Resonant ultrasound spectroscopy (RUS) allows identification of the elastic properties of solid materials vibrating under an ultrasonic excitation from the measurement of their inherent frequencies. Retrieving the resonant frequencies is… Click to show full abstract
Resonant ultrasound spectroscopy (RUS) allows identification of the elastic properties of solid materials vibrating under an ultrasonic excitation from the measurement of their inherent frequencies. Retrieving the resonant frequencies is therefore a key signal processing step in RUS, which is generally addressed using a linear prediction filter. In this study, the Empirical Mode Decomposition (EMD) was proposed to retrieve the inherent resonant frequencies of materials with low Q-factor (quality factor). EMD was used to decompose the frequency response of the tested sample into intrinsic mode functions (IMF). The relevant IMF was selected from which the resonant frequencies could be computed. A bovine cortical bone sample was measured and its resonant frequencies were identified with EMD and with linear prediction for comparison. The elastic constants were also derived using both approaches. The number of resonant frequencies (45) extracted with EMD was larger than the number of frequencies (26) identified using the classical linear prediction approach. In particular, EMD proved to be more effective in detecting resonance in the higher frequency range (i.e., between 235 kHz and 400 kHz), i.e., on the weak excitation side where the spectral amplitude is low. The number of measured frequencies matching with the calculated ones was also larger for EMD (39) compared to linear prediction (17). If these results are confirmed in further studies on more samples, EMD combined with RUS, by improving the extraction of resonant frequencies for low Q-factor materials, may be considered to be useful not only to improve the reliability of the estimation of elastic parameters, but also to extend the application range of RUS.
               
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