基于小波神经网络方法的桥梁结构损伤识别研究

肖书敏; 闫云聚; 姜波澜

doi:10.3879/j.issn.1000-0887.2016.02.004

基于小波神经网络方法的桥梁结构损伤识别研究

doi: 10.3879/j.issn.1000-0887.2016.02.004

¹西北工业大学力学与土木建筑学院, 西安 710129;²广东省建工设计院有限公司, 广州 510000

基金项目: 高校博士学科点专项科研基金（优先发展领域）(20126102130004);中央高校基本科研业务费专项资金资助(3102015BJ-MYZ13)

详细信息

作者简介:
肖书敏(1991—），女，硕士生(E-mail: 1037270561@qq.com);闫云聚(1954—)，男，教授，博士，博士生导师(通讯作者. E-mail: yjyan_2895@nwpu.edu.cn).

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出版历程
- 收稿日期: 2015-07-20
- 修回日期: 2015-10-23
- 刊出日期: 2016-02-15

Damage Identification for Bridge Structures Based on the Wavelet Neural Network Method

¹School of Mechanics and Civil Engineering & Architecture,Northwestern Polytechnical University, Xi’an 710129, P.R.China;²Guangdong Construction Engineering Design Institute Co., Ltd., Guangzhou 510000, P.R.China

摘要

摘要: 桥梁结构在服役期间会承受复杂的荷载，长期使用会不可避免地出现各种损伤。若这些损伤不能被及时发现和适当处理，将有可能造成严重的事故。因此，桥梁结构的局部小损伤识别对于其及时检修有重要意义。通常，损伤结构的全局动态特性测试可能对局部的结构损伤不敏感，特别是对小损伤，这就需要从结构动态响应信号中提取对损伤更敏感的特征量。建立了桥梁结构的有限元模型并进行动力特性分析；采用小波包分析方法处理结构动态响应信号以构造结构损伤指标，并结合结构损伤指标和人工神经网络方法进行桥梁结构的损伤定位.
- 结构损伤定位 /
- 损伤指标 /
- 小波包能量差 /
- 损伤大样本空间 /
- 人工神经网络
Abstract: Bridge structures will suffer complex loading environment during their service, and inevitable damages of structures may occur in long term service. If a damage can’t be found in time and treated properly, it may cause serious accidents. Therefore, the local small damage identification for bridge structures is of great significance for the timely maintenance. Generally, the measured global dynamic properties of a damaged structure are not sensitive enough to the local structural damages, especially to small damages, thus, it is necessary to extract more sensitive feature information to structural damages from the structural dynamic response signals. The finite element model of a bridge structure was established, and the dynamic characteristics were analyzed. The wavelet packet analysis was used to process the structural dynamic response signals and the structural damage index was presented. Then the damages of the bridge structure were positioned according to the damage index with the artificial wavelet neural network method. The results show that the wavelet packet energy change ratio makes an effective damage index; the properly trained neural network can fairly precisely position the bridge structural damages in the numerical test; the higher the damage degree is, the lower the positioning error comes.
- structural damage positioning /
- damage index /
- wavelet packet energy change /
- damage sample space /
- artificial neural network

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参考文献(13)

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基于小波神经网络方法的桥梁结构损伤识别研究

doi: 10.3879/j.issn.1000-0887.2016.02.004

作者简介:
肖书敏(1991—），女，硕士生(E-mail: 1037270561@qq.com);闫云聚(1954—)，男，教授，博士，博士生导师(通讯作者. E-mail: yjyan_2895@nwpu.edu.cn).

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Damage Identification for Bridge Structures Based on the Wavelet Neural Network Method

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基于小波神经网络方法的桥梁结构损伤识别研究

doi: 10.3879/j.issn.1000-0887.2016.02.004

作者简介: 肖书敏(1991—），女，硕士生(E-mail: 1037270561@qq.com);闫云聚(1954—)，男，教授，博士，博士生导师(通讯作者. E-mail: yjyan_2895@nwpu.edu.cn).

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Damage Identification for Bridge Structures Based on the Wavelet Neural Network Method

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出版历程

目录

作者简介:
肖书敏(1991—），女，硕士生(E-mail: 1037270561@qq.com);闫云聚(1954—)，男，教授，博士，博士生导师(通讯作者. E-mail: yjyan_2895@nwpu.edu.cn).