Wavelet-based built-in damage detection and identification for composites

In this paper, a wavelet-based built-in damage detection and identification algorithm for carbon fiber reinforced polymer (CFRP) laminates is proposed. Lamb waves propagating in laminates are first modeled analytically using higher-order plate theory and compared them with experimental results in terms of group velocity. Distributed piezoelectric transducers are used to generate and monitor the fundamental ultrasonic Lamb waves in the laminates with narrowband frequencies. A signal processing scheme based on wavelet analysis is applied on the sensor signals to extract the group velocity of the wave propagating in the laminates. Combined with the theoretically computed wave velocity, a genetic algorithms (GA) optimization technique is employed to identify the location and size of the damage. The applicability of this proposed method to detect and size the damage is demonstrated by experimental studies on a composite plate with simulated delamination damages.