Structural Damage Assessment under Uncertainty

Structural damage assessment has applications in the majority of engineering structures and mechanical systems ranging from aerospace vehicles to manufacturing equipment. The primary goals of any structural damage assessment and health monitoring systems are to ascertain the condition of a structure and to provide an evaluation of changes as a function of time as well as providing an early-warning of an unsafe condition. There are many structural heath monitoring and assessment techniques developed for research using numerical simulations and scaled structural experiments. However, the transition from research to real-world structures has been rather slow. One major reason for this slow-progress is the existence of uncertainty in every step of the damage assessment process.;This dissertation research involved the experimental and numerical investigation of uncertainty in vibration-based structural health monitoring and development of robust detection and localization methods. The basic premise of vibration-based structural health monitoring is that changes in structural characteristics, such as stiffness, mass and damping, will affect the global vibration response of the structure. The diagnostic performance of vibration-based monitoring system is affected by uncertainty sources such as measurement errors, environmental disturbances and parametric modeling uncertainties. To address diagnostic errors due to irreducible uncertainty, a pattern recognition framework for damage detection has been developed to be used for continuous monitoring of structures. The robust damage detection approach developed is based on the ensemble of dimensional reduction algorithms for improved damage-sensitive feature extraction. For damage localization, the determination of an experimental structural model was performed based on output-only modal analysis. An experimental model correlation technique is developed in which the discrepancies between the undamaged and damaged modal data are isolated based on the integration of sensitivity analysis and statistical sampling, which minimizes the occurrence of false-damage indication due to uncertainty. To perform diagnostic decision-making under uncertainty, an evidential reasoning approach for damage assessment is developed for addressing the possible imprecision in the damage localization results. The newly developed damage detection and localization techniques are applied and validated through both vibration test data from literature and in house laboratory experiments.