Non-destructive Material Identification of a Car Seat Frame Using Experimental Modal Parameters

The material properties of a structure can be estimated using destructive and non-destructive methods. Experimental vibration data of the structure can be used to conduct a non-destructive procedure to identify material properties. In this research, experimental modal parameters are utilized to estimate the Young’s modulus and the density of different components of a car seat frame. To do so, the finite element model of the structure is constructed and the modal parameters are evaluated by performing modal analysis. The obtained modal parameters are then used in an inverse identification procedure and compared with the experimental counterparts to estimate the material properties of the structure in an optimization framework. The objective function is defined by comparing the numerical and experimental natural frequencies where the material properties are considered as the design parameters of the optimization process. To find the optimum design parameters, the response surface optimization technique is employed to alleviate the computational costs of direct optimization. To this end, the design of experiment method using the Box-Behnken design is conducted to create the design points. The kriging method is then utilized to construct the response surfaces. Finally, the nonlinear programming quadratic Lagrangian method is employed to evaluate the best estimations for the material properties using the response surface optimization.