From detection to prediction of damage in thin-walled structures: A review on engineering acoustics and machine-learning methods

In the field of engineering acoustics, the communities of non-destructive testing and structural health monitoring rarely interact on shared scientific platforms. However, the similarities between acoustic and elastic wave propagation encourage research synergies in damage detection and localization methodologies. This compilation provides a shared perspective on methods for detecting and predicting damage using elastic and acoustic waves. Methods for detecting and predicting damage in thin-walled structures were reviewed. Active methods for mapping stationary defects using elastic waves were addressed. Passive methods for localizing active acoustic (audible sound) and elastic (acoustic emission) sources were illustrated. Both approaches were summarized in terms of conventional and advanced detection and localization methods, including wave-propagation-based and machine-learning approaches. The fundamentals of elastic and acoustic wave propagation were briefly introduced. The sensing principles of contact piezoelectric sensors and non-contact microphones were described in the context of non-destructive testing and structural health monitoring. Application examples of selected passive methods were shown. This paper discusses how the reviewed conventional and advanced methods can be employed to predict damage evolution in practical applications.