Within the field of structural health monitoring (SHM), active sensing methods involve exciting a structure and extracting features from the vibration response as damage-sensitive indicators. Research recently has brought forth a number of state-space methods, whereby features are derived from properties of attractors. Pattern recognition algorithms are applied to the attractors reconstructed from the dynamics in an attempt to recognize damage to the structure. This work explores the efficacy of various attractor-based features as indicators of bolt preload loss in a stainless steel frame. Steady-state chaotic and band-limited stochastic inputs are considered as excitation waveforms.
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