交通科学与工程2024,Vol.40Issue(2) :116-126.DOI:10.16544/j.cnki.cn43-1494/u.20211227240496

基于递归图和BP神经网络的桥梁损伤识别研究

Research on bridge damage identification based on recurrence plot and BP neural network

杨金易 孙兵 岳晓沛 殷新锋
交通科学与工程2024,Vol.40Issue(2) :116-126.DOI:10.16544/j.cnki.cn43-1494/u.20211227240496

基于递归图和BP神经网络的桥梁损伤识别研究

Research on bridge damage identification based on recurrence plot and BP neural network

杨金易 1孙兵 2岳晓沛 3殷新锋3
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作者信息

  • 1. 中铁上海设计院集团有限公司,上海 200000;长沙理工大学土木工程学院,湖南长沙 410114
  • 2. 四川公路桥梁建设集团有限公司,四川成都 610000
  • 3. 长沙理工大学土木工程学院,湖南长沙 410114
  • 折叠

摘要

为研究递归图和多层前馈(BP)神经网络在桥梁损伤识别方面的应用,以某大跨斜拉桥为例,采用ABAQUS有限元软件建立其三维模型,通过动力分析提取该三维模型的加速度曲线并进行递归图处理和BP神经网络分析.研究结果表明:递归图方法能够初步地识别主梁的损伤位置和损伤程度;BP神经网络分析能够精确识别主梁损伤的具体位置和损伤程度值,且识别准确率均大于85.0%.该方法可为类似桥梁工程的损伤识别提供借鉴.

Abstract

To study the damage identification of bridges using recursive graphs and BP neural networks,taking a certain large cable-stayed bridge as an example,a three-dimensional model was established using ABAQUS finite element software.The acceleration curve of this three-dimensional model was extracted through dynamic analysis and subjected to recursive graph processing and BP neural network analysis.The research results indicate that the recursive graph method can preliminarily identify the location and extent of damage to the main beam.The BP neural network analysis can accurately identify the specific location of damage to the main beam and the degree of damage,with an identification accuracy above 85.0%.This method can provide a reference for damage identification in similar bridge engineering projects.

关键词

递归图/BP神经网络/斜拉桥/有限元/损伤识别

Key words

recurrence plot/BP neural network/cable-stayed bridge/finite element/damage identification

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基金项目

国家自然科学基金资助项目(52078057)

湖南省自然科学基金创新研究群体项目(2020JJ1006)

出版年

2024
交通科学与工程
长沙理工大学

交通科学与工程

影响因子:0.444
ISSN:1674-599X
参考文献量21
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