The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model

Jiangpeng Shu; Ziye Zhang; Ignacio Gonzalez; Raid Karoumi

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The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model

机译：人工神经网络和列车振动的损伤检测方法在简化铁路桥梁模型中的应用

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摘要

A damage detection algorithm based on Artificial Neural Network (ANN) was implemented in this study using the statistical properties of structural dynamic responses as input for the ANN. Sensitivity analysis is performed to study the feasibility of using the changes of variances and covariances of the dynamic responses of the structure as input to the ANN. A finite element (FE) model of a one-span simply supported beam railway bridge was developed in ABAQUS", considering both single damage case and multi-damage case. A Back-Propagation Neural Network (BPNN) was built and trained to perform damage detection. A series of numerical tests on the FE model with different vehicle properties was conducted to prove the validity and efficiency of the proposed approach. The results reveal not only that the ANN, together with the statistics, can correctly estimate the location and severity of damage, but also that the identification of the damage location is more difficult than that of the damage severity. In summary, it is concluded that the use of statistical property of the structural dynamic responses as damage index along with the Artificial Neural Network as tool for damage detection for an idealized model of a bridge is reliable and effective.

机译：本研究基于结构动力响应的统计特性作为人工神经网络的输入，实现了基于人工神经网络（ANN）的损伤检测算法。进行敏感性分析以研究使用结构动力响应的方差和协方差变化作为ANN输入的可行性。考虑到单损伤情况和多损伤情况，在ABAQUS中开发了一个单跨简支梁铁路桥梁的有限元模型。对具有不同车辆特性的有限元模型进行了一系列数值测试，证明了该方法的有效性和有效性，结果表明，不仅人工神经网络和统计数据还可以正确地估计出车辆的位置和严重性。总的来说，结论是，利用结构动力响应的统计特性作为损伤指标，并结合人工神经网络作为工具来进行损伤识别。理想桥梁模型的损伤检测是可靠且有效的。

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来源
《Engineering Structures》 |2013年第7期|408-421|共14页
作者
Jiangpeng Shu; Ziye Zhang; Ignacio Gonzalez; Raid Karoumi;
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作者单位

Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;

Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;

Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;

Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Damage detection; Railway bridge; Dynamic response; Statistical property; Artificial Neural Network (ANN);

机译：损坏检测;铁路桥梁动态响应;统计属性;人工神经网络（ANN）;

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7. The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model [O] . Jiangpeng Shu, Ziye Zhang, Ignacio Gonzalez, 2013

机译：一种使用人工神经网络的损伤检测方法在简化铁路桥模型上进行射出振动的应用

The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model

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