Please use this identifier to cite or link to this item: http://repository.vnu.edu.vn/handle/VNU_123/32335
Title: A new method for beam-damage-diagnosis using adaptive fuzzy neural structure and wavelet analysis
Authors: Nguyen, Sy Dzung
Ngo, Kieu Nhi
Tran, Quang Thinh
Keywords: Fuzzy neural networks
Wavelet transform
Damage location
Damage diagnosis
Structure health monitor
Issue Date: 2013
Publisher: ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
Citation: ISIKNOWLEDGE
Abstract: In this work, we present a new beam-damage-locating (BDL) method based on an algorithm which is a combination of an adaptive fuzzy neural structure (AFNS) and an average quantity solution to wavelet transform coefficient (AQWTC) of beam vibration signal. The AFNS is used for remembering undamaged-beam dynamic properties, while the AQWTC is used for signal analysis. Firstly, the beam is divided into elements and excited to be vibrated. Vibrating signal at each element, which is displacement in this work, is measured, filtered and transformed into wavelet signal with a used-scale-sheet to calculate the corresponding difference of AQWTC between two cases: undamaged status and the status at the checked time. Database about this difference is then used for finding out the elements having strange features in wavelet quantitative analysis, which directly represents the beam-damage signs. The effectiveness of the proposed approach which combines fuzzy neural structure and wavelet transformmethods is demonstrated by experiment on measured data sets in a vibrated beam-type steel frame structure
URI: http://repository.vnu.edu.vn/handle/VNU_123/32335
ISSN: 0888-3270
Appears in Collections:Bài báo của ĐHQGHN trong Web of Science

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