New Algorithm Based on S-Transform to Increase Defect Resolution Within Ultrasonic Images

Recent years have seen a notable advance in the quality of produced industrial ultrasonic data. This is due to two main factors. On the one hand, advances on hardware level permitted to design and trigger ultrasound sensing arrays and matrices that led to new acquisition strategies such as phased array method and full matrix capture technique. On the other hand, the development of algorithms and software components to reconstruct and process the measured data allowed a major improvement of the signal and image quality. Within this aspect, modern signal processing algorithms improved the defect resolution and thus their detection in ultrasound data. Mostly, methods based on time-frequency analysis are used. The measure of the improvement resulting from the signal processing methodology can be confirmed, for instance, by evaluating A-scans containing defects near the front and the back wall of inspected specimens. In this work, we describe a novel algorithm for processing one-, two- or three-dimensional ultrasonic data, in order to increase their defect resolution. The algorithm is demonstrated using simulation phantom as well as on a real specimen both including defects at different depths. The proposed enhancement method is based on the Stockwell transform and normalized Hilbert envelope. Proposed method can effectively improve the quality of the ultrasound data.