Hybrid Immune Algorithm for Structural Health Monitoring Using Acceleration Data

In order to detect and identify damage of civil engineering structures precisely and efficiently, an approach for damage detection by employing hybrid immune algorithm combined with Negative Selection (NS) and Clonal Selection Algorithm (CSA) is proposed. NS and CSA play different roles in this process. The first step is to create a detector set by using normal acceleration data as input. The second step is to use negative selection algorithm to detect and localize the damage of the structure. At last, CSA will quantify the damage severity of the structure. The experimental results of an 8-story shear frame structure indicated that this hybrid immune algorithm can efficiently and precisely detect, localize and quantify damage of civil engineering structures with different damage location, extent and measurement noise.