Structural damage identification using adaptive immune clonal selection algorithm and acceleration data

In order to identify damage of civil engineering structures precisely and efficiently, an approach for damage identification by employing Adaptive Immune Clonal Selection Algorithm (AICSA) is proposed. By utilizing secondary response, adaptive mutation regulation and vaccination operator, AICSA achieves the dynamic control of evolution process, which realizes global optimal computing combined with the local searching. Compared with basic clonal selection algorithm, AICSA improves convergence rate and global optimum searching ability. The experimental results show that AICSA can efficiently and precisely identify single and multiple damages of civil engineering structures respect to different damage location, extent and measurement noise.