Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts
The ever-increasing use of complexly structured parts in modern manufacturing introduces new challenges to the inspection. However, high detection coverage and the contrast of ultrasonic images cannot be obtained by conventional B-scan imaging. To improve the quality of ultrasonic imaging of nonplan...
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sg-ntu-dr.10356-1613342022-08-25T08:46:14Z Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts Mei, Yujian Jin, Haoran Yu, Bei Wu, Eryong Li, Liqiang Yang, Keji School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Ultrasonic Image Reconstruction Robotics The ever-increasing use of complexly structured parts in modern manufacturing introduces new challenges to the inspection. However, high detection coverage and the contrast of ultrasonic images cannot be obtained by conventional B-scan imaging. To improve the quality of ultrasonic imaging of nonplanar components, we propose a robot-assisted track-scan imaging approach with multiple incident angles, and we have developed an ultrasonic data acquisition platform to implement it. The main idea of this method is to use multiple incident angles to improve the transfer of wave energy into the sample. Using rich information gathered from different incident angles, a nonplanar surface is correctly imaged by the proposed method. As seen from the experimental results, the proposed method can increase the detection coverage and contrast of images. Comparing different scanning trajectories and imaging methods, the detection coverage is improved by up to 57.3% and 88.7% for curved and inclined surfaces, respectively, by the proposed method. Similarly, the contrast-to-noise ratio increases up to 8.04 dB and 8.58 dB, respectively. Thus, our method has great potential for application in nondestructive ultrasonic imaging of complex-structure parts. 2022-08-25T08:46:14Z 2022-08-25T08:46:14Z 2021 Journal Article Mei, Y., Jin, H., Yu, B., Wu, E., Li, L. & Yang, K. (2021). Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts. Journal of Testing and Evaluation, 49(1), 675-689. https://dx.doi.org/10.1520/JTE20190908 0090-3973 https://hdl.handle.net/10356/161334 10.1520/JTE20190908 2-s2.0-85094979766 1 49 675 689 en Journal of Testing and Evaluation © 2021 ASTM International. All rights reserved. |
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Engineering::Electrical and electronic engineering Ultrasonic Image Reconstruction Robotics Mei, Yujian Jin, Haoran Yu, Bei Wu, Eryong Li, Liqiang Yang, Keji Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
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The ever-increasing use of complexly structured parts in modern manufacturing introduces new challenges to the inspection. However, high detection coverage and the contrast of ultrasonic images cannot be obtained by conventional B-scan imaging. To improve the quality of ultrasonic imaging of nonplanar components, we propose a robot-assisted track-scan imaging approach with multiple incident angles, and we have developed an ultrasonic data acquisition platform to implement it. The main idea of this method is to use multiple incident angles to improve the transfer of wave energy into the sample. Using rich information gathered from different incident angles, a nonplanar surface is correctly imaged by the proposed method. As seen from the experimental results, the proposed method can increase the detection coverage and contrast of images. Comparing different scanning trajectories and imaging methods, the detection coverage is improved by up to 57.3% and 88.7% for curved and inclined surfaces, respectively, by the proposed method. Similarly, the contrast-to-noise ratio increases up to 8.04 dB and 8.58 dB, respectively. Thus, our method has great potential for application in nondestructive ultrasonic imaging of complex-structure parts. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Mei, Yujian Jin, Haoran Yu, Bei Wu, Eryong Li, Liqiang Yang, Keji |
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Article |
author |
Mei, Yujian Jin, Haoran Yu, Bei Wu, Eryong Li, Liqiang Yang, Keji |
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Mei, Yujian |
title |
Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
title_short |
Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
title_full |
Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
title_fullStr |
Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
title_full_unstemmed |
Robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
title_sort |
robot-assisted track-scan imaging approach with multiple incident angles for complexly structured parts |
publishDate |
2022 |
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https://hdl.handle.net/10356/161334 |
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1743119615748210688 |