图像欠采样导致的细节丢失限制，构建了融合SwinIR超分辨率网络的亚像素边缘提取框架；针对微小离群点干扰大量点云计算负荷，提出融合信任点机制与同伦法的改进迭代重加权最小二乘法，在加速非线性收敛的同时显著提升了形状拟合的精度；进一步利用单应变换建立多视角特征匹配约束，并推导双目视锥交线算法，从底层投影机理上消除了透视畸变引发的空间圆心漂移，重建了高精度的空间几何特征参数。实验结果表明，系统对定位块与阶梯轴的各项几何公差测量结果与三坐标测量机高度一致，绝对误差稳定控制在0.04 mm以内。研究基于单目旋转视觉结构实现了三维特征重建与多类几何公差综合评定，在保证较高测量精度的同时提升了检测效率，可为精密制造产线在线质量控制提供有效方案。

Abstract

To address the lack of depth information and weak noise resistance of monocular cameras in geometric tolerance measurement

a comprehensive geometric tolerance measurement system based on monocular rotational vision is proposed. At the algorithm level

a sub-pixel edge extraction framework integrated with the SwinIR super-resolution network is constructed. It is used to overcome the loss of image details caused by undersampling in industrial images. To reduce the influence of small outliers and the computational burden in large-scale point cloud processing

an improved iterative reweighted least squares method is proposed. This method combines a trust-point mechanism with the homotopy method. It accelerates nonlinear convergence and significantly improves the accuracy of shape fitting. Furthermore

homography transformation is used to establish multi-view feature matching constraints. A stereo view-cone intersection algorithm is also derived. This method eliminates the spatial circle-center drift caused by perspective distortion from the underlying projection mechanism. It also reconstructs high-precision spatial geometric feature parameters. Experimental results show that the geometric tolerance measurements of positioning blocks and stepped shafts are highly consistent with those obtained by a coordinate measuring machine. The absolute errors are stably controlled within 0.04 mm. This study realizes three-dimensional feature reconstruction and comprehensive evaluation of multiple geometric tolerances based on monocular rotational vision. It improves inspection efficiency while maintaining high measurement accuracy. It can provide an effective solution for online quality control in precision manufacturing production lines.

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references

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