A loewner-based system identification and structural health monitoring approach for mechanical systems

Abstract

Data-driven structural health monitoring (SHM) requires precise estimates of the target system behaviour. In this sense, SHM by means of modal parameters is strictly linked to system identi5cation (SI). However, existing frequency-domain SI techniques have several theoretical and practical drawbacks.*is paper proposes using an input-output system identi5cation technique based on rational interpolation, known as the Loewner framework (LF), to estimate the modal properties of mechanical systems. Pioneeringly, the Loewner framework mode shapes and natural frequencies estimated by LF are then applied as damage-sensitive features for damage detection. To assess its capability, the Loewner framework is validated on both numerical and experimental datasets and compared to established system identi5cation techniques. Promising results are achieved in terms of accuracy and reliability.