We describe a stochastic ltering approach for tracking progressive fatigue damage in structures, wherein physically based damage evolution information is combined with active sensing guided wave measurements. The input waveform used to excite dispersive modes within the structure is adaptively con gured at each time step in order to maximize the damage estimation performance. The damage evolution model is based on Paris Law, and hidden Markov modeling of time-frequency features obtained from received signals is used to de ne the measurement model. Damage state estimation is performed using a particle lter. Results are presented for fatigue crack estimation in an aluminum specimen.

Date Published: 20 November 2013
PDF: 12 pages
Proc. SPIE 8694, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2013, 869413 (20 November 2013); doi: 10.1117/12.2012278

Published in SPIE Proceedings Vol. 8694:
Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2013
Tzu Yang Yu, Editor(s)