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《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]

卷:

41卷

期数:

2024年06期

页码:

41-48

栏目:

建筑结构

出版日期:

2024-11-30

文章信息/Info

Title:

Research on damage identification of truss structures based on BP neural network

文章编号:

1673-2049(2024)06-0041-08

作者:

冯紫科,杨 璐,柳美玉,李笑林

(北京工业大学 城市与工程安全减灾教育部重点实验室,北京 100124)

Author(s):

FENG Zike, YANG Lu, LIU Meiyu, LI Xiaolin

(Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, China)

关键词:

BP神经网络;  桁架结构;  损伤识别;  静力加载试验

Keywords:

BP neural network;  truss structure;  damage identification;  static loading test

分类号:

TU317

DOI:

10.19815/j.jace.2022.12049

文献标志码:

A

摘要:

为分析验证BP神经网络在结构损伤识别定位上应用的有效性,设计了一个桁架结构模型的静力加载试验,通过在桁架结构中更换不同直径的杆件来模拟杆件损伤,并记录其所引起的静力响应; 采用ABAQUS分析软件建立了对应的桁架有限元模型,并分析了该桁架在不同荷载工况下的受力性能与损伤情况; 在此基础上建立了用于预测桁架损伤状态的BP神经网络,该网络以有限元分析中桁架结构的荷载和节点位移作为输入参数,桁架杆件的损伤状态作为输出参数,建立了桁架结构杆件损伤状态与荷载、节点位移之间的关系; 采用桁架结构模型静力加载试验所得数据对BP神经网络算法的正确性进行验证。结果表明:BP神经网络用于桁架结构杆件的损伤识别定位能够达到较高的精度,可以实现对结构进行实时准确的安全状态评价。

Abstract:

In order to analyze and verify the effectiveness of BP neural network application in structural damage identification and location, a static loading test of a truss structure model was designed. The damage of the member was simulated by replacing the member with different diameters in the truss structure, and the static response caused by it was recorded. ABAQUS analysis software was used to establish the corresponding finite element model of the truss, and the mechanical performance and damage of the truss under different load cases were analyzed. On the basis, BP neural network was established to predict the truss damage state. The network took the load and node displacement of the truss structure in the finite element analysis as the input parameters, and the damage state of the truss member as the output parameters. The relationship between the damage state of the truss member and the load and node displacement was established. The correctness of BP neural network algorithm was verified by the data obtained from the static load test of the truss structure model. The results show that the BP neural network can achieve high accuracy in damage identification and location of truss members, and can realize real-time safety state evaluation of structures.

参考文献/References:

[1] 于振兴,刘文锋,付兴潘.工程结构倒塌案例分析[J].工程建设,2009,41(2):1-7,23.
YU Zhenxing,LIU Wenfeng,FU Xingpan.Analysis of engineering structure collapse cases[J].Engineering Construction,2009,41(2):1-7,23.
[2]RUMELHART D E,HINTON G E,WILLIAMS R J.Learning representations by back-propagating errors[J].Nature,1986,323(6088):533-536.
[3]李笑林,杨 璐,许 镇,等.建筑结构安全智能化监测研究现状及展望[J].土木工程与管理学报,2021,38(5):152-164.
LI Xiaolin,YANG Lu,XU Zhen,et al.Research status and prospect of intelligent monitoring of structure safety[J].Journal of Civil Engineering and Management,2021,38(5):152-164.
[4]黄家英,葛一楠,蔡 勇.讲座:人工神经网络 第三讲:误差反向传播学习算法及B-P网络[J].自动化与仪器仪表,1997(3):46-52.
HUANG Jiaying,GE Yinan,CAI Yong.Lecture:artificial neural network lecture 3:error back propagation learning algorithm and B-P network[J].Automation and Instrumentation,1997(3):46-52.
[5]姜绍飞.基于神经网络的结构优化与损伤检测[M].北京:科学出版社,2002.
JIANG Shaofei.Structural optimization and damage detection based on neural network[M].Beijing:Science Press,2002.
[6]孙宗光,倪一清,高赞明,等.基于斜拉索振动测量与神经网络技术的斜拉桥损伤位置识别方法[J].工程力学,2003,20(3):26-30.
SUN Zongguang,NI Yiqing,GAO Zanming,et al.Damage locating of cable-stayed bridges based on dynamic measurement and neural network technique[J].Engineering Mechanics,2003,20(3):26-30.
[7]李学良.同步学习BP神经网络及其在桥梁损伤识别中的应用[D].北京:北京工业大学,2005.
LI Xueliang.BP algorithm of learning simultaneously and its application to the damage detection of bridge[D].Beijing:Beijing University of Technology,2005.
[8]田 谷,续若楠,缪长青,等.基于BP神经网络的大跨桥梁结构混凝土温度预测[J].水利与建筑工程学报,2010,8(5):107-109,123.
TIAN Gu,XU Ruonan,MIAO Changqing,et al.Temperature estimation for mass concrete structure based on BP neural network[J].Journal of Water Resources and Architectural Engineering,2010,8(5):107-109,123.
[9]BARAI S V,PANDEY P C.Vibration signature analysis using artificial neural networks[J].Journal of Computing in Civil Engineering,1995,9(4):259-265.
[10]张玉平,马 超,李传习,等.基于均匀设计及BP神经网络的大体积混凝土热学参数反分析[J].土木与环境工程学报(中英文),2021,43(2):148-157.
ZHANG Yuping,MA Chao,LI Chuanxi,et al.Inverse analysis on thermal parameters of mass concrete based on uniform design and BP neural network[J].Journal of Civil and Environmental Engineering,2021,43(2):148-157.
[11]余 昆,倪海波,唐小兵.基于神经网络和遗传算法结合的桥梁结构损伤诊断[J].武汉理工大学学报(交通科学与工程版),2006,30(2):279-281.
YU Kun,NI Haibo,TANG Xiaobing.Identification of damages in bridge structures based on combining neural networks and genetic algorithm[J].Journal of Wuhan University of Technology(Transportation Science & Engineering),2006,30(2):279-281.
[12]于德介,雷 慧.用BP神经网络诊断结构破损[J].工程力学,2001,18(1):56-61.
YU Dejie,LEI Hui.A method for structural damage detection using neural networks[J].Engineering Mechanics,2001,18(1):56-61.
[13]田 壮,樊启武,王昌杰.深度学习在桥梁响应预测与健康监测中的应用[J].铁道工程学报,2021,38(6):47-52.
TIAN Zhuang,FAN Qiwu,WANG Changjie.Application of deep learning in bridge structure response prediction and health monitoring system[J].Journal of Railway Engineering Society,2021,38(6):47-52.
[14]王丕光,崔智谋,赵 娟.基于BP神经网络算法的混凝土单层框架损伤识别[J].防灾科技学院学报,2011,13(2):32-37.
WANG Piguang,CUI Zhimou,ZHAO Juan.Damage detection on concrete of single-story frame based on BP neural networks[J].Journal of Institute of Disaster Prevention,2011,13(2):32-37.
[15]徐长哲,余庆林,杨青松.基于BP神经网络的结构损伤识别技术[J].应用科技,2020,47(3):63-68.
XU Changzhe,YU Qinglin,YANG Qingsong.Structural damage identification technology based on BP neural network[J].Applied Science and Technology,2020,47(3):63-68.
[16]GAO Z Y.Structural health monitoring based on BP network and magnetic memory[J].Advances in Intelligent Systems and Computing,2019,1017:249-258.
[17]王清华,荆建中,陈 振,等.基于BP神经网络的单管通信塔损伤识别研究[J].特种结构,2020,37(5):112-116.
WANG Qinghua,JING Jianzhong,CHEN Zhen,et al.Damage identification of single-tower based on the BP neural network[J].Special Structures,2020,37(5):112-116.
[18]SAHIN M,SHENOI R A.Quantification and localisation of damage in beam-like structures by using artificial neural networks with experimental validation[J].Engineering Structures,2003,25(14):1785-1802.
[19]林小贝.基于BP神经网络与传递率函数融合的钢结构损伤检测方法研究[D].杭州:浙江工业大学,2020.
LIN Xiaobei.Research on steel structure damage detection method based on the fusion of BP neural network and transmissibility function[D].Hangzhou:Zhejiang University of Technology,2020.
[20]石 晟,杜东升,徐敬海,等.基础隔震结构基于实时监测数据的多级预警及其在南京博物院老大殿中的应用[J].建筑结构学报,2022,43(4):47-57.
SHI Sheng,DU Dongsheng,XU Jinghai,et al.Multi-level early-warning system for base-isolated structures based on real-time monitoring data and its application on the old hall of Nanjing museum[J].Journal of Building Structures,2022,43(4):47-57.
[21]赵艳男,杜文风,王英奇,等.基于BP神经网络算法的树状结构智能找形研究[J].建筑结构学报,2022,43(4):77-85.
ZHAO Yannan,DU Wenfeng,WANG Yingqi,et al.Study on intelligent shape finding for tree-like structures based on BP neural network algorithm[J].Journal of Building Structures,2022,43(4):77-85.

相似文献/References:

[1]尤杰,车轶,仲伟秋.基于BP神经网络的既有建筑混凝土强度预测[J].建筑科学与工程学报,2011,28(01):70.
　YOU Jie,CHE Yi,ZHONG Wei-qiu.Predition of Concrete Strength of Existing Buildings Based on BP Neural Networks[J].Journal of Architecture and Civil Engineering,2011,28(06):70.
[2]柳明亮,李翔宇,邢国华,等.大跨空间轮辐式弦支桁架结构施工过程监测与模拟分析[J].建筑科学与工程学报,2023,40(01):95.[doi:10.19815/j.jace.2022.05050]
　LIU Mingliang,LI Xiangyu,XING Guohua,et al.Monitoring and simulation analysis of construction process for large-span spatial spoke chord-supported truss structure[J].Journal of Architecture and Civil Engineering,2023,40(06):95.[doi:10.19815/j.jace.2022.05050]

备注/Memo

备注/Memo:

收稿日期:2023-12-21 投稿网址:http://jace.chd.edu.cn
基金项目:国家自然科学基金项目(52078011)
通信作者:柳美玉(1979-),女,工学博士,讲师,E-mail:liumeiyu@bjut.edu.cn。
Author resume: LIU Meiyu(1979-),female,PhD,assistant professor,E-mail:liumeiyu@bjut.edu.cn.

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更新日期/Last Update: 2024-12-10