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A Comparative Study of Modal Parameter Identification Based on Wavelet and Hilbert–Huang Transforms
Author(s) -
Yan Banfu,
Miyamoto Ayaho
Publication year - 2006
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.2005.00413.x
Subject(s) - hilbert–huang transform , modal , morlet wavelet , wavelet , benchmark (surveying) , algorithm , wavelet transform , mathematics , function (biology) , computer science , discrete wavelet transform , artificial intelligence , statistics , materials science , white noise , polymer chemistry , biology , geodesy , evolutionary biology , geography
This article presents a comparative study of the modal parameter identification of structures based on the continuous wavelet transform (WT) using the modified complex Morlet wavelet function and the improved Hilbert–Huang transform (HHT). Special attention is given to some implementation issues, such as the modal separation and end effect in the WT, the optimal parameter selection of the wavelet function, the new stopping criterion for the empirical mode decomposition (EMD) and the end effect in the HHT. The capabilities of these two techniques are compared and assessed by using three examples, namely a numerical simulation for a damped system with two very close modes, an impact test on an experimental model with three well‐separated modes, and an ambient vibration test on the Z24‐bridge benchmark problem. The results demonstrate that for the system with well‐separated modes both methods are applicable when the time–frequency resolutions are sufficiently taken into account, whereas for the system with very close modes, the WT method seems to be more theoretical and effective than HHT from the viewpoint of parameter design.