摘要
针对电解铝电解槽维护管理的现场数据交互难题,提出了一种基于混合现实的电解槽设备辅助管理系统。采用卷积神经网络模型识别电解槽号,以电解槽号为纽带获取电解槽后台海量生产数据,应用HoloLens2混合现实平台实现虚拟数据与电解槽实体融合,基于后台历史数据的可视化辅助员工设备管理及数据决策。该实现方法可以为相同应用场景提供参考。
Aiming at the problem of onsite data interaction in the maintenance and management of aluminum electrolytic cells,an auxiliary management system based on mixed reality is proposed.The convolutional neural network model is applied to identify the number of aluminum electrolytic cells,the electrolytic cell number is used as an important tie to obtain massive backend data of the electrolytic cells,the HoloLens2 mixed reality platform is utilized to realize the integration of virtual data and the electrolytic cell entity,and the the visualization of background historical data is applied to assist employees with equipment management and data decision.By doing so,references can be provided for the same application scenarios by the implementation methods mentioned in this paper.
作者
吴昊鹏
班剑锋
李建华
WU Haopeng;BAN Jianfeng;LI Jianhua(School of Mechanical and Electronical Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Chalco Steering Intelligent Technology Co.,Ltd.,Changsha 410006,China)
出处
《机械与电子》
2022年第3期40-44,共5页
Machinery & Electronics
基金
国家重点研发计划项目(2020YFB1713600)。
关键词
铝电解槽
混合现实
槽号识别
卷积网络
aluminum reduction cell
mixed reality
digital recognition
convolutional network
