Integration of acoustic emission and digital image correlation for damage of composite panels with different layup sequences

Prepreg and woven fabric are two primary materials of new-energy electric aircraft. Their mechanical behavior and damage expansion under different layup sequences are significant in design and maintenance of electric aircraft. The present work develops a combined experimental platform of acoustic emission and digital image correlation. The tensile damage process of two materials under different layup sequences is investigated by varying the waveform characteristic parameters and surface strain field. The damage of the [(±45)]_6S specimen was classified using principal component analysis and fuzzy c-means clustering algorithm. The results showed that the material type and layup sequence significantly affect the specimen's mechanical properties and damage expansion. The acoustic emission signal characteristics of the layup specimens of the same material along the warp and the weft directions are similar but significantly different from those laid along 45°. The damage to all five specimens starts from the edge of the specimen to the middle and is finally destroyed along the direction of the paving layer. The damage of [(±45)]_6S specimens was mainly caused by matrix cracking and fiber fracture. The specimen with fiber fracture initiation was later than debonding and matrix cracking. The results provide a scientific basis for aircraft design and health monitoring.