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Advances in Quantitative Ultrasonic Sensing and Imaging
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Advances in Quantitative Ultrasonic Sensing and Imaging

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 7567

Special Issue Editors

Dr. Patrice Masson

E-Mail Website
Guest Editor
Département de génie mécanique – Mechanical Engineering, Université de Sherbrooke, Sherbrooke, PQ J1K 2R1, Canada
Interests: mechatronics; structural health monitoring; active noise control
Dr. Madis Ratassepp

E-Mail Website
Guest Editor
Department of Civil Engineering and Architecture, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia
Interests: nondestructive testing; waves; wave propagation; finite element analysis; composites; materials testing; finite element modeling; mechanical testing; material characterization; structural health monitoring
Dr. Jing Rao

E-Mail Website
Guest Editor
Chair of Computational Modeling and Simulation, Technical University of Munich, 80333 München, Germany
Interests: guided wave tomography; flexible sensor; ultrasonic imaging; inverse problem
Dr. Maria V. Felice

E-Mail Website
Guest Editor
Screening Eagle Technologies
Interests: quantitative NDT; multi-technology NDT; digitalization; ergonomics

Special Issue Information

Dear Colleagues,

Ultrasonic waves have long been one of the most utilized methods of non-destructive evaluation because of their ability to penetrate to the interior of metal, ceramic or composite parts, without causing harm to the operator or part. In addition, these waves exhibit rich propagation phenomena, which can be utilized in extracting a wide range of information about the structural integrity of a component. Although various implementations of ultrasound testing have existed for many years, the widespread use of more quantitative approaches is still limited. Accurate and efficient techniques are required to characterize complex flaws (such as cracks, corrosion, impact damage) in advanced materials and structures (pipes, composites, additively manufactured materials) using bulk and guided waves. This Special Issue focuses on computational and experimental approaches for the acquisition of two-dimensional and three-dimensional images. It comprises topics such as the development of accurate and efficient sensor and array measurement systems, data processing algorithms and computational methods for ultrasonic imaging, analytical and numerical forward and inverse modeling techniques, and innovative aspects of ultrasound sensing and imaging.

Dr. Patrice Masson
Dr. Madis Ratassepp
Dr. Jing Rao
Dr. Maria V. Felice
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ultrasonic imaging
  • ultrasound tomography
  • array
  • forward modeling
  • inverse problems
  • defect sizing

Published Papers (3 papers)

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Research

13 pages, 1462 KiB  
Article
Machine Learning for Touch Localization on an Ultrasonic Lamb Wave Touchscreen
by Sahar Bahrami, Jérémy Moriot, Patrice Masson and François Grondin
Sensors 2022, 22(9), 3183; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093183 - 21 Apr 2022
Cited by 1 | Viewed by 1858
Abstract
Classification and regression employing a simple Deep Neural Network (DNN) are investigated to perform touch localization on a tactile surface using ultrasonic guided waves. A robotic finger first simulates the touch action and captures the data to train a model. The model is [...] Read more.
Classification and regression employing a simple Deep Neural Network (DNN) are investigated to perform touch localization on a tactile surface using ultrasonic guided waves. A robotic finger first simulates the touch action and captures the data to train a model. The model is then validated with data from experiments conducted with human fingers. The localization root mean square errors (RMSE) in time and frequency domains are presented. The proposed method provides satisfactory localization results for most human–machine interactions, with a mean error of 0.47 cm and standard deviation of 0.18 cm and a computing time of 0.44 ms. The classification approach is also adapted to identify touches on an access control keypad layout, which leads to an accuracy of 97% with a computing time of 0.28 ms. These results demonstrate that DNN-based methods are a viable alternative to signal processing-based approaches for accurate and robust touch localization using ultrasonic guided waves. Full article
(This article belongs to the Special Issue Advances in Quantitative Ultrasonic Sensing and Imaging)
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14 pages, 41229 KiB  
Article
Acoustic Forward Model for Guided Wave Propagation and Scattering in a Pipe Bend
by Carlos-Omar Rasgado-Moreno, Marek Rist, Raul Land and Madis Ratassepp
Sensors 2022, 22(2), 486; https://0-doi-org.brum.beds.ac.uk/10.3390/s22020486 - 09 Jan 2022
Cited by 4 | Viewed by 2063
Abstract
The sections of pipe bends are hot spots for wall thinning due to accelerated corrosion by fluid flow. Conventionally, the thickness of a bend wall is evaluated by local point-by-point ultrasonic measurement, which is slow and costly. Guided wave tomography is an attractive [...] Read more.
The sections of pipe bends are hot spots for wall thinning due to accelerated corrosion by fluid flow. Conventionally, the thickness of a bend wall is evaluated by local point-by-point ultrasonic measurement, which is slow and costly. Guided wave tomography is an attractive method that enables the monitoring of a whole bend area by processing the waves excited and received by transducer arrays. The main challenge associated with the tomography of the bend is the development of an appropriate forward model, which should simply and efficiently handle the wave propagation in a complex bend model. In this study, we developed a two-dimensional (2D) acoustic forward model to replace the complex three-dimensional (3D) bend domain with a rectangular domain that is made artificially anisotropic by using Thomsen parameters. Thomsen parameters allow the consideration of the directional dependence of the velocity of the wave in the model. Good agreement was found between predictions and experiments performed on a 220 mm diameter (d) pipe with 1.5d bend radius, including the wave-field focusing effect and the steering effect of scattered wave-fields from defects. Full article
(This article belongs to the Special Issue Advances in Quantitative Ultrasonic Sensing and Imaging)
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16 pages, 32286 KiB  
Article
Probe Standoff Optimization Method for Phased Array Ultrasonic TFM Imaging of Curved Parts
by Jorge Franklin Mansur Rodrigues Filho and Pierre Bélanger
Sensors 2021, 21(19), 6665; https://0-doi-org.brum.beds.ac.uk/10.3390/s21196665 - 07 Oct 2021
Cited by 9 | Viewed by 2799
Abstract
The reliability of the ultrasonic phased array total focusing method (TFM) imaging of parts with curved geometries depends on many factors, one being the probe standoff. Strong artifacts and resolution loss are introduced by some surface profile and standoff combinations, making it impossible [...] Read more.
The reliability of the ultrasonic phased array total focusing method (TFM) imaging of parts with curved geometries depends on many factors, one being the probe standoff. Strong artifacts and resolution loss are introduced by some surface profile and standoff combinations, making it impossible to identify defects. This paper, therefore, introduces a probe standoff optimization method (PSOM) to mitigate such effects. Based on a point spread function analysis, the PSOM algorithm finds the standoff with the lowest main lobe width and side lobe level values. Validation experiments were conducted and the TFM imaging performance compared with the PSOM predictions. The experiments consisted of the inspection of concave and convex parts with amplitudes of 0, 5 and 15 λAl, at 12 standoffs varying from 20 to 130 mm. Three internal side-drilled holes at different depths were used as targets. To investigate how the optimal probe standoff improves the TFM, two metrics were used: the signal-to-artifact ratio (SAR) and the array performance indicator (API). The PSF characteristics predicted by the PSOM agreed with the quality of TFM images. A considerable TFM improvement was demonstrated at the optimal standoff calculated by the PSOM. The API of a convex specimen’s TFM was minimized, and the SAR gained up to 13 dB, while the image of a concave specimen gained up to 33 dB in SAR. Full article
(This article belongs to the Special Issue Advances in Quantitative Ultrasonic Sensing and Imaging)
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