Structural health monitoring applications for space structures

Structural health monitoring (SHM) will be an important component of the next generation satellites and space transportation vehicles. Many SHM systems create Lamb waves and monitor their propagation for detection of structural problems such as cracks and material losses. Use of s-transformation for inspection of the signal, and fitting time delay-attenuation (DA) models by using genetic algorithms had been proposed. Robustness and performance of this approach was evaluated at the noisy and unfavorable conditions in this paper. S-transformation indicated the number of waves and characteristics of the signal. GA estimated the time delay of the DA models with less than 2% error when the waves were 180 degree out of phase with the excitation signal even though the model could not represent the phase information. Estimation of new waves with significant attenuation indicated the development of defects. The time delay information of the new waves indicated the defect location.