NDLI: Damage detection methodology on beam-like structures based on combined modal Wavelet Transform strategy

Content Provider	EDP Sciences
Author	Roger Serra Lautaro Lopez
Abstract	Different approaches on the detection of damages based on dynamic measurement of structures have appeared in the last decades. They were based, amongst others, on changes in natural frequencies, modal curvatures, strain energy or flexibility. Wavelet analysis has also been used to detect the abnormalities on modal shapes induced by damages. However the majority of previous work was made with non-corrupted by noise signals. Moreover, the damage influence for each mode shape was studied separately. This paper proposes a new methodology based on combined modal wavelet transform strategy to cope with noisy signals, while at the same time, able to extract the relevant information from each mode shape. The proposed methodology will be then compared with the most frequently used and wide-studied methods from the bibliography. To evaluate the performance of each method, their capacity to detect and localize damage will be analyzed in different cases. The comparison will be done by simulating the oscillations of a cantilever steel beam with and without defect as a numerical case. The proposed methodology proved to outperform classical methods in terms of noisy signals.
Page Count	18
File Format	HTM / HTML PDF
ISSN	22577777
e-ISSN	22577750
Issue Number	8
Journal	Mechanics & Industry
Volume Number	18
DOI	10.1051/meca/2018007
Alternate Webpage(s)	https://articles/meca/abs/2017/08/mi160269/mi160269.html
Language	English
Publisher	EDP Sciences
Publisher Date	2017-01-01
Access Restriction	Open
Rights Holder	© AFM, EDP Sciences 2017
Subject Keyword	Damage assessment modal analysis wavelet transform damage indicator cantilever beam Damage assessment / modal analysis / wavelet transform / damage indicator / cantilever beam
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Materials Science Mechanical Engineering

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