Hybrid damage identification based on wavelet transform and finite element model updating

Structural health monitoring (SHM) has gained more attentions recently since nearly 140,000 of a total 600,000 highway bridges in the US are nearing 50 years of age and are approaching the end of their design life. Most in-service highway bridge structures are suspected to be undergoing deterioration processes induced by the physical and harsh environmental changes. Therefore, timely maintenance with a robust SHM system having capability of early detection of impending damage is required to prevent catastrophic events for the public safety with reduced expenses.;Vibrational modal properties may not be sufficient for detecting early damage in local regions of complex civil infrastructure. Moreover, most of current damage detection methods require reference data which are not always available. There have also been pressing needs for real-time monitoring to prevent sudden catastrophic disasters. This dissertation addresses current challenges and needs identified in existing vibration-based damage detection methods, focusing on wavelet-based reference-free real-time damage identification and subsequent finite element model updating for quantifying damage severity.;First, a damage detection method based on a wavelet entropy analysis has been embedded in wireless smart sensor nodes (Imote2) and tested with three-story shear building and a laboratory truss bridge structure. To realize the reference-free damage detection, a continuous relative wavelet entropy (CRWE)-based damage detection method is also proposed and demonstrated with a laboratory truss bridge structure. Although the reference-free CRWE method can detect damage locations without reference data, computational times put limitations in its applications to a real-time SHM system. To make real-time monitoring feasible in SHM systems, a statistical reference-free real-time damage detection method has been developed based on the wavelet packet transformation and log likelihood ratios.;Second, finite element model updating has been conducted to quantify the level of damage at the identified damage locations. For an identification model, fracture-mechanics based cracked beam element with local flexibility coefficients and rotational spring stiffness coefficients have been used. After experimental modal testing of the laboratory truss structure, modal properties are extracted by the output-only frequency domain decomposition method. Because of limited number of sensors, mode shapes of each panel of the structure are separately extracted and combined by the interface DOF-by-DOF decentralized modal identification method. Modal properties (i.e. mode shapes and natural frequencies) are used to quantify physical damage level in term of crack depth.;In summary, this dissertation proposed wavelet-based robust and viable real-time reference-free damage localization methods and conducted damage quantification by finite element model updating. The proposed method has been experimentally verified and evaluated using test-beds that include a three-story shear building structure and a laboratory truss bridge structure.