计算机与现代化 ›› 2020, Vol. 0 ›› Issue (07): 121-126.doi: 10.3969/j.issn.1006-2475.2020.07.023

• 图像处理 • 上一篇    

基于机械臂的涡轮壳零件表面质量视觉检测

  

  1. (南京航空航天大学机电学院,江苏南京210016)
  • 出版日期:2020-07-06 发布日期:2020-07-15
  • 作者简介:张辉(1994-),男,山西汾阳人,硕士研究生,研究方向:计算机辅助测控,图像处理,E-mail: zhanghui6665@foxmail.com; 余厚云(1975-),男,江苏南京人,讲师,博士,研究方向:机械工程测量,机器视觉,E-mail: meehyyu@nuaa.edu.cn; 李克斌(1994-),男,硕士研究生,研究方向:计算机辅助测控,图像处理,E-mail: likebin@nuaa.edu.cn。
  • 基金资助:
    南京航空航天大学2019年教育教学改革研究项目(2019JG05140K)

Surface Quality Visual Inspection of Turbine Shell Based on Robotic Arm 

  1. (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Online:2020-07-06 Published:2020-07-15

摘要: 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。

关键词: 机械臂, 视觉检测, 涡轮壳, 图像处理

Abstract: 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.

Key words: robotic arm, visual inspection, turbine shell, image processing

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