Artificial intelligence, digital twins and the future of bridge management

被引：0
|
作者：
Lorenzen S.R. [1 ]
Berthold H. [1 ]
Rupp M. [1 ]
Schmeiser L. [1 ]
Schneider J. [1 ]
Thiele C.-D. [2 ]
Brötzmann J. [2 ]
Rüppel U. [2 ]
机构：
[1] Institut für Statik und Konstruktion, Technische Universität, Darmstadt
[2] Institut für Numerische Methoden und Informatik im Bauwesen, Technische Universität, Darmstadt
来源：
VDI Berichte | 2022年 / 2022卷 / 2379期
关键词：
Compendex;
D O I：
10.51202/9783181023792-109
中图分类号：
学科分类号：
摘要：
The ZEKISS research project, funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI), investigates the combination of direct Structural Health Monitoring (SHM) with indirect SHM for railway bridges and vehicles using Artificial Intelligence (AI) methods, multi-body simulations and finite element model update. Direct SHM refers to the monito-ring/evaluation of the structure with measurements on the structure. Indirect SHM, on the other hand, uses measurements on structures that interact with the structure being monito-red (train measures bridge / bridge measures train). The presentation will give a brief introduction to AI and SHM. Finally, the concept of the Digital Twin for bridge monitoring will be presented in order to show how a uniform data management system for the entire bridge infrastructure network can be created on this basis. In the future, this will enable the imple-mentation of a self-improving system in the context of predictive maintenance. © 2022, VDI Verlag GMBH. All rights reserved.
引用
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页码：109 / 124
页数：15
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