基于光度立体视觉的钢轨焊缝打磨表面缺陷检测

doi:10.3901/JME.2024.24.011

摘要/Abstract

摘要： 针对钢轨焊缝表面缺陷自动化检测存在的难题，提出基于光度立体视觉的钢轨焊缝打磨表面缺陷检测方法。分析钢轨几何特征和表面形貌，设计钢轨多表面图像采集系统，实现多照明角度下光度图像序列采集，基于高性能光度立体算法实现打磨表面法向重建。分析打磨表面法向特性以及缺陷特征，基于法向图自适应提取打磨区域，剔除背景区域干扰；提出基于双阶段和旋转矩形提取的横向纹路缺陷检测算法以及基于灰度直方图双阈值分割的高度突变缺陷检测算法，克服打磨区域的噪声和伪缺陷干扰，有效解决缺陷特征提取和定位困难的问题。试验结果表明，提出的打磨表面缺陷检测算法优于现有的基于深度学习的缺陷检测算法，横向纹路检测准确率达到94.4%，漏检率低到0.84%；高度突变检测准确率达到92.64%，漏检率低到1.56%；系统整体运行效率为23.784 s每处钢轨焊接面，满足实际生产需求。

关键词: 光度立体, 缺陷检测, 钢轨焊缝打磨表面, 法向特征, 特征提取

Abstract: A multi-surface information acquisition system for rails is designed to realize the image sequence capture of photometric stereo under multiple illumination directions. Normal estimation of grinding surfaces is implemented based on an excellent photometric stereo method. By analyzing the characteristics of polished surface normals and defect features, an adaptive polishing region extraction method is first proposed to eliminate the interference of the background areas. Secondly, a horizontal pattern defect detection algorithm based on two-stage and rotating rectangle extraction and a height mutation defect detection algorithm based on dual-threshold segmentation of grayscale histogram is proposed, which overcomes the noise and pseudo defect interference and effectively solves the problem of difficulty in defect feature extraction and localization. Experimental results demonstrate the superiority of the proposed polished surface defect detection algorithm over existing deep learning-based defect detection algorithms. The detection accuracy of the horizontal pattern reaches 94.4%, with a low omission rate of 0.84%. The accuracy of height mutation detection is 92.64%, with a low omission rate rate of 1.56%. The overall operation efficiency of the system is 23.784 s per rail welding surface, which meets the actual production requirements.

Key words: photometric stereo, defect detection, rail weld grinding surface, normal features, feature extraction

中图分类号:

TP391

韦逍遥, 刘文渊, 王龄裕, 丁斌杰, 曹衍龙, 杨将新, 黄芳. 基于光度立体视觉的钢轨焊缝打磨表面缺陷检测[J]. 机械工程学报, 2024, 60(24): 11-24.

WEI Xiaoyao, LIU Wenyuan, WANG Lingyu, DING Binjie, CAO Yanlong, YANG Jiangxin, HUANG Fang. Surface Inspection of Polished Rail Welds Based on Photometric Stereo[J]. Journal of Mechanical Engineering, 2024, 60(24): 11-24.

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