Ultrasonic Defect Mapping Using Signal Correlation for Nondestructive Evaluation (NDE)

This article presents the application of a signal correlation technique to automatically classify ultrasonic A-scan signals for defect and defect-free regions in isotropic and anisotropic materials. First, feature extraction was implemented by generating a reference A-scan signal of a defect-free area using an autocorrelation function and statistics. Then, a cross-correlation function, utilized as a feature detector, was applied to the reference signal and a signal of interest (SOI) to detect defect-free features in an SOI. The correlation result was considered as a pattern containing both defect and defect-free features. Next, the pattern was classified by measuring the similarity between features of the reference signal and an SOI based on their Euclidean distance. Each A-scan signal classification result was then plotted on a 2D map based on its position on the specimen. The present work uses multiple correlation functions and statistics to classify defect signals rather than relying on an inspector's prior knowledge to interpret C-scan data, and has particular value in automated ultrasonic signal classification and characterization.