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。
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-Smirnov fitting 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.
出处
《重庆交通大学学报（自然科学版）》
CAS
北大核心
2013年第6期1119-1122,1147,共5页
Journal of Chongqing Jiaotong University(Natural Science)
基金
重庆市科技攻关计划项目(CSCT2009AB6135)
