基于机械臂的涡轮壳零件表面质量视觉检测

Surface Quality Visual Inspection of Turbine Shell Based on Robotic Arm

针对涡轮壳零件表面质量检测中存在的检测精度和效率低、实现难度大等难题,提出一种基于机械臂和机器视觉的表面质量检测方法。首先采用机械臂带动视觉系统运动到检测工位采集零件表面图像,然后对图像进行滤波、区域提取、特征提取和分割等处理,检测出涡轮壳表面的磕碰、凹坑等缺陷。通过现场试验结果表明,本系统单工位平均检测时间小于2 s,漏检率仅为0.4%,检测精度和效率均满足工程应用要求。

In order to solve the problems of low accuracy and efficiency,and high difficulty to realize in the surface quality detection of turbine shell parts,a method of surface quality detection based on robotic arm and machine vision is proposed.Firstly,the robotic arm is used to drive the vision system to the detecting work station to collect the surface image of the part.Then the image is processed by image filtering,detection region extraction,feature extraction and segmentation.Finally,the defects such as bumps and pits on the surface of the turbine shell are detected.The field test results show that the average detection time of the single work station is less than 2 s,and the missing rate of the detection is only 0.4%,which proves that the accuracy and efficiency of the system meet the requirements of engineering application.