Identifying damage in spherical laminate shells by using a hybrid real-parameter genetic algorithm

Abstract

A hybrid algorithm combining an adaptive real-parameter genetic algorithm with simulated annealing is proposed to detect damage in a simply supported equal-sided sector of a spherical laminate shell. The proposed algorithm uses the data of natural frequencies and mode shapes. A single damage example and a two-damage example are investigated. To simulate the error on the measured data, three error cases are adopted. Error case one has no error, error case two has maximum 5% error on both the natural frequency and the mode shape, and error case three has maximum 5% error on the natural frequency and maximum 10% error on the mode shape. The results indicate that when the measured data is error-free, the proposed technique is very efficient in finding the exact damage locations and extents of both damage examples. In the other two error cases, the proposed method predicts the damage locations precisely and estimates the damage factor that is very close to the exact value.