基于软计算的模型更新技术的发展

Yogesh Yadav, Ishwor Singh Saud
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引用次数: 0

摘要

结构模型不一定能足够准确地预测测量数据。因此,需要对这些模型进行更新,以更好地反映测量数据。本文介绍了计算智能技术来更新有限元模型。模型更新被表述为一个约束优化问题,并使用一种新开发的启发式算法——人工蜂群(Artificial Bee Colony, ABC)算法来求解。利用本文提出的模型更新公式,编写了MATLAB代码。利用8层框架结构的拟实验数据和ASCE三层基准结构的实验数据,对所提出的模型更新技术进行了数值模拟研究。本文的研究清楚地表明了所提出的基于计算智能的模型更新技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a Model Updating Technique Using Soft Computing
The structural models, do not necessarily predict the measured data sufficiently accurately. Because of this, there is a need for these models to be updated to better reflect the measured data. This paper introduces computational intelligence techniques to update finite element models. The model updating is formulated as a constrained optimization problem and solved using a recently developed meta-heuristic algorithm called Artificial Bee Colony (ABC) algorithm. A MATLAB code is developed using the model-updating formulations presented in this paper. Numerical simulation studies are carried out by solving for the proposed model updating technique by using pseudo-experimental data of an 8storey framed structure and also the experimental data of ASCE three storey benchmark structure. Studies presented in this paper clearly indicate the effectiveness of the proposed computational intelligence-based model updating technique.
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