基于模态数据的板损伤定位高斯过程回归模型

S. S. Kourehli
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引用次数: 0

摘要

类板结构在不同工程领域的应用越来越广泛。本文研究了一种基于高斯过程回归模型(GPR)的损伤检测方法。探地雷达是一种高效的学习机器,已广泛应用于不同的工程领域。识别损伤,用于训练探地雷达的受损结构的模态振型和固有频率。在MATLAB环境下进行了数值算例的有限元建模和高斯过程回归(GPR)模型。为验证该方法的有效性,对双固定支承板和悬臂板进行了研究。在其他工作中,使用悬臂板进行了比较研究。在上述数值算例中,固有频率受到噪声的污染。结果表明,该方法在只考虑有噪声的第一模态数据时效果良好。换句话说,GPR可以使用有限的样本数进行训练。
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Gaussian process regression model for damage localization in plates based on modal data
The applications of plate like structures in different fields of engineering are increasing. In this paper, a new damage detection method investigated based on Gaussian process regression model (GPR). GPR is an efficient learning machines which has been used in different fields of engineering. To identify damage, mode shaped and natural frequencies of damaged structures used to train GPR. Finite element modelling of numerical examples and Gaussian process regression (GPR) model are carried out within the MATLAB environment. To show the effectiveness of presented approach, a two-fixed supported plate and a cantilever plate was studied. In other work, a comparative study has been done using a cantilever plates. The natural frequencies were contaminated with noise in above mentioned numerical examples. Results reveal that the proposed method works well using the only first mode data which may be noisy. In other word, GPR can be trained using limited sample numbers for training.
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来源期刊
Journal of Rehabilitation in Civil Engineering
Journal of Rehabilitation in Civil Engineering Engineering-Building and Construction
CiteScore
1.60
自引率
0.00%
发文量
0
审稿时长
12 weeks
期刊最新文献
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