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Damage localization method for building structures based on the interrelation of dynamic displacement measurements using convolutional neural network
Structural Control and Health Monitoring ( IF 4.6 ) Pub Date : 2020-06-11 , DOI: 10.1002/stc.2578
Byung Kwan Oh 1, 2 , Seol Ho Lee 3 , Hyo Seon Park 2, 3
Affiliation  

This study presents a damage localization method for building structures using dynamic displacement responses based on a convolutional neural network (CNN). The proposed method is based on the interrelation of dynamic displacement response measured from a building in a healthy state. Based on the interrelation constructed by CNN in advance, damaged stories are localized by investigating the discrepancy of dynamic responses between healthy and damaged states. Hence, this allows identification of the location of damage without the use of structural response labeled with damage information in the CNN training stage. Specifically, to construct the CNN presenting the interrelation of structural response of the building under the healthy state, dynamic displacement response is utilized in the both input and output of CNN. Then, when the building is suspected to be damaged, the displacement response measured from the building is used as an input data in the previously trained CNN. Based on the discrepancy between the output obtained by inputting damaged state response into CNN and the response in a healthy state, the location of damage in the building is identified. To express this discrepancy, indicators for damage localization are newly defined in this study, which can be calculated by healthy and damaged state responses with the trained CNN. Through the investigation of the distribution of those indicators extracted from multiple stories of the structure, the location of damage in building structures is identified. We validated the proposed method for identifying damage locations through a numerical study and an experimental study.

中文翻译:

基于卷积神经网络动态位移测量相关性的建筑结构损伤定位方法

这项研究提出了一种基于卷积神经网络(CNN)的使用动态位移响应的建筑结构损伤定位方法。所提出的方法基于从健康状态的建筑物测量的动态位移响应的相互关系。根据CNN预先构建的相互关系,通过调查健康状态和损坏状态之间动态响应的差异来定位损坏的故事。因此,这可以在不使用CNN训练阶段中标记有损伤信息的结构响应的情况下识别损伤的位置。具体地,为了构造呈现健康状态下建筑物的结构响应的相互关系的CNN,在CNN的输入和输出两者中利用动态位移响应。然后,当怀疑建筑物损坏时,将从建筑物测量的位移响应用作先前训练的CNN中的输入数据。根据通过将受损状态响应输入CNN所获得的输出与健康状态响应之间的差异,可以确定建筑物中受损的位置。为了表达这种差异,在这项研究中新定义了损害定位的指标,可以通过训练有素的CNN通过健康和受损状态响应来计算。通过调查从多个结构层中提取的那些指标的分布,可以确定建筑物结构中损坏的位置。我们通过数值研究和实验研究验证了提出的用于识别损坏位置的方法。从建筑物测得的位移响应在先前训练的CNN中用作输入数据。根据通过将受损状态响应输入CNN所获得的输出与健康状态响应之间的差异,可以确定建筑物中受损的位置。为了表达这种差异,在这项研究中新定义了损害定位的指标,可以通过训练有素的CNN通过健康和受损状态响应来计算。通过调查从多个结构层中提取的那些指标的分布,可以确定建筑物结构中损坏的位置。我们通过数值研究和实验研究验证了提出的用于识别损坏位置的方法。从建筑物测得的位移响应在先前训练的CNN中用作输入数据。根据通过将受损状态响应输入CNN所获得的输出与健康状态响应之间的差异,可以确定建筑物中受损的位置。为了表达这种差异,在这项研究中新定义了损害定位的指标,可以通过训练有素的CNN通过健康和受损状态响应来计算。通过调查从结构的多个楼层提取的那些指标的分布,可以确定建筑物结构中损坏的位置。我们通过数值研究和实验研究验证了提出的用于识别损坏位置的方法。
更新日期:2020-06-11
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