The application of an acoustic emission technique in the delamination of laminated composites

Fiber reinforced plastic composites are being increasingly used in engineering applications due to their high specific stiffness and strength. On the other hand, the incidence of internal defects may considerably alter the stiffness and reduce the strength and lifetime of the composites. The principal mode of failure in laminated composite materials is delamination. It can be caused by manufacturing faults or subsequent operational effects such as impact loads, fatigue, etc. It usually occurs within the structure and it is difficult to distinguish during the inspection. Therefore, it is not easy to detect the delamination existence and to characterize the onset and growth of it. Acoustic Emission (AE) is a capable non-destructive method to study the delamination damage. This
chapter represents the application of AE method to investigate delamination of laminated composite materials in two major sections:
• Initiation of damage: Various approaches such as AE energy, AE count, AE cumulative energy, and Sentry function are described as appropriate tools to determine interlaminar fracture toughness (GC) of composite materials. The AE results are also compared with the results of ASTM standard methods. It is
shown that the GC values obtained by the AE-based methods are in a close agreement with the ASTM results.
• Progression of damage: AE technique is utilized to predict delamination evolution curve, and to classify different damage mechanisms occurring during delamination propagation. In order to predict delamination evolution curve, two different AEbased procedures are presented. In the first method, after
determining the velocity of the AE waves in the composite specimens, the position of the crack tip can be estimated using two AE sensors. In the second method, the cumulative energy of the AE signals is utilized for localization of the crack tip. A very good agreement between the AE-predicted crack length and the
actual crack length verifies the accuracy of the presented procedures. Finally, wavelet packet transform and fuzzy clustering methods are used to classify the dominant damage mechanisms based on their AE signatures. Scanning electron
microscopic observations from the damage mechanisms are in a good agreement with the AE-based classification results.
In conclusion, the results indicate that AE has a good performance to
detect initiation stage of delamination, determining the delamination
crack length, and discriminating the different types of damage
mechanisms in the laminated composite structures.