Paper
20 November 2013 Active sensing waveform design for estimating progressive fatigue damage in structures
Daniel Huff, Narayan Kovvali, Antonia Papandreou-Suppappola, Aditi Chattopadhyay, Subhasish Mohanty
Author Affiliations +
Abstract
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.
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Daniel Huff, Narayan Kovvali, Antonia Papandreou-Suppappola, Aditi Chattopadhyay, and Subhasish Mohanty "Active sensing waveform design for estimating progressive fatigue damage in structures", Proc. SPIE 8694, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2013, 869413 (20 November 2013); https://doi.org/10.1117/12.2012278
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KEYWORDS
Particles

Sensors

Time-frequency analysis

Active remote sensing

Structural health monitoring

Data modeling

Receivers

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