热态重轨表面缺陷在线检测方法及关键技术

针对热态重轨轧制时表面缺陷检测困难,研制了一种基于机器视觉的热态重轨表面缺陷实时检测系统。根据重轨辐射和光照特性进行了光学选型,利用多个线阵CCD相机并行多角度采集得到热态重轨全表面图像,通过图像自适应预处理得到满足缺陷检测要求的图像。针对重轨表面缺陷结构连续性引起的传统图像分割算法难以实现缺陷提取的情况,提出了图像像素线线间相关度互检验算法,并利用像素去差异化和方差统计运算提取完整缺陷,此方法在该类问题的识别效果上明显优于传统边缘识别算法。系统在某集团轨梁厂的实际应用中取得了良好的效果。

The key technology research of on-line surface inspection for hot heavy rail

To overcome the detection difficulties of the surface defects when milling a hot heavy rail,a suite of detection system for on-line surface defect is developed. To select optical environment according to radiation of heavy rail and characteristics of light,use multi-linear array CCD cameras to parallel multi-angle collect images of whole surface of hot heavy rail,and obtain images through an image adaptive preprocessing to meet requirements of defect detection. For the condition that the defects extracting causing by continuity of the surface defects of hot heavy rail is hard to realize through traditional image segmentation, an examining algorithm of image relevance between pixel lines is proposed, using pixel de-differentiation and statistical variance operations to extract defect. This algorithm is demonstrated to be better than traditional edge detection,and the system has achieved good results in the practical application of a rail beam plant.