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作 者:贾政楠 王欣[1,2] 高顺德[1,2] 孙田 赵欣 李子陆 宋学官 JIA Zhengnan;WANG Xin;GAO Shunde;SUN Tian;ZHAO Xin;SONG Xueguan(School of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China;Fushun Yongmao Construction Machinery Co.,Ltd.,Fushun 113000,China;State Key Laboratory of High-Performance Precision Manufacturing,Dalian University of Technology,Dalian 116024,China)
机构地区:[1]大连理工大学机械工程学院,辽宁大连116024 [2]大连理工大学高性能精密制造全国重点实验室,辽宁大连116024 [3]抚顺永茂建筑机械有限公司,辽宁抚顺113000
出 处:《计算机集成制造系统》2024年第12期4468-4476,共9页Computer Integrated Manufacturing Systems
基 金:国家重点研发计划资助项目(2018YFB1700704);国家自然科学基金资助项目(52075068)。
摘 要:为了保证塔式起重机安全作业,提高塔式起重机的智能化水平,提出了基于数字孪生的塔式起重机结构性能监测方法。首先,根据塔式起重机的运行特点和实时监控的要求,提出了塔式起重机数字孪生框架,详细阐述了各部分的功能;其次,通过建立运动模型实现了塔式起重机实时状态映射、借助网格简化技术构建了塔机虚拟模型、利用人工神经网络技术实现塔式起重机的结构性能在线预测;最后,以STL760动臂塔式起重机为例,建立了动臂塔式起重机数字孪生系统,验证了塔式起重机数字孪生框架的可行性,证明了预测结果有较快的分析速度和较高的准确性,为塔机智能化管理提供了新思路。To ensure the safe operation and improve the intelligent level of tower crane,a monitoring method of tower crane structure performance based on digital twin was proposed.According to the operation characteristics of tower crane and the requirement of real-time monitoring,the digital twin frame of tower crane was put forward,and the functions of each part were elaborated in detail.The real-time state mapping of the tower crane was realized by establishing the motion model,the virtual model of the tower crane was constructed by using the grid simplification technology,and the structural performance of the tower crane was predicted online by using the artificial neural network technology.Taking STL760 boom tower crane as an example,the digital twin system of boom tower crane was established,which verified the feasibility of digital twin frame of tower crane,proved that the prediction results had high analysis speed and accuracy,and provided a new idea for the intelligent management of tower crane.
分 类 号:TH213.3[机械工程—机械制造及自动化]
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