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Adaptive reference updating for vibration-based structural health monitoring under varying environmental conditions

机译:自适应参考更新,用于在变化的环境条件下基于振动的结构健康监测

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In this paper, a novel adaptive principal component analysis is proposed for identifying structural damage under varying environmental conditions (i.e., both stationary and non-stationary conditions). The proposed method is based on an adaptive reference scheme in multivariate statistical analysis. One crucial advantage of the proposed method is the ability of generative learning to capture the intrinsic behavior of the normal condition. The proposed method is numerically tested with noise in measurement under environmental variations. Its performance is compared with conventional methods (i.e., the fixed reference scheme). The numerical study demonstrates the superior performance of the proposed method for structural damage detection. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在本文中,提出了一种新颖的自适应主成分分析方法,用于识别在变化的环境条件下(即静止和非静止条件下)的结构损伤。所提出的方法基于多元统计分析中的自适应参考方案。所提出的方法的一个关键优势是生成性学习能够捕获正常状况的内在行为的能力。所提出的方法在环境变化的条件下进行了数值测试,并带有噪声。将其性能与常规方法(即固定参考方案)进行比较。数值研究证明了该方法在结构损伤检测中的优越性能。 (C)2015 Elsevier Ltd.保留所有权利。

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