Search Results (611)

Anthropogenic activities on soil layers contribute to reworking and eventual modification, which, in most cases, are detrimental to the soil. Going by the significance of soil to life in many ramifications, it is imperative that its consistent assessment enhances and guides management practices. This study focuses on delineating soil structure alterations using ground-penetrating radar (GPR), a geophysical survey method. The principle of operation and the simplicity of the technique have attracted the choice of the non-destructive testing (NDT) method with a view that it could circumvent the drawbacks that characterized the conventional methods hitherto used for such evaluation. Furthermore, the technique allows for the spatial investigation of the concealing sub-layer of the soil and, thus, informs its choice. A test site was selected on a plain farmland in Kraków, Poland, where some parts of the soil structure distortions were induced using tractor movement, which exerted normal stress from the soil surface layer. Subsequently, GPR measurements were acquired via pre-established profiles on the test site, and soil samples were taken for the laboratory evaluation of some of the soil’s physical properties. An analysis of the field data revealed that zones of distorted soil structures have lower attenuation effects on the GPR signal, with corresponding lower amplitude values compared with the unaltered soil structure zones. Evaluated physical properties such as bulk density and state variables like moisture water contents also show a declining trend from the unaltered soil structure zone to the altered zones. The results have revealed characteristic signatures of the zone of soil structure alterations from GPR scanning that can enhance its identification and characterization in the field and, thus, promote decision making toward the effective utilization and management of soil. Full article

Concrete production has significant environmental impacts due to extensive raw material use and high CO₂ emissions. Reusing structural concrete elements can potentially reduce these environmental impacts by reducing the demand for new production. However, reliable and practical documentation of concrete properties is needed for safe and scalable reuse. Although several non-destructive testing (NDT) methods show promise for in situ assessment of concrete properties, a clear gap remains in implementing them into a comprehensive approach for reuse documentation. This study investigates the potential of combining ultrasonic pulse velocity (UPV), rebound hammer (RH), and electrical resistivity (ER) methods for documenting concrete properties for reuse. Several parameters relevant to reuse scenarios, such as saturation level and aggregate type and size, were systematically evaluated to understand their impact on NDT documentation of concrete for reuse. NDT documentation of compressive strength and chloride migration coefficient was assessed on 120 cylindrical specimens. Fifteen concrete mixtures were used with three aggregate compositions and five water–cement ratios. The experimental results are discussed in the context of in situ documentation of structural elements in donor buildings to ensure the practical applicability of the findings. The findings show that these NDT methods can potentially document the properties of concrete reliably and practically, thereby addressing the lack of in situ documentation procedures needed to enable the safe and scalable reuse of structural elements. Full article

Fiber-reinforced polymer (FRP) pipes have emerged as a preferred alternative to conventional metallic piping systems in various industries, including chemical processing, marine, and oil and gas industries, owing to their superior corrosion resistance, high strength-to-weight ratio, and extended service life. However, ensuring the long-term reliability and structural integrity of FRP pipes presents significant challenges, primarily because of their anisotropic and heterogeneous nature, which complicates defect detection and characterization. Traditional non-destructive testing (NDT) methods, which are widely applied, often fail to address these complexities, necessitating the adoption of advanced digital techniques. This review systematically examines recent advancements in digital NDT approaches with a particular focus on their application to composite materials. Drawing from 140 peer-reviewed articles published between 2016 and 2024, this review highlights the role of numerical modeling, simulation, machine learning (ML), and deep learning (DL) in enhancing defect detection sensitivity, automating data interpretation, and supporting predictive maintenance strategies. Numerical techniques, such as the finite element method (FEM) and Monte Carlo simulations, have been shown to improve inspection reliability through virtual defect modeling and parameter optimization. Meanwhile, ML and DL algorithms demonstrate transformative capabilities in automating defect classification, segmentation, and severity assessment, significantly reducing the inspection time and human dependency. Despite these promising developments, this review identifies a critical gap in the field: the limited translation of advanced digital methods into field-deployable solutions specifically tailored for FRP piping systems. The unique structural complexities and operational demands of FRP pipes require dedicated research for the development of validated digital models, application-specific datasets, and industry-aligned evaluation protocols. This review provides strategic insights and future research directions aimed at bridging the gap and promoting the integration of digital NDT technologies into real-world FRP pipe inspection and lifecycle management frameworks. Full article

Aircraft engines are regularly inspected with borescopes to detect faults at an early stage and maintain airworthiness. A critical part of this inspection process is accurately measuring any detected damage to determine whether it exceeds allowable limits. Current state-of-the-art borescope measurement techniques—primarily stereo camera systems and pattern projection—face significant challenges when engines lack sufficient surface features or when illumination is inadequate for reliable stereo matching. MEMS-based 3D scanners address these issues by focusing laser light onto a small spot, reducing dependency on surface texture and improving illumination. However, miniaturized MEMS-based scanner borescopes that can pass through standard engine inspection ports are not yet available. This work examines the essential steps to downsize MEMS 3D scanners for direct integration into borescope inspections, thereby enhancing the accuracy and reliability of aircraft engine fault detection. Full article

The growing application of Fiber-Reinforced Polymer (FRP) composites in rehabilitating deteriorating concrete infrastructure underscores the need for reliable, cost-effective, and automated nondestructive testing (NDT) methods. This review provides a comprehensive analysis of existing and emerging NDT techniques used to assess externally bonded FRP (EB-FRP) systems, emphasizing their accuracy, limitations, and practicality. Various NDT methods, including Ground-Penetrating Radar (GPR), Phased Array Ultrasonic Testing (PAUT), Infrared Thermography (IRT), Acoustic Emission (AE), and Impact–Echo (IE), are critically evaluated in terms of their effectiveness in detecting debonding, voids, delaminations, and other defects. Recent technological advancements, particularly the integration of artificial intelligence (AI) and machine learning (ML) in NDT applications, have significantly improved defect characterization, automated inspections, and real-time data analysis. This review highlights AI-driven NDT approaches such as automated crack detection, hybrid NDT frameworks, and drone-assisted thermographic inspections, which enhance accuracy and efficiency in large-scale infrastructure assessments. Additionally, economic considerations and cost–performance trade-offs are analyzed, addressing the feasibility of different NDT methods in real-world FRP-strengthened structures. Finally, the review identifies key research gaps, including the need for standardization in FRP-NDT applications, AI-enhanced defect quantification, and hybrid inspection techniques. By consolidating state-of-the-art research and emerging innovations, this paper serves as a valuable resource for engineers, researchers, and practitioners involved in the assessment, monitoring, and maintenance of FRP-strengthened concrete structures. Full article

This paper presents a discrete Fourier transform (DFT)-based signal processing framework for eddy current non-destructive testing (NDT), aiming to enhance signal quality for precise defect characterization in critical nuclear components. By enforcing strict periodicity matching between sampling points and signal frequencies, the proposed approach mitigates DFT spectrum leakage, validated via phase linearity analysis with errors of ≤0.07° across the 20 Hz–1 MHz frequency range. A high-resolution 24-bit analog-to-digital converter (ADC) hardware architecture eliminates complex analog balancing circuits, reducing system-wide noise by overcoming the limitations of traditional 16-bit ADCs. A 6 × 6 mm application-specific integrated circuit (ASIC) for array sensors enables three-dimensional (3D) defect visualization, complemented by Gaussian filtering to suppress vibration-induced noise. Our experimental results demonstrate that the digital method yields smoother signal waveforms and superior 3D defect imaging for nuclear power plant tubes, enhancing result interpretability. Field tests confirm stable performance, showcasing clear 3D defect distributions and improved inspection performance compared to conventional techniques. By integrating DFT signal processing, hardware optimization, and array sensing, this study introduces a robust framework for precise defect localization and characterization in nuclear components, addressing key challenges in eddy current NDT through systematic signal integrity enhancement and hardware innovation. Full article

Destructive testing is a common method for obtaining tensile strength properties of welds. However, it is inconvenient to characterize the overall weld, and it cannot be applied to in-service structures. Non-destructive testing and evaluation (NDT&E) methods have the potential ability of overcoming these limitations. In this paper, an ultrasonic-based non-destructive evaluating method for weld tensile strength was proposed. Multiple sets of fully automatic welded X80 steel pipes were prepared. Acoustic signals from a total of 240 measurement points of the welds were collected, and ultrasonic characteristic parameters were subtracted through signal processing. Subsequently, tensile strength values were obtained through destructive testing. Using the ultrasonic and tensile test databases, a multivariate regression-based (MLR) non-destructive evaluation model was established to predict the tensile strength value. Based on this, in order to rapidly characterize the welds, a grading evaluation model was introduced. The grading evaluation result of the 240 measurement points indicates that the accuracy of the proposed method is 76.3%. In order to improve accuracy, a deep learning-based method could be used in the future. Full article

This paper focuses on a midstream pipeline to help us develop a better understanding of Pipeline Inspection Gauge (PIG) operation. A methodological combination of non-destructive testing (NDT), non-destructive evaluation (NDE), and risk-based inspection (RBI) was applied within an engineering system compatible with industry standards. In this sense, the implementation of the protocol and an assessment of the effectiveness of the proposed research model for solving problems that occur during a PIG’s working life, such as damage mechanisms and methods for its repair, are presented. The RBI methodology is derived using two mutually validating approaches to provide a result with low uncertainty. The result of this research confirms the expediency of the multi-perspective research approach and demonstrates the applicability of this methodology through a model study in the area of protocol creation—an essential aspect of ensuring the safety of pipeline inspections. Full article

The welding quality of industrial pipelines directly impacts structural safety. X-ray non-destructive testing (NDT), known for its non-invasive and efficient characteristics, is widely used for weld defect detection. However, challenges such as low contrast between defects and background, as well as large variations in defect scales, reduce the accuracy of existing object detection models. To address these, an optimized detection model based on You Only Look Once (YOLO) v5 is proposed. Firstly, the Efficient Multi-Scale Attention (EMA) attention mechanism is integrated into the first Cross Stage Partial (C3) module of the backbone to enhance the model’s receptive field and the initial feature extraction. Secondly, the Efficient Channel Attention (ECA) attention mechanism is embedded before the Spatial Pyramaid Pooling Fast (SPPF) layer to enhance the model’s ability to extract small targets and key features. Finally, the Complete Intersection over Union (CIoU) loss is replaced with Wise Intersection over Union (WIoU) to improve localization accuracy and multi-scale detection performance. The experimental results show that the optimized model achieves a precision of 94.1%, a recall of 89.2%, and an mAP@0.5 of 94.6%, representing improvements by 11.5%, 5.4%, and 6.9%, respectively, over the original YOLOv5. The optimized model also outperforms several mainstream object detection models in weld defect detection. In terms of mAP@0.5, the optimized YOLOv5 model shows improvements of 14.89%, 13.02%, 6.1%, 19.37%, 7.1%, 7.5%, and 10.7% compared with the Faster-RCNN, SSD, RT-DETR, YOLOv3, YOLOv8, YOLOv9, and YOLOv10 models, respectively. This optimized model significantly enhances X-ray weld defect detection accuracy, meeting industrial application requirements and offering another high-precision solution for weld defect detection. Full article

The integrity of multi-bolted flanges is crucial for ensuring safety and operational efficiency in industrial systems across sectors such as oil and gas, chemical processing, and water treatment. Traditional non-destructive testing (NDT) methods often require operational downtime and may lack sensitivity for early-stage defect detection. This review examines acoustic emission testing (AET), a real-time monitoring technique for detecting acoustic waves generated by material defects. An analysis of 145 studies demonstrated AET’s effectiveness in detecting early-stage defects across various materials and industrial applications. Recent advances in sensor technology and signal processing have significantly enhanced AET’s capabilities. However, challenges remain regarding environmental noise interference and the need for specialized expertise. The review identifies knowledge gaps and proposes future research directions, including planned laboratory experiments to characterize defect signals in multi-bolted flange systems under different operational conditions. The findings position AET as a transformative solution for industrial inspection and maintenance, offering enhanced safety and reliability for critical infrastructures. Full article

Industrial Computed Tomography (CT) is a widely used Non-Destructive Testing (NDT) technique for evaluating internal and external geometries with high accuracy. However, its integration into industrial workflows is often hindered by long scan times and high energy consumption, raising sustainability concerns. This study introduces a novel approach to improving CT efficiency by integrating real-time energy consumption monitoring into the scanning process. A power measurement device was used to correlate scan parameters with energy usage and image quality, enabling a data-driven approach to parameter optimization. Results show that higher voltages improve image quality up to 32%, when evaluated using Contrast-to-Noise Ratio (CNR) amongst other image quality metrics, while reducing overall energy consumption by up to 61%. The results presented support the optimization of CT scan parameters by providing quantitative guidelines to balance efficiency, image quality, and sustainability. Additionally, deviations in dimensional measurements obtained through CT scans were compared against reference data from a Coordinate Measuring Machine (CMM), with differences up to ±45 μm. The findings contribute to enhancing CT performance while minimizing environmental impact. Full article

This text provides a comprehensive overview of structural timber old buildings, from an in-depth analysis of construction processes to laboratory-based research aimed at establishing a pattern for estimating the density of wood in buildings. It is now widely recognised by society that historic buildings should be subject to conservation or rehabilitation. This article discusses the good technical knowledge that those involved in old buildings should have: the understanding of and respect for old construction techniques; rigorous inspections and diagnosis before a project; and the recognition of the properties of wooden structural elements, either visually or by means of non-destructive or semi-destructive testing methods (NDT/SDT). The final section of this article presents a laboratory study that correlates penetration resistance test results with wood density and verifies them in situ by direct analysis with wood core extraction. The aim of this study is to establish and verify a reliable pattern that allows the user to estimate the density of Scots pine in any structural member in service in an old building. The results obtained in the laboratory and of wood in service show that Equation (1) is a suitable pattern to obtain wood density through the wood penetration resistance test. Full article

In recent years, innovative Non-Destructive Testing (NDT) techniques, applicable for the assessment of existing civil structures, have become available for in situ analysis on Reinforced Concrete (RC) and masonry structures, but they are still not established for regular inspections, especially after seismic events. The damage assessment of RC buildings after seismic events is a very relevant issue in Italy, where most of the structures built in the last 50 years are RC structures. Furthermore, there is also a growing interest in being able to monitor structural health aspects by storing them on the building’s digital twin. For these reasons, it is necessary to develop an affordable and ready-to-use NDT procedure that provides more accurate indications on the real state of damage of reinforced concrete buildings after seismic events and to integrate these data into an interoperable digital twin for automated, optimized building performance monitoring, management, and preventive maintenance. To this end, a case study was conducted on a building in the Marche region in Italy, damaged by the 2016 earthquake. Non-destructive tests were performed and inserted into the LIS platform for the creation of a digital twin of the building. This platform seamlessly manages, visualizes, and analyzes the collected data and integrates various sensor nodes deployed throughout the building. The paper also presents a methodology to simplify the work of the test operator and make the entire process of knowledge of the building faster and more sustainable through a QR-code interface. Full article

Concrete structures require routine inspections. Within elastic wave-based non-destructive testing methods, the Rayleigh wave (R-wave)-based method shows great potential in defect characterisation with only one-side access required. This paper aims to investigate the effect of different locations and densities of voids on R-waves using a 2D finite element model. The numerical model was validated and calibrated with experimental results to increase the reliability and representativeness of the model developed. The difference between the R-wave velocity obtained from the numerical model and theory was within 5%, while the correlation between the R-wave waveform collected from the numerical and experimental data was 0.975. The developed numerical model was used to carry out a series of parametric studies investigating the relationship between different R-wave properties and void characteristics. The results revealed that the 5 kHz velocity index was the most sensitive for distributed void identification, with solid correlations up to 0.9879 reported. The correlations obtained from the data analysis suggest good feasibility of the demonstrated computational approach in evaluating the effect of defects in concrete on R-wave behaviour. This approach also offers useful insights into developing an alternative assessment methodology for internal damage localisation and characterisation utilising elastic wave measurements. Full article

The aviation industry currently faces several challenges in inspecting and diagnosing aircraft structures. Current aircraft inspection methods still need to be fully automated, making early detection and precise sizing of defects difficult. Researchers have expressed concerns about current aircraft inspections, citing safety, maintenance costs, and reliability issues. The next generation of aircraft inspection leverages semi-autonomous and fully autonomous systems integrating robotic technologies with advanced Non-Destructive Testing (NDT) methods. Active Thermography (AT) is an example of an NDT method widely used for non-invasive aircraft inspection to detect surface and near-surface defects, such as delamination, debonding, corrosion, impact damage, and cracks. It is suitable for both metallic and non-metallic materials and does not require a coupling agent or direct contact with the test piece, minimising contamination. Visual inspection using an RGB camera is another well-known non-contact NDT method capable of detecting surface defects. A newer option for NDT in aircraft maintenance is 3D scanning, which uses laser or LiDAR (Light Detection and Ranging) technologies. This method offers several advantages, including non-contact operation, high accuracy, and rapid data collection. It is effective across various materials and shapes, enabling the creation of detailed 3D models. An alternative approach to laser and LiDAR technologies is photogrammetry. Photogrammetry is cost-effective in comparison with laser and LiDAR technologies. It can acquire high-resolution texture and colour information, which is especially important in the field of maintenance inspection. In this proposed approach, an automated vision-based damage evaluation system will be developed capable of detecting and characterising defects in metallic and composite aircraft specimens by analysing 3D data acquired using an RGB camera and a IRT camera through photogrammetry. Such a combined approach is expected to improve defect detection accuracy, reduce aircraft downtime and operational costs, improve reliability and safety and minimise human error. Full article