激光淬火加工质量视觉检测系统研究

Visual inspection system for laser quenching quality of rail

摘要:

针对金属表面激光离散淬火质量检测的需求,基于OpenCV设计了一种淬火斑尺寸测量和表面纹理检测的视觉检测系统。深入研究了相关图像处理算法,对Canny边缘检测算法进行了改进,实现了图像轮廓的选择性提取,得到了激光淬火斑连通域的几何尺寸,采用灰度共生矩阵计算淬火斑纹理信息。并根据三种不同能量输入背景下进行激光离散淬火产生的淬火斑,提出了一种双阈值判定方法来实现其质量检测,平均检测用时为10.1ms,检测准确率在92.5%以上。

Abstract:

Aiming at the requirement of laser dispersed quenching (LDQ) quality inspection for metal surface, a visual inspection system based on OpenCV was designed to measure the quenched spot size and detect the surface texture. In-depth study of the relevant image processing algorithms, Canny edge detection algorithm has been improved to achieve the selective extraction of image contours, the geometric dimensions of the laser quenching connected domain are obtained, and the gray level co-occurrence matrix is used to calculate the texture information of quenched spot. According to the quenched spots produced by LDQ under three different energy input backgrounds, a dual threshold determination method was proposed to realize the quality inspection. The average detection time was 10.1ms, and detection accuracy was above 92.5%.