Investigation of a perturbation-based model updating approach for structural health and event monitoring

With the intention to detect structural events, for example, occurrence of damage and assessing their severity under service, structural health and event monitoring proved itself as a reliable evaluation tool. While many algorithmic approaches exist, model-based monitoring offers the prominent advantage to enable extensive analysis of damage states based on a structural digital twin. In order to accurately replicate the dynamical behaviour of a real-world structure, inherent physical properties, for example, mass, stiffness and structural damping, of the digital twin might be corrected from nominal values. This can be achieved by numerical model updating procedures. In this study, the application of a model updating approach is presented to eliminate modal discrepancies. Based on the perturbated modal dynamic residual, an updating equation is formulated. Stiffness and mass correction terms with preserved orthogonality and symmetry conditions are determined by the method of least squares. A case study using computationally generated modal data is conducted, evaluating the numerical updating performance in terms of correction accuracy and reproduction of modal parameters. Finally, the transient structural response to an impulse excitation is compared between updated and reference model. The gathered results prove the method’s suitability as accurate and robust updating procedure, fostering its application in model-based monitoring frameworks.