Structural integrity monitoring of composite patch repairs using wavelet analysis and neural networks

Bonded composite repairs for the reinforcement of damaged aircraft structures are effective in extending the life of aging airframes. The structural integrity of the composite patch repair in terms of disbond, fracture at the bond-lines, delamination, and structural crack growth is to be investigated before the composite repair technology can be adopted by the aerospace industry. We have developed structural health monitoring techniques for locating, identifying, and quantifying damages using the changes in the dynamical response of the repaired structure. A signal-based health monitoring algorithms wavelet transforms, have been developed for monitoring the structural integrity of composite patches, which detects variations induced by small changes in the vibration signature of the repaired structure. In this paper, threshold wavelet maps and neural networks have been integrated to detect and quantify the damage (s) in the composite patch repairs. Neural networks are utilized to find the extent of the damage. This method is also capable of detecting multiple damages. The mode shapes are obtained analytically using finite element analysis and experimentally with laser vibrometer. We have also developed a wireless data acquisition system for collection, feature extraction, and transmission of vibration data. The results of the damage location and extent estimation in the composite patch repairs are satisfactory.