Cross-correlation vibro-acoustic modulation method for damage detection

The vibroacoustic modulation (VAM) method distinguishes itself from other linear or nonlinear acoustic structure health monitoring methods due to its advantages of high sensitivity, relatively simple implementation, and the capability to detect defects in complex structures. However, the damaged index of VAM-modulation index, which is used for quantifying the damage severity, is highly influenced by the frequency of the probe wave. To increase the reliability and robustness of the VAM method, researchers modified it by replacing the single harmonic probe wave with a chirp signal. The instantaneous frequency of the chirp signal linearly increases with time, allowing the modified VAM method to access the broadband frequency range in a relatively short amount of time. However, the sideband that attributes to the acoustic nonlinearity of the defect would be overwhelmed by the broadband frequency content of the probe wave. Hence, a different algorithm is needed to process the received signal of the modified VAM method. Previous studies have employed short-time Fourier transform, wavelet transform, Hilbert transform, and synchronous demodulation for this purpose. Yet, these signal processing methods do not take into account affection of the phase difference between the probe and pump waves to the final result. To address this issue, this paper proposes using a cross-correlation (CC) approach. The performance of the proposed CC approach and existing methods were compared using simulation and experimental testing, evaluating their ability to detect acoustic nonlinearity.