An experimental verification of a damage detection process using novel optimization techniques such as modified real coded genetic algorithms and swarm-based algorithms is presented. Here, the objective function is defined as the sum of differences of the modal frequencies between intact and stiffness damaged state, which has to be minimized to identify the damage location and its severity in the process of model updating. In addition to the structural or damage variables such as the mass or stiffness of the numerical model, the profiles of modal frequency shifts are also damage-sensitive features. The iterative process that uses the proposed population-based optimization algorithms successfully identifies the local mass change of a test structure by updating the damage variables to fit the modal data of test structures such as a cantilevered beam and multibay truss frame.
structural health monitoring; damage detection; optimization algorithm; genetic algorithm; swarm based