Classification of Seismic Damages in Buildings Using Fuzzy Logic Procedures

Abstract

It is well-known that damage observations on buildings after severe earthquakes exhibit interdependence with the seismic intensity parameters. Numerical elaboration of structural systems quantified the interrelation degree by correlation coefficients. Further, the seismic response of buildings is directly depended on the ground excitation. Consequently, the seismic response of buildings is directly depended on the used accelerogram and its intensity parameters. Among the several response quantities, the focus is on the overall damage. Thus, the Maximum Inter-Storey Drift Ratio and the damage index of Park/Ang are used. Intervals for the values of the damage indices are defined to classify the damage degree in low, medium, large and total. This paper presents an Adaptive Neuro-Fuzzy Inference System for the damage classification. The seismic excitations are simulated by artificial accelerograms. Their intensity is described by seismic parameters. The proposed system was trained and tested on a reinforced concrete structure. The results have shown that the proposed fuzzy technique contributes to the development of an efficient blind prediction of seismic damages. The recognition scheme achieves correct classification rates over 90%.