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Wavelet Transforms for System Identification in Civil Engineering
Author(s) -
Kijewski T.,
Kareem A.
Publication year - 2003
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 - 10.1111/1467-8667.t01-1-00312
Subject(s) - wavelet , morlet wavelet , frequency domain , computer science , identification (biology) , context (archaeology) , modal , wavelet transform , speech recognition , discrete wavelet transform , artificial intelligence , computer vision , geology , botany , biology , chemistry , polymer chemistry , paleontology
The time‐frequency character of wavelet transforms allows adaptation of both traditional time and frequency domain system identification approaches to examine nonlinear and non‐stationary data. Although challenges did not surface in prior applications concerned with mechanical systems, which are characterized by higher frequency and broader‐band signals, the transition to the time‐frequency domain for the analysis of civil engineering structures highlighted the need to understand more fully various processing concerns, particularly for the popular Morlet wavelet. In particular, as these systems may possess longer period motions and thus require finer frequency resolutions, the particular impacts of end effects become increasingly apparent. This study discusses these considerations in the context of the wavelet's multi‐resolution character and includes guidelines for selection of wavelet central frequencies, highlights their role in complete modal separation, and quantifies their contributions to end‐effect errors, which may be minimized through a simple padding scheme.