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作 者:张祎彤 陈奎 张宇坤 Zhang Yitong;Chen Kui;Zhang Yukun(Xi’an Aviation Computing Technology Research Institute,Xi’an Shaanxi 710065,China)
机构地区:[1]中国航空工业集团公司西安航空计算技术研究所,陕西西安710065
出 处:《山西电子技术》2023年第4期71-73,81,共4页Shanxi Electronic Technology
摘 要:在国家工业制造领域全面智能化转型的过程中,质量检测方式正在由人工目检、传统机器视觉向AI视觉检测的方式转变。AI视觉检测使用智能算法赋能3D-AOI检测设备,以深度学习算法为核心并面向多种质量缺陷形态进行统一建模,构建大规模的工艺缺陷知识库。基于对主流3D-AOI设备的深度使用与研究,分别从上板运动机构、图像采集系统和缺陷检测算法三个部分对AI视觉检测技术的特点、先进性和应用范围进行详细阐述与对比,充分论证智能化3D-AOI技术对检验流程的优化方案,在提高质量检测精度效率的同时减少人工依赖。In the process of comprehensive and intelligent transformation of national industrial manufacturing,the quality inspection method is changing from manual and traditional machine vision to artificial intelligence(AI)vision.AI vision inspection uses intelligent algorithm to empower three dimensional automatic optical inspection(3D-AOI)equipment,takes deep learning algorithm as the core and conducts unified modeling for multiple defect forms to build a large-scale knowledge base of process defects.Based on the application and research of mainstream 3D-AOI equipment,this paper elaborates and compares the characteristics,progressiveness and application scope of AI visual inspection technology from three parts:charging control mechanism,image acquisition system and defect detection algorithm.it fully demonstrates the optimization scheme of intelligent 3D-AOI technology for inspection process,which could improve the accuracy and efficiency of quality inspection and reduce the manual dependence.
分 类 号:TP242.62[自动化与计算机技术—检测技术与自动化装置]
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