中文摘要：

针对HHT方法中经验模态分解（EMD）过程容易出现模态混叠、虚假模态和端点效应的问题,提出了改进的HHT方法.首先利用帯通滤波对原始信号进行预处理,得到一组窄带频率信号之和;接着进行EMD过程,得到若干个本征模函数（IMF）,根据IMFs和原信号的相关系数来判定其是否是真正的IMFs;然后运用随机减量技术（RDT）和希尔伯特变换（HT）及最小二乘拟合技术识别出结构的模态参数.最后应用所提方法识别了一实测7层钢框架的模态参数.结果表明该方法成功解决了上述原HHT方法中存在的缺陷,并能更加准确地提取信号的模态参数和瞬时特征.

英文摘要：

To solve existing problems of Hilbert-Huang transform（HHT）,such as mode aliasing,false mode and end effect problems in the course of empirical mode decomposition（EMD）,an improved HHT method was proposed in this paper.At first,a band-pass filter method is used to pre-process measured primary response signals,the sum of narrow-band signals is obtained.Then a series of Intrinsic Mode Functions（IMFs）are separated from the processed signals by using EMD.The real IMFs are determined by the correlative coefficient between the separated IMFs and the primary signal.Afterwards,the random decrement technique（RDT）and Hilbert Transform（HT）and the least square fitting are employed to identify structural modal parameters from the free vibration responses.The presented method was used to identify modal parameters of a measured steel frame finally.The results show that the improved method can extract mode parameters and transient features from signals more effectively,and some problems existed in the original HHT can be resolved successfully.