Abstract: Acoustic sensing has become an increasingly important enabling technology for nondestructive evaluation, condition monitoring, and intelligent perception. Conventional acoustic and ultrasonic inspection methods have been widely applied to structural health monitoring (SHM), nondestructive testing (NDT), and industrial inspection. More recently, advances in artificial intelligence, signal processing, novel acoustic transducers, embedded sensing systems, and edge computing have considerably expanded the scope of acoustic nondestructive sensing toward more complex and interdisciplinary applications.

In particular, intelligent acoustic sensing is no longer limited to the inspection of engineering structures. Acoustic emission, ultrasonic sensing, laser ultrasonics, guided waves, vibration-acoustic sensing, and related techniques are increasingly being explored for applications including infrastructure monitoring, advanced manufacturing, agricultural systems, food quality assessment, biological materials, precision agriculture, and other emerging sensing scenarios. Meanwhile, machine learning and artificial intelligence are enabling acoustic sensing systems to automatically extract informative features, identify defects or abnormal conditions, quantify material properties, and support decision-making from complex and noisy measurements.