Developing a supervised machine‐learning model capable of distinguishing fiber orientation of polymer composite samples nondestructively tested using active ultrasonics

Abstract This study evaluated the paired performance of different signal processing techniques and supervised learning models being capable of identifying subtle differences in otherwise similar acoustic signals related to detecting the fiber orientation of a polymer composite. Projection of Latent Structures models demonstrated poor predictive capabilities of the composite structure based on spectral analysis of the acoustic signal. AI based …