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Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing

Ultrasonic guided wave (UGW) testing is widely applied in numerous industry areas for the examination of pipelines where structural integrity is of concern. Guided wave testing is capable of inspecting long lengths of pipes from a single tool location using some arrays of transducers positioned arou...

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Autores principales: Pedram, Seyed Kamran, Gan, Tat-Hean, Ghafourian, Mahdieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506708/
https://www.ncbi.nlm.nih.gov/pubmed/32842489
http://dx.doi.org/10.3390/s20174759
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author Pedram, Seyed Kamran
Gan, Tat-Hean
Ghafourian, Mahdieh
author_facet Pedram, Seyed Kamran
Gan, Tat-Hean
Ghafourian, Mahdieh
author_sort Pedram, Seyed Kamran
collection PubMed
description Ultrasonic guided wave (UGW) testing is widely applied in numerous industry areas for the examination of pipelines where structural integrity is of concern. Guided wave testing is capable of inspecting long lengths of pipes from a single tool location using some arrays of transducers positioned around the pipe. Due to dispersive propagation and the multimodal behavior of UGW, the received signal is usually degraded and noisy, that reduce the inspection range and sensitivity to small defects. Therefore, signal interpretation and identifying small defects is a challenging task in such systems, particularly for buried/coated pipes, in that the attenuation rates are considerably higher compared with a bare pipe. In this work, a novel solution is proposed to address this issue by employing an advanced signal processing approach called “split-spectrum processing” (SSP) to minimize the level of background noise and enhance the signal quality. The SSP technique has already shown promising results in a limited trial for a bar pipe and, in this work, the proposed technique has been experimentally compared with the traditional approach for coated pipes. The results illustrate that the proposed technique significantly increases the signal-to-noise ratio and enhances the sensitivity to small defects that are hidden below the background noise.
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spelling pubmed-75067082020-09-26 Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing Pedram, Seyed Kamran Gan, Tat-Hean Ghafourian, Mahdieh Sensors (Basel) Article Ultrasonic guided wave (UGW) testing is widely applied in numerous industry areas for the examination of pipelines where structural integrity is of concern. Guided wave testing is capable of inspecting long lengths of pipes from a single tool location using some arrays of transducers positioned around the pipe. Due to dispersive propagation and the multimodal behavior of UGW, the received signal is usually degraded and noisy, that reduce the inspection range and sensitivity to small defects. Therefore, signal interpretation and identifying small defects is a challenging task in such systems, particularly for buried/coated pipes, in that the attenuation rates are considerably higher compared with a bare pipe. In this work, a novel solution is proposed to address this issue by employing an advanced signal processing approach called “split-spectrum processing” (SSP) to minimize the level of background noise and enhance the signal quality. The SSP technique has already shown promising results in a limited trial for a bar pipe and, in this work, the proposed technique has been experimentally compared with the traditional approach for coated pipes. The results illustrate that the proposed technique significantly increases the signal-to-noise ratio and enhances the sensitivity to small defects that are hidden below the background noise. MDPI 2020-08-23 /pmc/articles/PMC7506708/ /pubmed/32842489 http://dx.doi.org/10.3390/s20174759 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pedram, Seyed Kamran
Gan, Tat-Hean
Ghafourian, Mahdieh
Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing
title Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing
title_full Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing
title_fullStr Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing
title_full_unstemmed Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing
title_short Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing
title_sort improved defect detection of guided wave testing using split-spectrum processing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506708/
https://www.ncbi.nlm.nih.gov/pubmed/32842489
http://dx.doi.org/10.3390/s20174759
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