Damage detection of fixed-fixed Beam: A fuzzy Neuro hybrid system based approach

Abstract

Integration of Neural Networks (NN) and Fuzzy Logic (FL) have brought researchers from various scientific and engineering domains for the need of developing adaptive intelligent systems to address real time applications. The integration of NN and FL can be classified broadly into three categories namely concurrent model, cooperative model and fully fused model. In the present analysis, fuzzy logic and neural network have been adopted to form a damage identification tool for structural health monitoring for fixed-fixed beam made of steel. The proposed methodology utilizes the modal characteristics of the fixed-fixed beam structure using numerical modeling techniques and anticipates the position and severities of the damage present in the system. The robustness of the proposed technique has been realized by conducting experiments on the steel fixed-fixed beam with different damage characteristics.