Title: Detection of structural damage via free vibration responses generated by approximating artificial neural networks
Authors: Kao, CY
Hung, SL
土木工程學系
Department of Civil Engineering
Keywords: neural networks;structural damage detection;free vibration responses;system identification;shaking table test;structural health monitoring
Issue Date: 1-Nov-2003
Abstract: This work presented a novel neural network-based approach for detecting structural damage. The proposed approach involves two steps. The first step, system identification, uses neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The second step, structural damage detection, uses the aforementioned trained NSINs to generate free vibration responses with the same initial condition or impulsive force. Comparing the periods and amplitudes of the free vibration responses of the damaged and undamaged states allows the extent of changes to be assessed. Furthermore, numerical and experimental examples demonstrate the feasibility of applying the proposed method for detecting structural damage. (C) 2003 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/S0045-7949(03)00323-7
http://hdl.handle.net/11536/27400
ISSN: 0045-7949
DOI: 10.1016/S0045-7949(03)00323-7
Journal: COMPUTERS & STRUCTURES
Volume: 81
Issue: 28-29
Begin Page: 2631
End Page: 2644
Appears in Collections:Articles


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