Online structural performance monitoring method of tower crane based on digital twin

被引：0
|
作者：
Jia, Zhengnan [1 ]
Wang, Xin [1 ,2 ]
Gao, Shunde [1 ,2 ]
Sun, Tian [2 ]
Zhao, Xin [3 ]
Li, Zilu [3 ]
Song, Xueguan [1 ,2 ]
机构：
[1] School of Mechanical Engineering, Dalian University of Technology, Dalian,116024, China
[2] State Key Laboratory of High-Performance Precision Manufacturing, Dalian University of Technology, Dalian,116024, China
[3] Fushun Yongmao Construction Machinery Co., Ltd., Fushun,113000, China
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2024年 / 30卷 / 12期
基金：
中国国家自然科学基金;
关键词：
Neural networks - Towers;
D O I：
10.13196/j.cims.2023.0I03
中图分类号：
学科分类号：
摘要：
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. © 2024 CIMS. All rights reserved.
引用
收藏
页码：4468 / 4476
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