Sensor placement optimization for structural modal identification of flexible structures using genetic algorithm

The position of vibration sensors influences the modal identification quality of flexible structures for a given number of sensors, and the quality of modal identification is usually estimated in terms of correlation between the natural modes using the modal assurance criterion (MAC). The sensor placement optimization is characterized by the fact that the design variables are not continuous but discrete, implying that the conventional sensitivity-driven optimization methods are not applicable. In this context, this paper presents the application of genetic algorithm to the sensor placement optimization for improving the modal identification quality of flexible structures. A discrete-type optimization problem using genetic algorithm is formulated by defining the sensor positions and the MAC as the design variables and the objective function, respectively. The proposed GA-based evolutionary optimization method is validated through the numerical experiment with a rectangular plate, and its excellence is verified from the comparison with the cases using different modal correlation measures.