中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2013, Vol. 32 ›› Issue (6): 1119-1121.DOI: 10.3969/j.issn.1674-0696.2013.06.05

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改进Hilbert-Huang 变换在钢管混凝土 脱空检测中的应用

韩西1,王吉1,钟厉2, 向丽1   

  1. 1.重庆交通大学士木建筑学院,重庆 400074;2.震庆交通大学机电与汽车t 程学院,重庆 400074
  • 收稿日期:2012-05-22 修回日期:2013-01-27 出版日期:2013-12-15 发布日期:2015-01-22
  • 作者简介:韩西(1964—),男,重庆人,教授,博士,主要从事结构力学、振动工程方面的研究。E-mail:xihan@cquc.edu.cn
  • 基金资助:
    重庆市科技攻关计划项目(CSCT009AB6135 )

Application of the Improved Hilbert-Huang Transformation to CFST Cavity Detection

Han Xi 1,Wang Ji1 , Zhong Li2, Xiang Li1   

  1. 1.School of Civil Engineering & Architecture , Chongqing Jiaotong University , Chongqing 400074 , China; 2.School of Mechatronics & Automotive Engineering, Chongqing Jiaotong University , Chongqing 400074 , China
  • Received:2012-05-22 Revised:2013-01-27 Online:2013-12-15 Published:2015-01-22

摘要: 在钢管混凝土脱空检测试验中,采用Hilbert-Huang变换对声音这种非线性非平稳信号进行采集分析。原信号 先经验模态分解为固有模态IMF分量,然后对IMF分量进行Hilbert变换,但是经验模态分解出的IMF分量中可能 有一部分的虚假分量。利用Kolmogorov-Smirnov拟合优度检验法,来判别出分解后的每一个IMF分量与原信号概率 分布的相似概率,去除掉虚假分量,采用相似概率比较高的IMF分量,最后得出合理的Hilbert边际谱,正确反映了 结构的局部特性,有效地实现了脱空的检测。

关键词: Kolmogorov-Smimov检验法, Hilbert-Huang变换, 声音信号, 概率分布

Abstract: In CFST cavity detection test , Hilbert-Huang transformation was used to collect and analyze the sound , which was nonlinear and non-stationary signal. Empirical mode of the original signal was decomposed into the intrinsic mode function (IMF) components , and then Hilbert Transformation of IMF component was carried out. However , IMF components decomposed from the empirical mode decomposition may include a portion of false components. So Kolmogorov-Smimov fiuing goodness inspection test method was used to distinguish the similar probabilities of each IMF component and the original signal after decomposition. Furthermore , false components were got rid of. Finally , IMF components , whose similar probability was relatively high , were applied to get a reasonable Hilbert marginal spectrum. IMF components accurately reflect the local characteristics of the structure , and effectively realize CFST cavity detection.

Key words: Kolmogorov-Smimov inspection, Hilbert-Huang transfonmation, voice signal, probability distribution

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