Efficient Response Monitoring of Flexible Structures

The definition of an accurate model to represent the dynamic behavior of a flexible system has a significant impact on the understanding of its current health. However, due to lack of information on the physical properties as well as complexity of applied loads, accurate modeling is not usually a simple task, and inaccuracies in predicting the response of the flexible structure arise. In this work, a combined experimental and numerical approach, called Extended Load Confluence Algorithm (ELCA), is presented to improve the accuracy in the estimate of the dynamic response using an iterative approach that corrects the initial model. The objective is to accurately estimate the displacements, strains, and accelerations of the entire body. The full-field dynamic response is reconstructed from a limited set of experimental data, with little knowledge about the applied loads. ELCA estimates the state of the structure by defining fictitious applied forces that depend on the error of the estimate. The proposed algorithm is based on an initial numerical model for the prediction of the system s behavior. This model is updated based on a modal expansion of the response in the frequency domain. The algorithm starts with an initial guess of the applied loads and updates them in few iterations in order to match the numerical dynamic response with the experimental measurements at the sensors locations. Numerical and experimental analyses will show the feasibility of the proposed approach. It will be shown that a few sensors are sufficient to represent the overall behavior of the system and ELCA converges in a few iterations.