Damage state evaluation of adhesive composite joints using chaotic ultrasonic waves

Ultrasonic chaotic excitations combined with sensor prediction algorithms have shown the ability to identify incipient damage (loss of preload) in a bolted joint. In this study we examine the capability of this damage detection scheme to identify disbonds and poorly cured bonds in a composite-to-composite adhesive joint. The test structure consists of a carbon fiber reinforced polymer (CFRP) plate that has been bonded to a CFRP rectangular tube/spar with several sizes of disbond as well as a poorly cured section. Each excitation signal is imparted to the CFRP plate through a macro-fiber composite (MFC) patch on one side of the adhesive joint and sensed using an equivalent MFC patch on the opposite side of the joint. A novel statistical classification feature is developed from information theory concepts of cross-prediction and interdependence. Temperature dependence of this newly developed feature will also be examined.