Method for automated crack detection and analysis using ultrasound images

Abstract

A computer-based method and system for predicting the propagation of cracks along a pipe is provided, wherein successive time-indexed ultrasound images of a pipe surface are captured and digitized. A computer vision algorithm processes the images to identify defects in the pipe, including cracks. At least one blob detection module is used to identify groups of cracks on the pipe surface that have created detectable areas of stress concentration or a prescribed likelihood of crack coalescence or crack cross-influence. The center locations and radial extents of respective blobs are each parametrized as a function of time and pipe surface location by determining parity relationships between successive digital data sets from successive captured images. The determined parity relationships are then used as training data for a machine learning process to train a system implementing the method to predict the propagation of cracks along the pipe.