A Review of Signal Processing Techniques for Ultrasonic Guided Wave Testing

Ultrasonic guided wave testing (UGWT) is a non-destructive testing (NDT) technique commonly used in structural health monitoring to perform wide-range inspection from a single point, thus reducing the time and effort required for NDT. However, the multi-modal and dispersive nature of guided waves makes the extraction of essential information that leads to defect detection an extremely challenging task. The purpose of this article is to give an overview of signal processing techniques used for filtering signals, isolating modes and identifying and localising defects in UGWT. The techniques are summarised and grouped according to the geometry of the studied structures. Although the reviewed techniques have led to satisfactory results, the identification of defects through signal processing remains challenging with space for improvement, particularly by combining signal processing techniques and integrating machine learning algorithms.

Automated summary

This article provides an overview of signal processing techniques used for filtering signals, isolating modes, and identifying and localizing defects in ultrasonic guided wave testing (UGWT). The techniques are summarized and grouped based on the geometry of the tested structures. Although satisfactory results have been achieved, there is still room for improvement, especially by integrating machine learning algorithms to enhance defect identification.