A novel methodology for modal parameters identification of large smart structures using MUSIC, empirical wavelet transform, and Hilbert transform

2017 ◽  
Vol 147 ◽  
pp. 148-159 ◽  
Author(s):  
Juan P. Amezquita-Sanchez ◽  
Hyo Seon Park ◽  
Hojjat Adeli
Keyword(s):  
Wavelet Transform ◽  
Hilbert Transform ◽  
Smart Structures ◽  
Parameters Identification ◽  
Modal Parameters ◽  
Empirical Wavelet Transform ◽  
Modal Parameters Identification

Study on Modal Parameters Identification Based on Stratified Sampling and Complex Morlet Wavelet Transform

2011 ◽  
Vol 305 ◽  
pp. 428-433
Author(s):  
Yong Hua Jiang ◽  
Hong Xu ◽  
Guang Ming Cheng ◽  
Jian Ming Wen ◽  
Ji Jie Ma
Keyword(s):  
Wavelet Transform ◽  
Maximum Energy ◽  
Morlet Wavelet ◽  
Stratified Sampling ◽  
Parameters Identification ◽  
Modal Parameters ◽  
Engineering Structures ◽  
Modal Parameters Identification ◽  
Complex Morlet Wavelet ◽  
Morlet Wavelet Transform

The natural frequency of large engineering structures are very low and closely, and it’s very difficult to excite the structures by exciter, in order to identify the modal parameters of large engineering structures, a novel modal parameters identification method based on stratified sampling and complex Morlet wavelet transform is proposed. In order to improve the precision of sampling, stratified sampling, which replaces the random sampling, is applied on random decrement method for extracting the free decrement response signal, and a method is introduced to determine the sample layer weights based on fitting deviation and sample size. In order to improve the identification precision of closely spaced modals, a method is developed to adaptive select the bandwidth parameter and scale parameter of the Morlet wavelet based on the principle of minimum wavelet energy entropy and maximum energy. The analysis of data from the model test of Chongqing Chaotianmen bridge show that, the method is effective to identify the low and closely modal parameters.

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