摘要
为解决干散货码头大型设备日常巡检人员安全风险高、劳动强度大、作业效率低,以及状态检测系统智能化水平不高、设备运行数据难以有效利用、设备交叉作业安全隐患大等问题,结合港口实际工况,借助数字孪生、人工智能、视觉识别、北斗定位等信息化技术,研发大型设备状态检测及安全防护系统,改善巡检作业环境,减少设备维保作业量,提高干散货码头生产作业安全性。
To address issues such as high safety risks,heavy labor intensity,and low operational efficiency in daily inspections of large equipment at dry bulk terminals,as well as the low level of intelligence in condition monitoring systems,ineffective utilization of equipment operation data,and significant safety hazards in cross-equipment operations,this study integrates digital twin,artificial intelligence,visual recognition,and Beidou positioning technologies to develop a condition monitoring and safety protection system for large equipment.The system improves the inspection environment,reduces equipment maintenance workload,and enhances the safety of production operations at dry bulk terminals.
作者
杨廷帅
杨洪锡
赵栋
王玉琪
孙明帅
Yang Tingshuai;Yang Hongxi;Zhao Dong;Wang Yuqi;Sun Mingshuai(Qiangang Branch,Qingdao Port International Co.,Ltd.)
出处
《港口装卸》
2025年第2期42-43,47,共3页
Port Operation
关键词
干散货码头
大型设备
状态检测
数字孪生
安全防护
dry bulk terminal
large equipment
condition monitoring
digital twin
safety protection
