Use of chaotic excitation and attractor property analysis in structural health monitoring.

This work explores the utility of attractor-based approaches in the field of vibration-based structural health monitoring. The technique utilizes the unique properties of chaotic signals by driving the structure directly with the output of a chaotic oscillator. Using the Kaplan-Yorke conjecture, the Lyapunov exponents of the driving signal may be tuned to the dominant eigenvalues of the structure, thus controlling the dimension of the structural response. Data are collected at various stages of structural degradation and a simple nonlinear model, constructed from the undamaged data, is used to make predictions for the damaged response data. Prediction error is then introduced as a "feature" for classifying the magnitude of the damage. Results are presented for an experimental cantilevered beam instrumented with fiber-optic strain sensors.