Structural Damage Detection via Modal Data with Genetic Algorithms

Abstract

This paper presents a nondestructive global damage detection and assessment methodology based on the changes in frequencies and mode shapes of vibration of a structural system. The method is applied at an element level using a finite-element model. According to continuum damage mechanics, damage is represented by a reduction factor of the element bending stiffness. A nonclassical optimization approach involving the use of genetic algorithms (GAs) is proposed to localize damaged areas of the structure. The method has been verified by a number of damage scenarios for simulated beams and by using directly experimental data from the vibration tests of a beam. It is shown that the proposed GA yields a suitable damage location and severity detection while introducing numerous advantages compared to classical methods. The influence of noise in the modal data has also been considered.