Damage detection using vibration data and dynamic transmissibility ensemble with auto-associative neural network

In this paper, a transmissibility based damage detection methodology using artificial intelligence is proposed. Structural health monitoring requires accurate damage detection in real engineering while the environmental uncertain-ties make this a challenge. In order to reduce this effect, artificial intelligence, such as artificial neural networks might be a possible strategy for achieving a better interpretation of the monitored data during operational condition. In this study, transmissibility is taken into account as damage sensitive feature because it accounts for the response data only. Then, auto-associative neural network is employed for detecting the structural damage and predicting its severity. In order to validate our proposed technique, a ten-floor structure is simulated and studied. The results show good perfor-mance in detecting damages.DOI: http://dx.doi.org/10.5755/j01.mech.23.5.15339