首页|基于深度学习的"微型灯塔工厂"物理和虚拟交互平台设计

基于深度学习的"微型灯塔工厂"物理和虚拟交互平台设计

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针对电子产品装配过程中存在的元器件精确定位难、细微缺陷检测慢、工程可视化程度低等技术难题,设计和搭建"微型灯塔工厂"工程示范厂房,采用Tecnomatix平台搭建微型灯塔工厂数字孪生体,解决制造过程中可视化程度低的问题;采用LabVIEW平台及深度学习算法实现CO-WORK及人机工程的快速检测和诊断,解决了生产运维难的问题;通过融合多尺度注意力权重信息的智能检测识别算法,解决了微型电子电路板检测速度慢和识别率低的难题.
Design of a"Micro Lighthouse Factory"Physical and Virtual Interaction Platform Based on Deep Learning
In view of the technical challenges such as difficulty in precise positioning of components,slow detection speed for minor defects,and low engineering visualization level in the assembly process of electronic products,the"Micro Lighthouse Factory"demon-stration factory was designed and built.The Tecnomatix platform was used to build a digital twin of a miniature lighthouse factory,to solve the problem of low visualization in the manufacturing process.The LabVIEW platform and deep learning algorithm were used to achieve rapid detection and diagnosis of CO-WORK and human-machine engineering,the problem of difficult production,operation and maintenance was solved.The intelligent detection and recognition algorithm integrating with multi-scale attention weight information was used to solve the problems of slow detection speed and low recognition rate in micro electronic circuit boards.

lighthouse factorydigital twindeep learning algorithm

白岩、孟祥民、迟盛元、李洪洲、邢吉生、王立奇

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北华大学机械工程学院,吉林吉林 132021

北华大学电气与信息工程学院,吉林吉林 132021

上海仪酷智能科技有限公司,上海 200000

灯塔工厂 数字孪生 深度学习算法

北华大学博士基金吉林省高教科研重点课题吉林省科技发展计划吉林省教育厅科学技术研究项目

JGJX2023C4920210203109SFJJKH20210035KJ

2024

机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
年,卷(期):2024.52(8)