[1]常军,尤传雨.复杂追踪算法结合EEMD识别结构损伤[J].地震工程与工程振动,2017,01(05):146-154.[doi:10.13197/j.eeev.2017.05.146.changj.017]
 CHANG Jun,YOU Chuanyu.Damage identification based on complexity pursuit and EEMD[J].EARTHQUAKE ENGINEERING AND ENGINEERING DYNAMICS,2017,01(05):146-154.[doi:10.13197/j.eeev.2017.05.146.changj.017]
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复杂追踪算法结合EEMD识别结构损伤
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《地震工程与工程振动》[ISSN:/CN:]

卷:
01
期数:
2017年05期
页码:
146-154
栏目:
论文
出版日期:
2017-10-01

文章信息/Info

Title:
Damage identification based on complexity pursuit and EEMD
作者:
常军 尤传雨
苏州科技大学 土木工程学院, 江苏 苏州 215011
Author(s):
CHANG Jun YOU Chuanyu
School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
关键词:
盲源分离复杂追踪集合经验模态分解结构损伤识别信号分布向量
Keywords:
blind source separationcomplexity pursuitensemble empirical mode decompositionstructural damage identificationsource distribution vector
分类号:
U441
DOI:
10.13197/j.eeev.2017.05.146.changj.017
摘要:
结构损伤会引起结构振动信号的突变,而该突变信号会淹没于环境噪声信号中。为此,文章将复杂追踪理论(CP)引入结构损伤识别领域,将损伤识别问题转化为突变特征提取问题。提出一种复杂追踪结合集合经验模态分解(EEMD)识别结构损伤的新方法,首先采用EEMD预处理结构振动信号,接着将分解得到的本征模函数(IMF)作为混合信号输入CP模型中,提取出包含损伤特征的本征模函数,进而识别出结构损伤发生的时刻及位置。最后,通过对环境激励下六自由度质量-弹簧系统和地震激励下三层框架模型的数值分析。结果表明,该方法能够准确有效地识别结构损伤异常时刻与位置。
Abstract:
The vibration signal of structure changes suddenly when the structure damaged, and the changes always are submerged in the ambient noise. So, complexity pursuit(CP) is introduced into structural damage identification, and damage identification issue can be changed into the mutation feature extraction issue. A new method of structural damage identification based on CP and EEMD is presented. Firstly, the measured structural signals are preprocessed by EEMD. Then the intrinsic mode function(IMF) gained from EEMD is introduced into CP as mixtures, and damage novelty signals are extracted, and damage instant and location are revealed. Finally, the numerical models of 6-dof mass-spring system under ambient excitation and the three-story-frame under seismic excitation are built, the analysis results show that the proposed method can identify damage instant and location effectively.

参考文献/References:

[1] 闫桂荣, 段忠东, 欧进萍. 基于结构振动信息的损伤识别研究综述[J]. 地震工程与工程振动, 2007, 27(3):95-103. YAN Guirong, DUAN Zhongdong, OU Jinping. Review on structural damage detection based on vibration data[J]. Earthquake Engineering and Engineering Dynamics, 2007, 27(3):95-103.(in Chinese)
[2] 朱军华. 环境因素作用下的结构损伤检测[D]. 广州:暨南大学, 2011. ZHU Junhua. Structural damage detection under environmental variability[D]. Guangzhou:Jinan University, 2011.(in Chinese)
[3] 周翠. 考虑环境因素影响的结构健康监测损伤识别[D]. 大连:大连理工大学, 2013. ZHOU Cui. Damage identification algorithms considering temperature variation for civil structural health monitoring[D]. Dalian:Dalian University of Technology, 2013.(in Chinese)
[4] Yang Y, Nagarajaiah S. Blind identification of damage in time-varying systems using independent component analysis with wavelet transform[J]. Mechanical Systems & Signal Processing, 2014, 47(1/2):3-20.(in Chinese)
[5] 刘涛, 李爱群, 丁幼亮. 小波分析在结构损伤识别中的应用[J]. 地震工程与工程振动, 2008, 28(2):29-35. LIU Tao, LI Aiqun, DING Youliang. Application of wavelet analysis to structural damage identification[J]. Earthquake Engineering and Engineering Dynamics, 2008, 28(2):29-35.(in Chinese)
[6] Hou Z K, Noori M N, Amand R S. Wavelet-based approach for structural damage detection[J]. Journal of Engineering Mechanics, 2000, 126(7):677-683.
[7] Huang N E, Huang N E, et al. The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society A Mathematical Physical & Engineering Sciences, 1998, 454(1971):903-995.
[8] Wu Z, Huang N E. Ensemble empirical mode decomposition:a noise assisted data analysis method[J]. Advances in Adaptive Data Analysis, 2009, 1(1):1-41.
[9] Hazra B, Narasimhan S. Wavelet-based blind identification of the UCLA Factor building using ambient and earthquake responses[J]. Smart Materials & Structures, 2009, 19(2):328-335.
[10] 张晓丹. 基于盲源分离技术的工程结构模态参数识别方法研究[D]. 北京:北京交通大学, 2010. ZHANG Xiaodan. Study on structural modal identification using blind source separation techniques[D]. Beijing:Beijing Jiaotong University, 2010.(in Chinese)
[11] 静行, 袁海庆, 赵毅. 基于独立分量分析的结构模态参数识别[J]. 振动冲击, 2010, 29(3):137-141. JING Hang, YUAN Haiqing, ZHAO Yi. Structural modal parameter identification based on independent component analysis[J]. Journal of Vibration and Shock, 2010, 29(3):137-141.(in Chinese)
[12] 林友新, 周翠, 李宏男. 基于盲源分离的损伤识别方法[J]. 地震工程与工程振动, 2013, 33(6):158-163. LIN Youxin, ZHOU Cui, LI Hongnan. Damage identification method based on blind source separation[J]. Earthquake Engineering and Engineering Dynamics, 2013, 33(6):158-163.(in Chinese)
[13] Hyvärinen A. Complexity pursuit:separating interesting components from time series[J]. Neural Computation, 2001, 13(4):883-98.
[14] Hyvärinen A, Oja E.A fast fixed-point algorithm independent component analysis[J]. Neural Computation, 1997, 9(7):1483-1492.
[15] 吕淑平, 方兴杰, 杨丽微. 独立分量分析的算法分析与改进[J]. 噪声与振动控制, 2013, 33(6):153-157. LV Shuping,FANG Xingjie,YANG Liwei. Analysis and improvement of independent component analysis algorithm[J]. Noise and Vibration Control, 2013, 33(6):153-157.(in Chinese)
[16] 余先川, 胡丹. 盲源分离理论与应用[M]. 北京:科学出版社, 2011. YU Xianchuan, HU Dan. Theory and application of blind source separation[M]. Beijing:Science Press, 2011.(in Chinese)

相似文献/References:

[1]林友新,周翠,李宏男.基于盲源分离的损伤识别方法[J].地震工程与工程振动,2013,04(06):158.
 LIN Youxin,ZHOU Cui,LI Hongnan.Damage identification method based on blind source identification[J].EARTHQUAKE ENGINEERING AND ENGINEERING DYNAMICS,2013,04(05):158.

备注/Memo

备注/Memo:
收稿日期:2016-06-15;改回日期:2016-10-05。
基金项目:江苏省自然科学基金资助项目(BK20141180);江苏省结构工程重点实验室开放课题(DZ1405);江苏省建设系统科技项目(2015ZD77)
作者简介:常军(1973-),男,教授,博士,主要从事健康监测与振动控制研究.E-mail:changjun21@usts.edu.cn
更新日期/Last Update: 2017-10-25