A hybridised CSAGA method for damage detection in structural elements

Abstract

In recent years, significant developments have been noticed in nondestructive techniques for damage detection in cracked structures. Some of the proposed methods can be used to find out the existence of the crack; other methods locate and simultaneously find out the damage severity. In the current investigation, a novel hybridised method is proposed for damage detection in structural elements. The proposed method can be used to investigate both location and nature of damage in structures within a reasonable time limit. The problem in the current analysis requires a set of dynamic parameters that depend on the dynamics of the cracked structure due to the presence of the crack. In the present study, the first three natural frequencies of a structure are considered as the inputs to find out the damage location. A finite element method is used to generate the first three natural frequencies of a cracked cantilever beam with multiple cracks. A method hybridizing the nature-inspired artificial intelligence techniques has been implemented for crack detection. Here, clonal selection algorithm and genetic algorithm have been integrated to design the framework of the hybrid technique. The changes in the natural frequencies are given as inputs to the hybrid technique and the output from the technique is the locations of damage.