Parameter Identification of Experimental a 1DoF Mechanical System Coupled to Tuned Liquid Column Dampers Magneto-Rheological Using Genetic Algorithm Optimization

Resumo

Among passive control solutions for wind turbines, TLCD is a viable alternative. They are based on a fluid mass in a liquid column, and the relative movement of this fluid in relation to the main structure dissipates the kinetic energy of the structure. The genetic algorithm (GA) is a good solution for experimental parameters identification. The GA is a computational optimization technique inspired by the principles of biological evolution. It simulates natural selection and reproduction to find optimal or near-optimal solutions to complex problems. This research aims to determine a modal parameters of numerical model using experimental results of the acceleration frequency response of 1DoF system coupled to TLCD-MR by GA minimization of least-square error metric. Through experimental forced vibration techniques, the dynamic parameters and dynamic behavior of the coupled system will be investigated and validated. A genetic algorithm-based code routine is programmed for error minimization fitting of the experimental results. The experimental response of the TLCD-MR+1DoF coupled system is compared to the 2DoF numerical model. The numerical behavior of the TLCD-MR is sought to be achieved by obtaining the parameters that fit the experimental result.