Estimation of localized dynamic loads by means of sparse optimizationEstimation of localized dynamic loads by means of sparse optimization
Faculty of Applied Engineering Sciences
Optical Metrology, 3D design and Mechanics (Op3Mech)
Engineering sciences. Technology
6th International Operational Modal Analysis Conference (IOMAC 2015), 12-14 May 2015, Gijon, Spain
University of Antwerp
The identification of system parameters using forward approaches is not always practical due to the rising complexity of modern structures, leaving no chance for direct parameter measurements. In contrast to forward methods, inverse techniques have been gaining popularity, since the advent of high performing computers. This approach consists of the computation of input parameters of a system, with known output data and the system model. When the number of equations (sensors) becomes lower than the amount of unknowns (input parameters), or when the condition number of the system is high, the problem does not have a unique solution. The system becomes under-determined and highly sensitive to input perturbations. The discrete force identification problem in mechanics consists of estimating the applied force locations and their corresponding time history based on measured structural responses. In this article, the applicability of a recently proposed force identification technique (G-FISTA) will be tested using a real-life measurement on a footbridge. This iterative algorithm promotes structured sparsity in the force vector. This algorithm creates a new mathematical setting for the inverse problem, and then solves it using a mixed cost function of group-penalized least squares. This study shows that the location and time history of discrete forces applied on a footbridge can be correctly estimated using the proposed technique.