ANN-based Real-Time Damage Detection Algorithm using Output-only Acceleration Signals

가속도를 이용한 인공신경망 기반 실시간 손상검색기법

In this study, an ANN-based damage detection algorithm using acceleration signals is developed for alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed for damage detection in real time. The cross-covariance of two acceleration signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained for potential loading patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.