Journal Description
NDT
NDT
is an international, peer-reviewed, open access journal on non-destructive testing published quarterly online by MDPI. The Faringdon Research Centre for Non-Destructive Testing and Remote Sensing (FCNDT&RS) is affiliated with NDT and its members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- Rapid Publication: first decisions in 16 days; acceptance to publication in 5.8 days (median values for MDPI journals in the second half of 2023).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Latest Articles
Geophysical Surveys to Highlight Buried Ancient Walls of Ugento (Lecce, Italy)
NDT 2024, 2(3), 204-213; https://doi.org/10.3390/ndt2030012 - 22 Jun 2024
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Geophysics is a fundamental tool to detect buried structures of archaeological interest through non-destructive techniques. The Messapian city walls in Ugento (Puglia, southern Italy) are of great archaeological importance, and some sections are still visible. In order to locate a stretch of the
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Geophysics is a fundamental tool to detect buried structures of archaeological interest through non-destructive techniques. The Messapian city walls in Ugento (Puglia, southern Italy) are of great archaeological importance, and some sections are still visible. In order to locate a stretch of the city walls, geophysical prospections were performed using the low-frequency electromagnetic method and ground-penetrating radar. The surveys were carried out in a peripheral area of Ugento, near a visible section of the city walls. The analysis and interpretation of the measured data revealed clear anomalies that could be ascribed to the city walls that aligned with an adjacent section of the visible walls. Archaeological excavation campaigns found a part of the walls and some important elements, as identified by the geophysical data interpretation.
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Open AccessArticle
Repeatability and Reproducibility of Pavement Density Profiling Systems
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Fabricio Leiva-Villacorta and Adriana Vargas-Nordcbeck
NDT 2024, 2(3), 190-203; https://doi.org/10.3390/ndt2030011 - 22 Jun 2024
Abstract
The work conducted in this study was designed to establish achievable testing tolerances for non-destructive pavement density measurements using Density Profiling Systems (DPSs). Nine and six sensors were used to determine the precision of repeatability and reproducibility in the laboratory and the field,
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The work conducted in this study was designed to establish achievable testing tolerances for non-destructive pavement density measurements using Density Profiling Systems (DPSs). Nine and six sensors were used to determine the precision of repeatability and reproducibility in the laboratory and the field, respectively. A minimum of six sensors (considered in this study as independent laboratories) were needed to comply with the minimum number of participants required in the current ASTM standard practice (ASTM E691). The methodology included the development of laboratory precision evaluation with a total of nine sensors and two different mixtures (9.5 mm fine-graded mix, 19.0 mm coarse-graded mix) compacted at four density levels (97%, 94%, 91%, and 88% of Gmm). For the field portion of this study, pavement sections built at the National Center for Asphalt Technology (NCAT) Test Track in 2021 served as experimental variables. These sections were built with fine-graded asphalt mixtures and open-graded mixes as wearing courses. Additionally, the pavement sections included three underlying materials: new asphalt (binder layer), milled asphalt surface, and granular base, with thicknesses ranging from 3.8 to 13.9 cm. Density profile testing was conducted at two locations: within the mat (center of the lane) and along the joint. Computed precision statements regarding dielectric values within and between laboratories were about double for field results compared to laboratory results. However, when converted to density, the statements were significantly below the reported statements for Bulk Specific Gravity and Vacuum Sealing in the laboratory and Nuclear and Electromagnetic density gauges in the field.
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(This article belongs to the Topic Nondestructive Testing and Evaluation)
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Open AccessArticle
Assessment of Special Rubberized Concrete Types Utilizing Portable Non-Destructive Tests
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Amr El-Nemr and Ibrahim G. Shaaban
NDT 2024, 2(3), 160-189; https://doi.org/10.3390/ndt2030010 - 21 Jun 2024
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Concrete is the second most common material demanded over the world. Recently, a trending issue is the vast tracking in constructing infrastructure to ensure traffic movement and life quality. Concrete types such as self and rolled compacted concrete offer magical solutions ensuring vast
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Concrete is the second most common material demanded over the world. Recently, a trending issue is the vast tracking in constructing infrastructure to ensure traffic movement and life quality. Concrete types such as self and rolled compacted concrete offer magical solutions ensuring vast infrastructure and life quality. However, these structures must be assessed using non-destructive testing methods to observe the difference between the concrete types. Several studies have used recycled waste, specifically the crumb rubber extracted from old tires, as a potential replacement for natural aggregate in concrete manufacturing. However, limited research has been devoted to nondestructive testing of produced concrete to further evaluate existing concrete elements containing crumb rubber. This study investigates the self and rolled compacted concrete in comparison with normal ones, in addition to using chopped rubber as recycled materials. This study examines the concrete manufactured destructively by evaluating its compressive, tensile, and flexural strength, in addition to impact resistance, and correlates those results with the non-destructive such as Schmit hammer and Ultrasonic Pulse (UPV) for extended utilization of the concrete produced and data publication. The results showed unique performance and a high potential for data contribution to the extensive utilization of self-compacted rubberized concrete and rolled compacted concrete.
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Open AccessArticle
Electrospray Ionization—Mass Spectrometry Characterization of Pine Bark Extracts
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Mireia Conde, Maria Mercè Solé, Sílvia Sorolla, Concepció Casas and Anna Bacardit
NDT 2024, 2(2), 143-159; https://doi.org/10.3390/ndt2020009 - 20 Jun 2024
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This study explored the potential application of polyphenols from Pinus halepensis bark in leather tanning. The primary objective was to characterize these polyphenols. The extraction and atomization processes proved efficient, reducing moisture content to 7.4%, increasing tannin content from 26.2% to 45.1%, and
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This study explored the potential application of polyphenols from Pinus halepensis bark in leather tanning. The primary objective was to characterize these polyphenols. The extraction and atomization processes proved efficient, reducing moisture content to 7.4%, increasing tannin content from 26.2% to 45.1%, and reducing insoluble substances by 77.5%. High-performance liquid chromatography (HPLC) coupled with mass spectrometry identified and quantified various polyphenolic compounds, including (+)-catechin, (+)-taxifolin, protocatechuic acid, and procyanidin B2. Notably, tannic catechin dimers were detected. Lignin was effectively removed through filtration. Concentrations of protocatechuic acid, (+)-catechin, (+)-taxifolin, (−)-epicatechin, and procyanidin B1 were significantly higher in the extract than in the powder, with the extract showing 1214.3 mg/kg of protocatechuic acid, 2098.0 mg/kg of (+)-catechin, 4017.0 mg/kg of (+)-taxifolin, 2163.0 mg/kg of (−)-epicatechin, and 917.0 mg/kg of procyanidin B1.
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Open AccessArticle
Deep Learning-Based Superpixel Texture Analysis for Crack Detection in Multi-Modal Infrastructure Images
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Sara Shahsavarani, Clemente Ibarra-Castanedo, Fernando Lopez and Xavier P. V. Maldague
NDT 2024, 2(2), 128-142; https://doi.org/10.3390/ndt2020008 - 14 Jun 2024
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Infrared and visible imaging play crucial roles in non-destructive testing, where accurate defect segmentation and detection are paramount. However, the scarcity of annotated training data or the limited number of data availability often poses a challenge. To address this, we propose an innovative
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Infrared and visible imaging play crucial roles in non-destructive testing, where accurate defect segmentation and detection are paramount. However, the scarcity of annotated training data or the limited number of data availability often poses a challenge. To address this, we propose an innovative framework tailored to the domain of infrared and visible imaging, integrating segmentation and detection tasks. The proposed approach eliminates the dependency on annotated defect data during training, enabling models to adapt to real-world scenarios with limited annotations. By utilizing super-pixel segmentation and texture analysis, the proposed method enhances the accuracy of defect detection. Concrete structures, globally subjected to aging and degradation, demand constant monitoring for structural health. Traditional manual crack detection methods are labor-intensive, necessitating automated systems. The proposed approach combines deep learning-based super-pixel segmentation with texture analysis, offering a solution for limited-defect-data situations. Utilizing convolutional neural networks (CNNs) for super-pixel segmentation and texture features for defect analysis, the proposed methodology improves the efficiency and accuracy of crack detection, especially in scenarios with limited labeled data or a limited number of data available. Evaluation on public benchmark datasets have validated the effectiveness of the proposed approach in detecting cracks in concrete structures.
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Open AccessArticle
Automated Weld Defect Detection in Industrial Ultrasonic B-Scan Images Using Deep Learning
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Amir-M. Naddaf-Sh, Vinay S. Baburao and Hassan Zargarzadeh
NDT 2024, 2(2), 108-127; https://doi.org/10.3390/ndt2020007 - 7 Jun 2024
Abstract
Automated ultrasonic testing (AUT) is a nondestructive testing (NDT) method widely employed in industries that hold substantial economic importance. To ensure accurate inspections of exclusive AUT data, expert operators invest considerable effort and time. While artificial intelligence (AI)-assisted tools, utilizing deep learning models
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Automated ultrasonic testing (AUT) is a nondestructive testing (NDT) method widely employed in industries that hold substantial economic importance. To ensure accurate inspections of exclusive AUT data, expert operators invest considerable effort and time. While artificial intelligence (AI)-assisted tools, utilizing deep learning models trained on extensive in-laboratory B-scan images, whether they are augmented or synthetically generated, have demonstrated promising performance for automated ultrasonic interpretation, ongoing efforts are needed to enhance their accuracy and applicability. This is possible through the evaluation of their performance with experimental ultrasonic data. In this study, we introduced a real-world ultrasonic B-scan image dataset generated from proprietary recorded AUT data during industrial automated girth weld inspection in oil and gas pipelines. The goal of inspection in our dataset was detecting a common type of defect called lack of fusion (LOF). We experimentally evaluated deep learning models for automatic weld defect detection using this dataset. Our assessment covers the baseline performance of state-of-the-art (SOTA) models, including transformer-based models (DETR and Deformable DETR) and YOLOv8. Their flaw detection performance in ultrasonic B-scan images has not been reported before. The results show that, without heavy augmentations or architecture customization, YOLOv8 outperforms the other models with an F1 score of 0.814 on our test set.
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(This article belongs to the Special Issue Recent Advances in Ultrasonic Nondestructive Evaluation)
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Open AccessArticle
Acoustic Emission Monitoring for Damage Assessment of a Magnetite Ultra-High-Performance Concrete (MUHPC) Block in a Bending Test
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Cyrus Bourbour
NDT 2024, 2(2), 87-107; https://doi.org/10.3390/ndt2020006 - 8 May 2024
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Ultra-high-performance concrete (UHPC) is widely used because of its exceptional properties, such as high compressive and flexural strength, low permeability, and resistance to abrasion and chemical attack. It is commonly employed for intricate constructions like skyscrapers, precast concrete components, and infrastructure. Nevertheless, the
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Ultra-high-performance concrete (UHPC) is widely used because of its exceptional properties, such as high compressive and flexural strength, low permeability, and resistance to abrasion and chemical attack. It is commonly employed for intricate constructions like skyscrapers, precast concrete components, and infrastructure. Nevertheless, the incorporation of appropriate fibers into UHPC is carried out in order to accomplish objectives such as augmenting strength, enhancing toughness, and regulating cracking. This study employed magnetite as an additive to a UHPC block in order to examine the mechanical characteristics of a newly cast UHPC block. Acoustic emission was employed to evaluate the damage to the UHPC block for tracking purposes. Acoustic emission is a non-invasive testing technique that does not cause harm to the specimen when it is exposed to a load. On the basis of this, many critical locations that indicated the propagation of cracks were analyzed, as well as various loading stages across the specimen. The b-value is a method that can evaluate the extent of damage by analyzing the amplitude distribution. Distinct paths of b-values were noted for each loading stage, indicating major damage scenarios based on their slopes.
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Open AccessArticle
Statistical Evaluation of the Accuracy of Consumer Drone Photogrammetry at a Romanesque Church in Eastern Bavaria (Germany)
by
Roland Linck, Andreas Stele and Christoph Schimmer
NDT 2024, 2(2), 76-86; https://doi.org/10.3390/ndt2020005 - 11 Apr 2024
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For several years, photogrammetric surveys are quite often applied for surveying cultural heritage. For a detailed and accurate result, it is indispensable that the calculated point cloud represents the original geometry of the building in high quality, with vertical and horizontal structures in
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For several years, photogrammetric surveys are quite often applied for surveying cultural heritage. For a detailed and accurate result, it is indispensable that the calculated point cloud represents the original geometry of the building in high quality, with vertical and horizontal structures in the same manner. Whereas many published papers in the field of digital heritage documentation are dealing with creating such models or using photogrammetric data for damage detection, only a few papers are investigating the crucial fact of accuracy and how it can be influenced by the used camera resolution. We want to present a case study, in which we compare the photogrammetric point cloud of a normal consumer drone with a high-end device. Beside the actual survey results showing the details of a Romanesque church, a statistical calculation of deviation is shown. It becomes evident that there is only a difference within some millimetres between the corresponding point clouds in most parts of the monument. Hence, it can be stated that, for most applications in heritage protection, affordable consumer unmanned aerial vehicles (UAVs) are sufficient. Only if faint details have to be resolved will a better resolution of the mounted camera be required.
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Open AccessReview
Review of Ground Penetrating Radar Applications for Bridge Infrastructures
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Paola Boldrin, Giacomo Fornasari and Enzo Rizzo
NDT 2024, 2(1), 53-75; https://doi.org/10.3390/ndt2010004 - 21 Mar 2024
Cited by 2
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Infrastructure bridges play a crucial role in fostering economic and social development. However, the adverse effects of natural hazard and weather degradation, coupled with escalating rates of traffic, pose a significant threat. The resultant strain on the structure can lead to undue stress,
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Infrastructure bridges play a crucial role in fostering economic and social development. However, the adverse effects of natural hazard and weather degradation, coupled with escalating rates of traffic, pose a significant threat. The resultant strain on the structure can lead to undue stress, elevating the risk of a critical asset failure. Hence, non-destructive testing (NDT) has become indispensable in the surveillance of bridge infrastructure. Its primary objectives include ensuring safety, optimizing structural integrity, minimizing repair costs, and extending the lifespan of bridges. NDT techniques can be applied to both existing and newly constructed bridge structures. However, it is crucial to recognize that each NDT method comes with its own set of advantages and limitations tailored to specific tasks. No single method can provide an effective and unequivocal diagnosis on its own. Among the various NDT methods, Ground Penetrating Radar (GPR) has emerged as one of the most widely employed techniques for monitoring bridges. In fact, recent technical regulations now mandate the use of GPR for bridge monitoring and characterization, underscoring its significance in ensuring the structural health and longevity of these critical infrastructures. Ground Penetrating Radar (GPR) stands out as one of the most highly recommended non-destructive methods, offering an efficient and timely assessment of the structural conditions of infrastructure. Recognizing the pivotal role of non-destructive testing (NDT) in this context, this paper aims to elucidate recent scientific endeavors related to the application of GPR in bridge engineering structures. The exploration will commence with a focus on studies conducted both at the model level within laboratory settings and on real cases. Subsequently, the discussion will extend to encompass the characterization and monitoring of the bridge’s main elements: slab, beam, and pillar. By delving into these scientific experiences, this paper intends to provide valuable insights into the efficacy and applicability of GPR in assessing and ensuring the structural integrity of bridges. This paper provides a concise survey of the existing literature on the application of Ground Penetrating Radar (GPR) in the assessment of bridges and viaducts constructed with masonry and reinforced concrete, taking into account papers of journal articles and proceedings available on open databases. Various approaches employed in both laboratory and field settings will be explored and juxtaposed. Additionally, this paper delves into discussions on novel processing and visualization approaches, shedding light on advancements in techniques for interpreting GPR data in the context of bridge and viaduct evaluations.
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Open AccessArticle
Acoustic Emission Analysis of Mode II Interlaminar Fracture Toughness of 3D Reinforced CFRP
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Thiago Luiz Lara Oliveira, Daniel Brighenti Bortoluzzi, Lorena Cristina Miranda Barbosa and Antônio Carlos Ancelotti, Jr.
NDT 2024, 2(1), 32-52; https://doi.org/10.3390/ndt2010003 - 12 Jan 2024
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The use of composites in industry is increasing due to their ability to replace traditional materials. Carbon fiber-reinforced polymers offer a favorable strength-to-weight ratio, making them advantageous in numerous applications. Delamination is a common failure mode for composite materials, making it a crucial
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The use of composites in industry is increasing due to their ability to replace traditional materials. Carbon fiber-reinforced polymers offer a favorable strength-to-weight ratio, making them advantageous in numerous applications. Delamination is a common failure mode for composite materials, making it a crucial factor in ensuring material safety during service life. While fiber orientation in composites is designed for specific directional reinforcement, out-of-plane loads are often neglected, posing a critical challenge. Implementing through-thickness reinforcement, such as tufting, can enhance out-of-plane resistance, enabling more accurate structural designs. Non-destructive testing methods, particularly acoustic emission, play a significant role in ensuring component safety by detecting early damage and flaws. This study focused on monitoring mode II interlaminar fracture toughness and end-notched flexure (ENF), using acoustic emissions to compare the performance of samples with different through-thickness reinforcements against that of nonreinforced samples. The research analyzed acoustic emission patterns during testing, revealing a strong correlation with failure stages and the resistance induced by reinforcements. This approach provided valuable insights into damage characterization, supported by fractography analysis, especially concerning the final stages of failure due to damage, and the effects of different thread reinforcements. Acoustic emission proved crucial for real-time monitoring, enabling informed decisions to be made regarding component repair and lifespan extension in composite materials.
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Open AccessArticle
Reporting the Bearing Capacity of Airfield Pavements Using PCR Index
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Angeliki Armeni and Andreas Loizos
NDT 2024, 2(1), 16-31; https://doi.org/10.3390/ndt2010002 - 6 Jan 2024
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Airfield pavements are important assets that have to secure the safe operation of an airport. On this basis, assessing and reporting the bearing capacity of an airfield runway pavement is a critical task. Recently, the Aircraft Classification Rating-Pavement Classification Rating (ACR-PCR) system has
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Airfield pavements are important assets that have to secure the safe operation of an airport. On this basis, assessing and reporting the bearing capacity of an airfield runway pavement is a critical task. Recently, the Aircraft Classification Rating-Pavement Classification Rating (ACR-PCR) system has been introduced, which uses the PCR index for expressing the bearing capacity of an airfield pavement. In order to accurately determine PCR, the mechanical characteristics and the thicknesses of the individual layers of a pavement are required. For this purpose, it is not seldom that in the absence of resources dedicated to detailed pavement evaluation procedures, assumptions for the material characteristics of the pavement considering typical materials may be made, while pavement thicknesses may be derived by pavement design records. The present paper highlights the importance of using Non-Destructive Testing (NDT) for accurately assessing the in-situ condition of a flexible runway pavement and determining the PCR index. In order to achieve the goal of the investigation, measurements were performed along the flexible pavement of an airport runway. In addition, the paper focuses on the impact of the variation of the thickness and of the mechanical characteristics of the asphalt concrete layers on the PCR index and on the interpretation of the results considering the acceptance of aircraft operations by airport authorities.
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Open AccessArticle
Simulation Study: Data-Driven Material Decomposition in Industrial X-ray Computed Tomography
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Moritz Weiss, Nick Brierley, Mirko von Schmid and Tobias Meisen
NDT 2024, 2(1), 1-15; https://doi.org/10.3390/ndt2010001 - 5 Jan 2024
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Material-resolving computed tomography is a powerful and well-proven tool for various clinical applications. For industrial scan setups and materials, several problems, such as K-edge absence and beam hardening, prevent the direct transfer of these methods. This work applies dual-energy computed tomography methods for
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Material-resolving computed tomography is a powerful and well-proven tool for various clinical applications. For industrial scan setups and materials, several problems, such as K-edge absence and beam hardening, prevent the direct transfer of these methods. This work applies dual-energy computed tomography methods for material decomposition to simulated phantoms composed of industry-relevant materials such as magnesium, aluminium and iron, as well as some commonly used alloys like Al–Si and Ti64. Challenges and limitations for multi-material decomposition are discussed in the context of X-ray absorption physics, which provides spectral information that can be ambiguous. A deep learning model, derived from a clinical use case and based on the popular U-Net, was utilised in this study. For various reasons outlined below, the training dataset was simulated, whereby phantom shapes and material properties were sampled arbitrarily. The detector signal is computed by a forward projector followed by Beer–Lambert law integration. Our trained model could predict two-material systems with different elements, achieving a relative error of approximately 1% through simulated data. For the discrimination of the element titanium and its alloy Ti64, which were also simulated, the relative error increased to 5% due to their similar X-ray absorption coefficients. To access authentic CT data, the model underwent testing using a 10c euro coin composed of an alloy known as Nordic gold. The model detected copper as the main constituent correctly, but the relative fraction, which should be 89%, was predicted to be ≈70%.
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Open AccessArticle
Ultrasonic Non-Contact Air-Coupled Technique for the Assessment of Composite Sandwich Plates Using Antisymmetric Lamb Waves
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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
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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
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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.
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Open AccessArticle
Wind Turbine Surface Defect Detection Method Based on YOLOv5s-L
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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
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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
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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.
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Open AccessArticle
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 - 9 Sep 2023
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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
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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%.
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Open AccessArticle
Development of Non-Destructive Dynamic Characterization Technique for MMCs: Predictions of Mechanical Properties for Al@Al2O3 Composites
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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
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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@Al O composites by varying alumina nanoparticles (Al
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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@Al O composites by varying alumina nanoparticles (Al O 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 Al O NPs content in the composition, irrespective of the testing method. Along with this, natural frequency also increases with the increase in the Al O 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.
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Open AccessArticle
Defect Localization in Metal Plates Using Vibroacoustic Modulation
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Mohammad M. Bazrafkan and Marcus Rutner
NDT 2023, 1(1), 3-21; https://doi.org/10.3390/ndt1010002 - 16 Jul 2023
Cited by 1
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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
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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.
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Open AccessEditorial
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
Abstract
It is with great pleasure that the journal NDT (ISSN 2813-477X) [...]
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