[1]麻胜兰、刘昱昊、张铮、吴琛.基于模态振型和L1正则化的结构损伤识别[J].福建工程学院学报,2020,18(01):40-45.[doi:10.3969/j.issn.1672-4348.2020.01.008]
　MA Shenglan,LIU Yuhao,ZHANG Zheng,et al.Structural damage detection based on modal shapes and L1 regularization[J].Journal of FuJian University of Technology,2020,18(01):40-45.[doi:10.3969/j.issn.1672-4348.2020.01.008]
点击复制

基于模态振型和L1正则化的结构损伤识别()
分享到：

《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第18卷
期数:
2020年01期
页码:
40-45
栏目:
出版日期:
2020-02-25

文章信息/Info

Title:
Structural damage detection based on modal shapes and L1 regularization
作者:
麻胜兰、刘昱昊、张铮、吴琛
福建工程学院土木工程学院
Author(s):
MA Shenglan;  LIU Yuhao;  ZHANG Zheng;  WU Chen
School of Civil Engineering, Fujian University of Technology
关键词:
损伤检测;  有限元方法;  模态分析;  稀疏恢复;  L1正则化
Keywords:
damage detection; 　finite-element method;  model analysis;  sparse recovery; 　L1 regularization
分类号:
TU317
DOI:
10.3969/j.issn.1672-4348.2020.01.008
文献标志码:
A
摘要:
考虑到基于2范数的正则化算法存在对结构识别结果过度光滑的效果，提出了基于模态振与L1正则化的损伤识别方法。以—2D简支梁有限元模型为数值算例，比较了使用不同振型数不同损伤程度对损伤识别效果的影响。数值模拟结果表明，对于多损伤工况，当损伤结构的振型数和无损结构的振型数乘积数大于6时，能较好地进行损伤定位，并能对损伤程度给出定性的描述。
Abstract:
Considering that the regularization algorithm based on norm 2 has over-smooth effect on the structure recognition results, a damage detection method based on modal vibration and L1 regularization was proposed.Taking the finite element model of a 2D simply-supported beam as a numerical example, the effect of using different numbers of vibration modes and that of using different damage degrees on the damage recognition effect were compared.Simulation results show that, for multi-damage　cases, when the product of the number of vibration modes of the damaged structure multiplied by that of the undamaged structure is larger than 6, the presented method could detect the structural damage location preferably and give a qualitative description for the damage degree.

参考文献/References:

[1] 李宏男, 李东升. 土木工程结构安全性评估、 健康监测及诊断述评[J]. 地震工程与工程振动, 2002，22 (3): 82-90.[2] OU J, LI H. The state-of-the-art and practice of structural health monitoring for civil infrastructures in the mainland of China [J]. Structural Health Monitoring and Intelligent Infrastructure, 2006(1): 69-93.[3] HOULT N, FIDLER P, HILL P, et al. Long-term wireless structural health monitoring of the ferriby road bridge[J]. Journal of Bridge Engineering, 2010, 15(2): 153-159. [4] 姜绍飞, 吴兆旗. 结构健康监测与智能信息处理技术及应用[M]. 北京: 中国建筑工业出版社, 2011.[5] 涂成枫, 刘泽佳, 张舸, 等. 面向桥梁长期健康监测的大数据处理技术及应用[J]. 实验力学, 2017, 32(5): 652-663.[6] 史治宇, 罗绍湘, 张令弥. 结构破损定位的单元模态应变能变化率法[J]. 振动工程学报, 1998, 11(3): 356-360.[7] 吴子燕, 何银, 简晓红. 基于损伤敏感性分析的传感器优化配置研究[J]. 工程力学, 2009, 26(5): 239-244.[8] 张谢东, 张治国, 詹昊. 基于曲率模态和柔度曲率的结构多损伤识别[J]. 武汉理工大学学报, 2005, 27(8): 35-37, 55.[9] 阳洋, MOSALAM K, 金国芳, 等. 基于改进直接刚度法的加州某桥梁结构损伤评估研究[J]. 工程力学, 2012, 29(1): 114-120, 140.[10] 唐盛华, 罗承芳, 方志, 等. 振型归一化对梁结构柔度曲率损伤指标的影响[J/OL]. 计算力学学报, 2019: 1-10.[11] 周述美, 鲍跃全, 李惠. 基于结构灵敏度分析与稀疏约束优化的结构损伤识别方法[J]. 振动与冲击, 2016, 35(9): 135-140.[12] 夏志鹏, 王树青, 徐明强, 等. 基于Tikhonov正则化迭代求解的结构损伤识别方法[J]. 振动与冲击, 2019, 38(17): 251-259.[13] 杨斌, 程军圣. 基于奇异值分解及特征正交分解的结构损伤检测方法[J]. 振动与冲击, 2014, 33(22): 164-167.[14] REN W, ROECK G. Structural damage identification using modal data. I: simulation verification[J]. Journal of Structural Engineering, 2002, 128(1): 87-95.[15] HOU R, XIA Y, BAO Y, et al. Selection of regularization parameter for l1-regularized damage detection[J]. Journal of Sound and Vibration, 2018, 423: 141-160.[16] HOU R, XIA Y, XIA Q, et al. Genetic algorithm based optimal sensor placement for L1-regularized damage detection[J]. Struct Control and Health Monitoring, 2019, 26(1): e2274.[17] 李惠, 鲍跃全, 李顺龙, 等. 结构健康监测数据科学与工程[M]. 北京: 科学出版社, 2016.[18] 骆紫薇, 余岭, 刘焕林, 等. 基于范数归一化和稀疏正则化约束的结构损伤检测[J]. 振动与冲击, 2018, 37(18): 30-35, 58.[19] 张纯, 陈林, 宋固全, 等. 基于L1正则化无迹卡尔曼滤波的结构损伤方法[J]. 工程力学, 2017, 34(8): 76-84.

更新日期/Last Update: 2019-02-25