STRUCTURAL DAMAGE IDENTIFICATION METHOD WITH DATA FUSION BASED ON FUZZY NEURAL NETWORK

In order to make full use of the information collected by multi-source sensors and to increase the damage identification accuracy of a structural health monitoring system, a damage identification method with data-fusion based on fuzzy neural network is proposed in this paper. In this method, original structural response data is preprocessed and feature parameters are extracted. The parameters are used as the input of the fuzzy neural network model, and decision is obtained using this model. Finally, fusion decision results are analyzed by data fusion algorithms. A 7-degree-of-freedom building model is utilized to validate the proposed method, and a comparison is made between this method and a single fuzzy neural network model. The results show that the proposed damage identification method is more exact and reliable than that of a single fuzzy neural network model.