摘要
在工业智能制造行业中,质量缺陷检测工作面临一定的困难。在传统的物体表面缺陷检测中,人工目测不但过于主观,而且效率低下。基于机器视觉和深度学习的智能检测技术借助光学成像及图像处理等功能,能够准确计算待测物体的坐标信息,然后对物体实施自动定位并引导,同时完成自动装配。该检测技术具备非接触、无损伤、准确性高、连续工作时间长和高效率等优势,是目前智能制造检测较理想的方式。
In the industrial intelligent manufacturing industry,quality defect detection is faced with certain difficulties.In the traditional object surface defect detection,manual visual inspection is not only too subjective,but also inefficient.The intelligent detection technology based on machine vision and deep learningc an accurately calculate the coordinate information of the objcet to be measured with the help of optical imaging and image processing,and then implement automatic positioning and guidance of the object,and complete automatic assembly.The detection etchnology has the advantages of non-contact,no damage,high accuracy,long continuous working time and high efficiency,and has become the most ideal way of intelligent manufacturing detection.
作者
李锦棠
LI Jintang(Guangzhou Mechanical and Electrical Technician College,Guangzhou 510000)
出处
《现代制造技术与装备》
2023年第8期190-192,共3页
Modern Manufacturing Technology and Equipment
关键词
机器视觉
深度学习
智能制造
缺陷检测
machine vision
deep learning
intelligent manufacturing
defect detection
