基于改进EMD-ICA的结构模态参数识别研究

付春; 姜绍飞

doi:10.6052/j.issn.1000-4750.2012.07.0486

基于改进EMD-ICA的结构模态参数识别研究

付春^1,2,
姜绍飞^1,

1.
福州大学土木工程学院，福建，福州350108；
2.
辽宁石油化工大学石油天然气工程学院，辽宁，抚顺113001

基金项目: 国家自然科学基金项目(51278127,50878057)；国家“十二五”科技支撑计划项目(2012BAJ14B05)

详细信息

通讯作者:
姜绍飞(1969－),男,山东青岛人,特聘教授,博士,博导,主要从事结构健康监测与组合结构研究(E-mail:cejsf@163.com).

中图分类号: TU317.5;TU311.3
计量
- 文章访问数: 255
- HTML全文浏览量: 7
- PDF下载量: 203
出版历程
- 收稿日期: 2012-07-03
- 修回日期: 2013-03-04
- 刊出日期: 2013-10-24

STUDY ON THE MODAL PARAMETER IDENTIFICATION BASED ON IMPROVED EMD AND INDEPENDENT COMPONENT ANALYSIS

FU Chun^1,2,
JIANG Shao-fei^1,

1.
College of Civil Engineering, Fuzhou University, Fuzhou, Fujian 350108, China;
2.
College of Petroleum Engineering, Liaoning Shihua University, Fushun, Liaoning 113001, China

摘要

摘要: 该文针对频带滤波改进经典经验模态分解(EmpiricalModeDecomposition，EMD)的模态分解能力不足时产生过多虚假模态的问题以及真正本征模函数(IntrinsicModeFunction，IMF)的判定问题，提出了将改进EMD与独立分量相结合的信号分析方法。该方法不需要人为预先设定阈值，能够自动分离出真正的IMF分量，消除改进EMD过程中产生的虚假模态，保障EMD分解信号的有效性。然后利用随机减量技术获得各IMFs的自由模态，最后利希尔伯特变换和最小二乘拟合技术相结合的方法来识别出结构的频率和阻尼比，并通过两个数值算例和一个七层钢框架的模态试验予以验证。研究结果表明：该方法可有效解决改进EMD的缺陷，并成功识别出结构的模态参数。
- 改进Hilbert-Huang变换 /
- 模态参数识别 /
- 经验模态分解 /
- 独立分量分析 /
- 随机减量技术
Abstract: Considering the problem of a false modal and the decision of a real IMF in an improved Empirical Mode Decomposition (EMD) by using frequency-band filters, a signal analysis method based on the combination of improved EMD and Independent Component Analysis (ICA) was proposed. This proposed method does not require setting a threshold in advance, and the real IMF component can be isolated automatically. This method also can eliminated the false modal components, which appeared in the process of an improved EMD, thusly it can make sure the validity of an EMD very well. Afterwards, the random decrement technique (RDT) is used to obtain free vibration modes of each IMF. Finally, Hilbert Transform (HT) and the least square fitting are employed to identify structural modal parameters from these free vibration modes. Finally, the presented method is used to identify modal parameters of two numerical examples and a seven-story steel frame. The results show that the proposed method can resolve the drawbacks of an improved EMD more effectively, and the modal parameters can be identified successfully.
- improved Hilbert-Huang transform /
- modal parameter identification /
- empirical mode decomposition /
- independent component analysis /
- random decrement technique

HTML全文

参考文献(13)

[1]	Xiaomin Zhao, Tejas H Patel, Ming J Zuo. Multivariate EMD and full spectrum based condition monitoring for rotating machinery [J]. Mechanical Systems and Signal Processing, 2012, 27: 712―728.
[2]	胡劲松, 杨世锡, 任达千. 一种基于EMD的振动信号时频分析新方法研究[J]. 振动与冲击, 2008, 27(8): 71―73, 154.Hu Jingsong, Yang Shixi, Ren Daqian. Study on the method of EMD-based vibration signal time-frequency analysis [J]. Journal of Vibration and Shock, 2008, 27(8): 71―73, 154. (in Chinese)
[3]	董银峰, 李英民, 赖明. 基于EMD和VARMA模型的结构损伤识别[J]. 振动与冲击, 2010, 29(12): 141―147.Dong Yinfeng, Li Yingmin, Lai Ming. EMD and VARMA models based structural damage detection [J]. Journal of Vibration and Shock, 2010, 29(12): 141―147. (in Chinese)
[4]	Wang Tong, Zhang Mingcai, Yu Qihao, Zhang Huyuan. Comparing the applications of EMD and EEMD on time-frequency analysis of seismic signal [J]. Journal of Applied Geophysics, 2012, 83: 29―34.
[5]	Huang N E, Shen Z, Long S R. A new view of nonlinear water waves: the Hilbert spectrum [J]. Annual Review of Fluid Mechanics, 1999, 31: 417―457.
[6]	Wu Z H, Huang N E. Ensemble empirical mode decomposition: a noise-assisted data analysis method [J]. Advances in Adaptive Data Analysis, 2009, 1: 1―41.
[7]	Yang W X. Interpretation of mechanical signals using an improved Hilbert-Huang transform [J]. Mechanical Systems and Signal Processing, 2008, 22: 1061―1071.
[8]	Peng Z K, Tse W Peter, Chu F L. An improved Hilbert-Huang transform and its application in vibration signal analysis [J]. Journal of Sound and Vibration, 2005, 286: 187―205.
[9]	姜绍飞. 改进希-黄变换的结构响应分析方法[P]. 中国: ZL200610046897.7, 2009.Jiang Shaofei. Analytical Method of Structural Responses based on Revised Hilbert-Huang Transform [P]. China: ZL200610046897.7, 2009. (in Chinese)
[10]	黄天立, 邱发强, 楼梦麟. 基于改进HHT方法的密集模态结构参数识别[J]. 中南大学学报(自然科学版), 2011, 42(7): 2054―2062.Huang Tianli, Qiu Faqiang, Lou Menglin. Application of an improved HHT method for modal parameters identification of structures with closely spaced modes [J]. Journal of Central South University (Science and Technology), 2011, 42(7): 2054―2062. (in Chinese)
[11]	余先川, 胡丹. 盲源分离理论与应用[M]. 北京: 科学出版社, 2011: 51―103.Yu Xianchuan, Hu Dan. The theory and application of blind source separation [M]. Beijing: Science Press, 2011: 51―103. (in Chinese)
[12]	李鸿燕, 王华奎. 独立分量分析在混叠通信信号分离中的应用[J]. 仪器仪表学报, 2006, 27(6): 664―665.Li Hongyan, Wang Huakui. Application of independent component analysis on overlapped communication signal separation [J]. Chinese Journal of Scientific Instrument, 2006, 27(6): 664―665. (in Chinese)
[13]	付春. 基于改进的HHT结构信号分析与损伤检测研究[D]. 沈阳: 沈阳建筑大学, 2006.Fu Chun. Study of structural signal analysis and damage detection based on improved Hilbert-Huang transform [D]. Shenyang: Shenyang Jianzhu University, 2006. (in Chinese)

施引文献

资源附件(0)

计量

文章访问数: 255
HTML全文浏览量: 7
PDF下载量: 203
被引次数: 0

基于改进EMD-ICA的结构模态参数识别研究

通讯作者: 姜绍飞(1969－),男,山东青岛人,特聘教授,博士,博导,主要从事结构健康监测与组合结构研究(E-mail:cejsf@163.com).

计量

出版历程

STUDY ON THE MODAL PARAMETER IDENTIFICATION BASED ON IMPROVED EMD AND INDEPENDENT COMPONENT ANALYSIS

计量

出版历程

目录

通讯作者:
姜绍飞(1969－),男,山东青岛人,特聘教授,博士,博导,主要从事结构健康监测与组合结构研究(E-mail:cejsf@163.com).