Noise reduction in ultrasonic Non-Destructive Evaluation (NDE) and imaging

Li, M. and Hayward, G. (2018) Noise reduction in ultrasonic Non-Destructive Evaluation (NDE) and imaging. In: Farrow, M. (ed.) Noise Reduction: Methods, Applications and Technology. Nova Science Publishers Inc: New York, pp. 147-169. ISBN 9781536135411

Abstract

Reliable and robust defect detection is a challenging yet essential problem in ultrasonic non-destructive evaluation (NDE). The flaw echoes are usually contaminated by high-level time-invariant grain noise originating from the material microstructures. This phenomenon becomes even worse when inspecting coarse-grained materials like austenitic stainless steel, alloy, carbon-reinforced composite and concrete, which however, form some of the most important and commonly used industrial materials. This problem has attracted great attentions from the NDE community and a wide variety of techniques have been investigated to enhance the signal-to-noise ratio (SNR) and flaw detection. In this chapter, the signal processing approaches that exploit the spatial and temporal-spectral characteristics of the flaw echo and noise for enhanced defect detection and noise reduction in ultrasonic NDE are presented. The first category of techniques exploits the spatial diversity created by the transducer array, and utilises spatial filtering to discriminate the flaw echo from the clutter noise. Particularly, minimum variance beamforming seeks to minimize the power of the array output while maintaining a unit gain on the focal point, and weighs the observations with data-dependent apodization. The second category of approaches investigates the time-frequency analysis and statistical properties of flaw echoes and grain noise. In particular, the advanced matched filter is designed to match unknown flaw echoes rather than the transmitted signal, and utilise an optimization paradigm to tweak and search the best filter parameters. Results from simulation studies and experiments on the real industrial samples are presented to evaluate the techniques, and demonstrate their robustness and advantages over the classical methods.

• Item Type: Book Sections
• Status: Published
• Glasgow Author(s) Enlighten ID: Li, Dr David
• Authors: Li, M., and Hayward, G.
• Subjects: T Technology > TA Engineering (General). Civil engineering (General); T Technology > TJ Mechanical engineering and machinery; T Technology > TK Electrical engineering. Electronics Nuclear engineering
• College/School: College of Science and Engineering > School of Engineering
• Publisher: Nova Science Publishers Inc
• ISBN: 9781536135411
• Copyright Holders: Copyright © 2018 Nova Science Publishers
• Publisher Policy: Reproduced in accordance with the publisher copyright policy