The detection of flaws in austenitic welds using the decomposition of the time reversal operator
Cunningham, Laura J. and Mulholland, Anthony J. and Tant, Katherine M. M. and Gachagan, Anthony and Harvey, Gerry and Bird, Colin (2016) The detection of flaws in austenitic welds using the decomposition of the time reversal operator. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 472 (2188). 20150500. ISSN 1471-2962 (https://doi.org/10.1098/rspa.2015.0500)
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Abstract
The non-destructive testing of austenitic welds using ultrasound plays an important role in the assessment of the structural integrity of safety critical structures. The internal microstructure of these welds is highly scattering and can lead to the obscuration of defects when investigated by traditional imaging algorithms. This paper proposes an alternative objective method for the detection of flaws embedded in austenitic welds based on the singular value decomposition of the time-frequency domain response matrices. The distribution of the singular values is examined in the cases where a flaw exists and where there is no flaw present. A lower threshold on the singular values, specific to austenitic welds, is derived which, when exceeded, indicates the presence of a flaw. The detection criterion is successfully implemented on both synthetic and experimental data. The datasets arising from welds containing a flaw, are further interrogated using the decomposition of the time reversal operator (DORT) method and the total focussing method (TFM) and it is shown that images constructed via the DORT algorithm typically exhibit a higher signal to noise ratio than those constructed by the TFM algorithm.
ORCID iDs
Cunningham, Laura J., Mulholland, Anthony J. ORCID: https://orcid.org/0000-0002-3626-4556, Tant, Katherine M. M. ORCID: https://orcid.org/0000-0003-4345-7054, Gachagan, Anthony ORCID: https://orcid.org/0000-0002-9728-4120, Harvey, Gerry and Bird, Colin;-
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Item type: Article ID code: 56153 Dates: DateEvent30 April 2016Published1 April 2016Published Online14 March 2016AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics
Faculty of Engineering > Electronic and Electrical EngineeringDepositing user: Pure Administrator Date deposited: 14 Apr 2016 14:52 Last modified: 24 Nov 2024 01:10 URI: https://strathprints.strath.ac.uk/id/eprint/56153