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In this study, sequential approaches for damage detection in beams using time-modal features and artificial neural networks are proposed.
The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in signal analysis and information processing techniques.
Scenario-based inductive design methods and detail design approaches for damage containment must also be part of the future of safe innovation.
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An approach for damage localization that operates with free vibration signals in the damaged state is presented.
The results show that RSM is a potentially useful approach for damage detection.
The paper presents an efficient multi-stage optimization approach for damage detection in plate-like structures.
An approach for damage inspection of composite structures utilizing carbon nanotubes (CNT) networks is investigated.
The performance of these DSFs is compared with mode shape curvature-based approach for damage localization.
The proposed approach for damage localization is introduced based on perturbation matrices that are defined by the difference between mass and stiffness matrices of undamaged and damage structures.
The present paper aims to propose a novel approach for damage identification of continuum structures based on their dynamic performances.
A damage index (DI) approach for damage detection and localization based on high frequency wave propagation data and low frequency vibration measurements is presented.
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CEO of Professional Science Editing for Scientists @ prosciediting.com