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Multi‐scale model updating of a transmission tower structure using Kriging meta‐method
Author(s) -
Wang F.Y.,
Xu Y.L.,
Zhan S.
Publication year - 2017
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1952
Subject(s) - kriging , scale (ratio) , transmission tower , tower , metamodeling , scale model , computer science , transmission (telecommunications) , key (lock) , algorithm , mathematical optimization , engineering , structural engineering , machine learning , mathematics , telecommunications , physics , computer security , quantum mechanics , programming language , aerospace engineering
Summary A multi‐scale model is often constructed using different finite elements and consists of a global scale model for the structural system and a few local scale models for critical structural components so that the multi‐scale simulation can concurrently exhibit both global performance and local behavior of the structure. To ensure the multi‐scale model can best represent the real structure, multi‐scale model updating technique shall be developed accordingly. This paper thus presents a multi‐scale model updating method for a transmission tower structure using the Kriging meta‐model that actually is a surrogate for the multi‐scale model. Firstly, the multi‐scale model of a transmission tower is established by using beam elements to simulate global structure and solid elements to simulate local joints with bolt connections. Secondly, the multi‐objective optimization problem that involves multiple objective functions is established to update key parameters of the multi‐scale model so that the errors between the measured and predicted structural dynamic characteristics and multi‐scale responses can be minimized. To improve the computational efficiency and accuracy of optimization, the Kriging meta‐method is used to find the updated key parameters of the tower after a comparison with other meta‐methods is made. Finally, the proposed method is applied to a physical transmission tower model, which has been tested in a laboratory, to demonstrate the feasibility and accuracy of the proposed model‐updating method. The updated results show that the proposed updating method can improve the accuracy of the multi‐scale model of the tower in both global and local structural responses.