基于Qt的钢管壁厚在线检测软件设计

针对目前钢管端面壁厚的测量多采用人工抽检的方式，从而导致测量效率低、精度低、测量数据少的情况，对机器视觉测量技术进行了研究。基于机器视觉，设计钢管壁厚在线检测系统。通过对相机进行标定，获得图像像素值与实际值之间的关系，使用相机采集钢管端面图像，对采集得到的图像进行图像预处理、边缘特征点提取等操作；改进RHT圆检测算法，完成钢管端面圆形轮廓的检测，进而实现对钢管端面壁厚的测量。为了便于操作，基于Qt跨平台开发框架设计了钢管壁厚检测系统人机交互界面软件。结果表明：该系统具有良好的稳定性，检测误差约为0.1 mm,可以高效地完成壁厚检测任务。

Research on Online Detection for the Wall Thickness of the Steel Pipe Based on Qt

In view of the actual situation of low measurement efficiency,low precision and little metering data caused by manual sampling detection for steel pipe end wall thickness,the machine vision measurement technology was studied,the online detection system of the steel pipe wall thickness based on machine vision was designed.The relationship between the image pixel value and the actual value was obtained by calibrating the camera.The images of steel pipe end captured by the camera were processed to image preprocessing,edge feature point extraction and other operations.The RHT circle detection algorithm was improved to detect the round profile of the steel pipe end surface,and the wall thickness of the steel pipe was measured.In order to facilitate the operation,the human-machine interface software of steel pipe wall thickness detection system was designed based on Qt cross-platform development framework.The test result shows that the system is of good stability,with measuring error of about 0.1 mm,which can efficiently complete the wall thickness detection task.