Artificial Neural Network Prediction of Ultimate Strength of Unidirectional T-300/914 Tensile Specimens Using Acoustic Emission Response

Acoustic Emission (AE) Monitoring was used to evaluate unidirectional carbon epoxy specimens when tensile loaded with a 100 kN Universal Testing Machine. A series of eighteen samples were loaded to failure to generate AE data for this analysis. After data acquisition, AE response from each test was filtered to include only data collected up to 50% of the actual failure load for further analysis. Amplitude, Duration and Energy are effective parameters utilized to differentiate various failure modes in composites viz., matrix crazing, fiber cut, and delamination with several sub categories such as matrix splitting, fiber/matrix debonding, fiber pull-out etc.