Exploring damage sensitivity of state-space based prediction error methods for structural health monitoring

摘要

One paradigm within the structural health monitoring field involves analyzing the vibration response of structures as a method of detecting damage. Recent work has focused on extracting damage-sensitive features from the state-space representation of the structural response. Some of these features involve constructing a baseline attractor and an attractor at some later time and using the baseline to predict the evolution of the future attractor. An inability to accurately predict said evolution can be construed as possible damage to the structure. Such attractor-based methods are sensitive to a number of parameters related to reconstruction of the attractor, prediction techniques, and statistical accuracy. This work couples various input excitations with experimental data in an attempt to optimize these parameters for maximum sensitivity to damage.