Combining Digital Image Correlation and Acoustic Emission to Characterize the Flexural Behavior of Flax Biocomposites

Abstract

Understanding the effect of staking sequences and identifying the damage occurring within a structure using a structural health monitoring system are the keys to an efficient design of composite-based parts. In this research, a combination of digital image correlation (DIC) and acoustic emission (AE) is used to locate and classify the type of damage depending on the stacking sequence of the laminate during flexural loading. As a first step, the results of the strain fields for unidirectional, cross-ply, and quasi-isotropic laminates were compared to discuss their global behavior and to correlate the different damage patterns with the possible failure mechanisms. The damage was then addressed using a comprehensive interpretation of the acoustic emission signatures and the K-means classification of the acoustic events. The development of each damage mechanism was correlated to the applied load and expressed as a function of the loading rate to highlight the effect of the stacking sequence. Finally, the results of DIC and AE were combined to improve the reliability of the damage investigation without limiting the failure mechanism to matrix cracking, interfacial failure, and fiber breakage, as expected by the unsupervised event clustering.