Acoustic Emission

Acoustic emission (AE) analysis involves detecting and interpreting transient elastic waves generated by material deformation or fracture, primarily aiming to locate damage sources and monitor structural health. Current research heavily utilizes machine learning, particularly convolutional neural networks and Gaussian processes, often coupled with signal processing techniques like wavelet transforms, to improve source localization accuracy and reduce data acquisition needs. This approach is proving valuable in diverse applications, from monitoring the condition of bolted joints and predicting porosity in additive manufacturing to detecting sunquakes and enhancing predictive maintenance strategies for complex structures.