Automatic detection, sizing and characterisation of weld defects using ultrasonic time-of-flight diffraction

摘要

Ultrasonic time-of-flight diffraction (TOFD) is known as a reliable non-destructive testing technique for weld inspection in steel structures, providing accurate aw positioning and sizing. Despite all its good features, TOFD data interpretation and reporting are still performed manually by skilled inspectors and interpretation software operators. This is a cumbersome and error-prone process, leading to inevitable delay and inconsistency. The quality of the collected TOFD data is another issue that may introduce a host of error to the overall interpretation process. Manual interpretation focuses only on the compression waves portion of the collected TOFD data and overlooks the mode-converted waves region and considers it redundant. This region may provide useful and accurate aw sizing and classification information when there is uncertainty or ambiguity due to the nature of the collected data or the type of aw, and can reduce the number of supplementary (parallel) B-scans by utilising the (longitudinal) D-scans only. The automation of data processing in TOFD is required to minimise time and error and towards building a comprehensive computer-aided TOFD interpretation tool that can aid human operators. This project aims at proposing interpretation algorithms to size and characterise flaws automatically and accurately using data acquired from D-scans only. In order to achieve this, a number of novel data manipulation and processing techniques have been specifically developed and adapted to expose the information in the mode-converted waves region. In addition, several multi-resolution approaches employing the Wavelet transform and texture analysis have been used in aw detection and for de-noising and enhancing quality of the collected data. Performance of the developed algorithms and the results of their application have been promising in terms of speed, accuracy and consistency when compared to human interpretation by an expert operator, using the compression waves portion of the acquired data. This is expected to revolutionise the TOFD data interpretation and be in favour of a real-time processing of large volumes of data. It is highly anticipated that the research findings of this project will increase significantly the reliance on D-scans to obtain high sizing accuracy without the need to perform further B-scans. The overall inspection and interpretation time and cost will therefore be reduced significantly.