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NDT, Volume 1, Issue 1 (December 2023) – 6 articles

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16 pages, 4842 KiB  
Article
Ultrasonic Non-Contact Air-Coupled Technique for the Assessment of Composite Sandwich Plates Using Antisymmetric Lamb Waves
by Eduardo Moreno, Roberto Giacchetta, Ricardo Gonzalez, David Sanchez, Olalla Sanchez-Sobrado, Andrea Torre-Poza, Guillermo Cosarinsky and Wagner Coelho
NDT 2023, 1(1), 58-73; https://doi.org/10.3390/ndt1010006 - 28 Oct 2023
Viewed by 1025
Abstract
This paper describes the design and implementation of an ultrasonic non-contact air-coupled technique (UNCACT) using antisymmetric Lamb waves (ALW) for NDT assessments in novel composite sandwich plates of a car body shell. This technique is complemented with a C-Scan image implementation using guided [...] Read more.
This paper describes the design and implementation of an ultrasonic non-contact air-coupled technique (UNCACT) using antisymmetric Lamb waves (ALW) for NDT assessments in novel composite sandwich plates of a car body shell. This technique is complemented with a C-Scan image implementation using guided waves. The finite element method (FEM) was developed using Comsol 6.1 for the interpretation of the several wave modes presented in the experiments, including the ALW mode. This FEM model is indispensable for the correct interpretation of the received signals and contributes to a better implementation of this technology. This is a novel contribution building upon previously reported work. Additionally, the phase velocity method (PVM) was applied for the verification of the ALW mode in the portion of the RF signal necessary for the C-Scan image. Full article
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12 pages, 11307 KiB  
Article
Wind Turbine Surface Defect Detection Method Based on YOLOv5s-L
by Chang Liu, Chen An and Yifan Yang
NDT 2023, 1(1), 46-57; https://doi.org/10.3390/ndt1010005 - 13 Oct 2023
Cited by 1 | Viewed by 920
Abstract
In order to solve the problems of low efficiency, time consumption and high costs in the detection of defects on wind turbine surfaces in industrial scenarios, an improved YOLOv5 algorithm for wind turbine surface defect detection is proposed, named YOLOv5s-L. Firstly, the C3 [...] Read more.
In order to solve the problems of low efficiency, time consumption and high costs in the detection of defects on wind turbine surfaces in industrial scenarios, an improved YOLOv5 algorithm for wind turbine surface defect detection is proposed, named YOLOv5s-L. Firstly, the C3 module of YOLOv5s is replaced with the C2f module, which is more abundant in gradient flow, to enhance the ability of feature extraction and feature fusion. Secondly, the Squeeze and Excitation (SE) module is embedded in the YOLOv5 Backbone network to filter out redundant feature information and retain important feature information. Thirdly, the weighted Bidirectional Feature Pyramid Network (BiFPN) is introduced to replace the FPN + PAN, which can achieve a higher level of feature fusion while keeping the weight light. Finally, the Focal Loss function is used to replace the CIOU Loss function of the YOLOv5 algorithm to optimize the training model and improve the accuracy of the algorithm. The experimental results show that, compared with the traditional YOLOv5 algorithm, the average precision mAP is improved by 1.9%, and the frame rate FPS can reach 145 F/s without increasing the model parameters; it can satisfy the requirements for real-time, accurate detection on mobile devices. This method provides effective support for surface defect detection of wind turbines and provides reference for intelligent wind farm operation and maintenance. Full article
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11 pages, 9412 KiB  
Article
A Novel Method for Reducing the Lift-Off Effect in Coercivity Measurement through Auxiliary Inductance Data
by Ruilin Lyu, Tian Meng, Yuchun Shao, Jorge Ricardo Salas Avila and Wuliang Yin
NDT 2023, 1(1), 35-45; https://doi.org/10.3390/ndt1010004 - 09 Sep 2023
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Abstract
Coercivity is the strength of the reverse magnetic field required to demagnetize a material after saturation, and it is an indication of the hardness of magnetic materials. Air gaps cause errors in coercivity measurement referred to as the lift-off effect. This paper proposes [...] Read more.
Coercivity is the strength of the reverse magnetic field required to demagnetize a material after saturation, and it is an indication of the hardness of magnetic materials. Air gaps cause errors in coercivity measurement referred to as the lift-off effect. This paper proposes a new method to address this issue by incorporating additional inductance measurements and formulating a calibration method. The calibration principle is based on the fact that both the coercivity and the inductance measurements change with the variation of air gaps. This paper starts by finding how coercivity changes with air gaps between the sensor and the sample, then derives the coefficients for the coercivity–inductance relationship for different samples. A correction method is then proposed to predict the base coercivity (i.e., the coercivity when the air gap = 0) using the inductance and coercivity measurement results at an unknown lift-off. The measurement system was implemented, and experimental results suggest the error caused by air gaps can be reduced from 40% to less than 10%. Full article
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13 pages, 9276 KiB  
Article
Development of Non-Destructive Dynamic Characterization Technique for MMCs: Predictions of Mechanical Properties for Al@Al2O3 Composites
by Ajay D. Pingale, Diplesh Gautam, Ayush Owhal, Dhruv Deshwal, Sachin U. Belgamwar and Venkatesh K. P. Rao
NDT 2023, 1(1), 22-34; https://doi.org/10.3390/ndt1010003 - 31 Jul 2023
Viewed by 1157
Abstract
In the past several decades, many destructive and non-destructive testing techniques have been developed to evaluate the characteristics of metal matrix composites (MMCs). This research aims to calculate the mechanical properties of the Al@Al2O3 composites by varying alumina nanoparticles (Al [...] Read more.
In the past several decades, many destructive and non-destructive testing techniques have been developed to evaluate the characteristics of metal matrix composites (MMCs). This research aims to calculate the mechanical properties of the Al@Al2O3 composites by varying alumina nanoparticles (Al2O3 NPs) content using a non-invasive, position sensing detector (PSD) unit-based optical method. The composite was prepared by a powder metallurgy technique, and its characterization was conducted using SEM and XRD to understand its surface morphology and microstructure. The natural frequency and Young’s modulus of the composite were estimated experimentally. Young’s modulus was calculated using this natural frequency. The proposed study shows that Young’s modulus of the composite increases with an increase in Al2O3 NPs content in the composition, irrespective of the testing method. Along with this, natural frequency also increases with the increase in the Al2O3 NPs content. Evaluated properties were compared with the numerical modeling using COMSOL Multiphysics. The experimental and numerical results are equivalent and within the margin of error. This study illustrates the development of an experimental approach for evaluating the mechanical properties of a composite material. This experimental approach can be used whenever sample dimension and space are constrained to evaluate the mechanical behavior of nanomaterials and nanocomposites. Full article
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19 pages, 8252 KiB  
Article
Defect Localization in Metal Plates Using Vibroacoustic Modulation
by Mohammad M. Bazrafkan and Marcus Rutner
NDT 2023, 1(1), 3-21; https://doi.org/10.3390/ndt1010002 - 16 Jul 2023
Cited by 1 | Viewed by 1109
Abstract
This paper reviews the state-of-the-art approaches in defect localization and specifies the remaining questions and challenges. Furthermore, this study presents a novel defect localization methodology using the nonlinear interaction of primary Lamb wave modes and vibroacoustic modulation (VAM), combined with damage imaging, to [...] Read more.
This paper reviews the state-of-the-art approaches in defect localization and specifies the remaining questions and challenges. Furthermore, this study presents a novel defect localization methodology using the nonlinear interaction of primary Lamb wave modes and vibroacoustic modulation (VAM), combined with damage imaging, to address the current shortcomings of defect localization. The study investigates this methodology experimentally with respect to defect interpretation, resolution, and applicability. Two Lamb waves with high and low frequencies, one being continuous and the other a tone burst, were excited using two different piezoelectric sensors. The amplitude of the measured signal at the first sideband frequency was evaluated with a short-time Fourier transform (STFT) and used for damage imaging via the delay and sum method. This study also includes a discussion on identifying the source of nonlinearity reflected in the first sideband. The experimental measurements prove that the localization of defect nonlinearity is possible with high accuracy, without the need for a baseline measurement, and with a minimum number of sensors. Sensitivity measurements with respect to the required length of the high-frequency tone burst and the sensor arrangement were also conducted. Full article
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2 pages, 433 KiB  
Editorial
Year I—Introducing NDT: A New Journal on Non-Destructive Testing Science, Technology and Their Applications
by Fabio Tosti
NDT 2023, 1(1), 1-2; https://doi.org/10.3390/ndt1010001 - 20 Mar 2023
Viewed by 1840
Abstract
It is with great pleasure that the journal NDT (ISSN 2813-477X) [...] Full article
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