轮胎缺陷视觉检测方法探析

Analysis of visual inspection methods for tire defects

随着自动化技术的发展,基于视觉的轮胎缺陷检测方法也越来越成熟,成功取代了人工缺陷检测。胎里气泡、轮胎裂纹、外缘尺寸偏差和胎面花纹沟槽深度偏差是四种常见的轮胎缺陷。由于各种缺陷特征不同,使现有的视觉轮胎缺陷检测方法并不完全适用于上述四种缺陷。针对以上问题,本文总结了二维视觉检测手段和三维点云检测手段对每种缺陷的应用,进而得知轮胎缺陷检测的具体情况,并探析了各种算法的优劣性。同时,在总结现有轮胎缺陷视觉检测方法的基础上,本文提出结合二维数据和三维数据的优势实现融合检测,为更准确高效的轮胎缺陷检测方法指出了发展方向。

With the development of automation technology, vision-based tire defect detection methods have become more and more mature, successfully replacing artificial defect detection. There are 4 common tire defects: inner bubble, tire crack, outer edge size deviation and tread groove depth deviation. Due to the different characteristics of various defects, the existing visual tire defect detection methods are not fully applicable to the above 4 defects. In view of the above problems, this paper summarizes the application of two-dimensional vision detection and three-dimensional point cloud detection to each kind of defect, and then knows the specific situation of tire defect detection, and analyzes the advantages and disadvantages of various algorithms. At the same time, on the basis of summarizing the existing visual inspection methods of tire defects, this paper proposes to combine the advantages of two-dimensional data and three-dimensional data to achieve fusion detection, and points out the development direction for more accurate and efficient tire defect detection methods.