VIBRATION-BASED DAMAGE IDENTIFICATION IN BEAM STRUCTURES USING NEURAL NETWORKS

Abstract

It is important to detect and locate damages in structures at an early stage to extend service life of the structures. Vibration-based damage identification methods that examine changes in vibration characteristics between intact and damaged stats of structures has been proposed by many researchers. However, it is difficult to accurately estimate multiple damages caused by natural disasters or long-term deterioration, for example. This study attempts to identify multiple damages in a cantilever and a simple beam using neural networks based on natural frequencies and natural vibration modes, which are typical vibration characteristics. To examine the accuracy of identification, particular attention is given to high-order vibration characteristics and slope elements in natural vibration modes. The results suggest that suitable data preprocessing method for each boundary condition is required to improve the accuracy of identification.