Zero-Defect Manufacturing and Automated Defect Detection Using Time of Flight Diffraction (TOFD) Images

Data Availability Statement: Data available on request due to restrictions eg privacy or ethical.Copyright © 2022 by the authors.Ultrasonic time-of-flight diffraction (TOFD) is a non-destructive testing (NDT) technique for weld inspection that has gained popularity in the industry, due to its ability to detect, position, and size defects based on the time difference of the echo signal. Although the TOFD technique provides high-speed data, ultrasonic data interpretation is typically a manual and time-consuming process, thereby necessitating a trained expert. The main aim of this work is to develop a fully automated defect detection and data interpretation approach that enables predictive maintenance using signal and image processing. Through this research, the characterization of weld defects was achieved by identifying the region of interest from A-scan signals, followed by segmentation. The experimental results were compared with samples of known defect size for validation; it was found that this novel method is capable of automatically measuring the defect size with considerable accuracy. It is anticipated that using such a system will significantly increase inspection speed, cost, and safety.The research leading to these results has received funding from the UK’s innovation agency, Innovate UK, under grant agreement No. 103991. The research has been undertaken as a part of the project Amphibious robot for inspection and predictive maintenance of offshore wind assets (iFROG). The iFROG project is a collaboration between the following organizations: Innovative Technology and Science Ltd., Brunel University London, TWI Ltd., and ORE Catapult Development Services Ltd

Multiframe Ultrasonic TOFD Weld Inspection Imaging Based on Wavelet Transform and Image Registration

TOFD (time of flight diffraction) is a kind of weld defect detection technology by using ultrasonic diffraction wave signal. Because the diffraction intensity is far less than ultrasonic echo wave intensity, thus, the noise contained in TOFD signal is fairly large, and the formed image is not clear enough. Therefore, it is difficult to determine the size of defects accurately. In this paper, a method of noise reduction of TOFD signal and improving the resolution of the image are discussed based on the combination of wavelet thresholding and image registration. Wavelet multiresolution analysis method is adopted and the A-scan signal is decomposed into different frequency components. We propose a new threshold function to process the wavelet coefficients, which guarantees to denoise while preserving the useful information as much as possible. Setting up the ultrasonic TOFD inspection system and the image data with randomly distributed noise can be obtained via fine shake of the probes during testing. Then, image registration based on maximum correlation and blending is adopted to eliminate the noise in further step. The result shows that the proposed method can achieve denoising, together with resolution enhancement