Search Results (91)

As a branch of nondestructive testing (NDT), Pulsed Eddy Current Testing (PECT) is characterized by its wide frequency spectrum and high penetration depth. After years of development, it has been widely applied to defect detection and material characterization of key components in industries such as petrochemicals, new energy, and aerospace. With the large-scale application of new energy sources like liquefied natural gas (LNG), methanol, and liquid hydrogen, the demand for NDT of non-ferromagnetic materials (e.g., austenitic stainless steel) has surged. However, challenges such as electromagnetic leakage caused by low magnetic permeability and the lift-off effect induced by protective layers impose stricter requirements on inspection technologies, driving the evolution of PECT towards adaptability in complex scenarios. This paper systematically reviews the latest advances in PECT technology, covering detection sensors, modeling methods, detection signal processing, and engineering applications. With a particular emphasis on research outcomes from the past decade, this paper also proposes potential directions for future development, aiming to provide a reference for innovative research and the industrial promotion of PECT technology. Full article

Non-destructive testing (NDT) methods have been widely used for damage examination and structural maintenance, e.g., detecting and repairing fatigue cracks. In-service inspections help increase fatigue reliability by providing new information for updating structural failure probability and making repair decisions. However, these benefits are often compromised by uncertainties associated with inspection methods. Sometimes, existing cracks may not be identified, and positive inspection indication may actually not exist. It is of great interest to consider the influence of inspection uncertainty in maintenance optimization, because the benefits and costs of maintenance are affected by inspection decisions (e.g., inspection times and methods), which are subjected to inspection uncertainty. The influence of inspection uncertainty on maintenance optimization has not been explicitly and adequately covered in the literature. In this paper, the problem has been investigated by probabilistic modelling of the qualities of inspection methods via probability of detection (PoD) functions. A new PoD function is proposed to characterize the inspection quality when inspection uncertainty is neglected. Optimum inspection decisions are derived by the objective of maximizing lifetime reliability index under two scenarios (considering and not considering inspection uncertainty). The effectiveness index of a planned inspection is defined based on the max reliability indexes under the two scenarios. It is shown that the max lifetime reliability index generally deceases when inspection uncertainty is considered. Inspection uncertainty may have little influence on the lifetime reliability index, depending on the planned inspection time. The effectiveness index of a planned inspection increases with the decrease in the mean detectable crack size. However, inspection uncertainty can result in significant increases in expected life cycle costs and maintenance costs. Full article

This study examines the mechanical performance of small-sized glued-laminated timber (GLT) produced from low-quality oak (Quercus spp.) lamellae and veneer arranged in 2–5 layers. After both non-destructive and bending tests, density, modulus of rupture, deflection and modulus of elasticity by static and dynamic methods were evaluated. Average densities ranged from 747 to 777 kg/m³. The two- and three-layer GLTs exhibited modulus of rupture values of 59.0 MPa and 63.7 MPa, while the four- and five-layer specimens reached 80.4 MPa and 80.0 MPa, respectively—up to 36% higher due to veneer reinforcement on the tension side. Static modulus of elasticity ranged between 11.2 and 12.1 GPa, and dynamic modulus of elasticity reached 13.0 GPa. The findings demonstrate that multi-layer configurations with veneer reinforcement effectively enhance bending performance and reliability, promoting the structural application potential of low-grade hardwood in accordance with EN 14080. Full article

As the volume of reinforced concrete structures continues to grow, it is important to determine the quality of concrete in the shortest time possible. Therefore, the development and validation of methods for non-destructive testing (NDT) of concrete structures are becoming increasingly important. However, some factors may affect the accuracy of the measurement results obtained as concrete is often exposed to a moist environment, e.g., in marine structures. Ignoring these factors may lead to an inaccurate interpretation of measurements. Therefore, in this research, the water saturation factor of concrete was investigated in response to various NDT methods. C25/30 and C40/50 MPa concrete were evaluated using ultrasonic pulse velocity and rebound hardness devices, and for the first time, a drilling resistance (DR) method was systematically adapted and validated for moisture-affected concrete testing. Unlike conventional approaches that only consider surface effects, the DR method introduced here provides in-depth profiling of concrete, revealing variations in resistance with depth and identifying zones influenced by internal moisture distribution. This study demonstrates that the DR method can complement traditional NDT techniques, providing a more reliable evaluation of moisture-induced variations in concrete properties. Moreover, with the novel DR method, changes in the mechanical response with depth have been quantified, offering new insight into internal moisture effects that are not accessible by conventional NDT methods. Full article

In this paper, an efficient algorithm for modeling the operation of a DDT (Deterministic Decision Tree) solving the problem of realizability of DRs (Decision Rules) is proposed and analyzed. For this problem, it is assumed that a DRS (Decision Rule System) is given; for an arbitrary tuple of feature values, it is required to recognize whether there is a DR realizable on this tuple, i.e., a DR for which the left-hand side is true on the tuple. It is shown that the weighted depth of the modeled DDT does not exceed the square of the minimum weighted depth of the NDT (Nondeterministic Decision Tree) solving the realizability problem. Full article

Stabilized soils are used as structural components in pavement construction and highway engineering. Due to their broad application, practical methods for predicting their strength are essential. The unconfined compressive strength (UCS) test is a fundamental technique for assessing mechanical properties. This study focuses on the development of a new method for predicting the strength of cement-stabilized soils. The analysis was based on three series of tests. The first series examined the effect of variable initial moisture content, ranging from 6% to 13%. The second series focused on the impact of cement content, ranging from 1% to 9%. The third series examined the effect of cement content on strength increase over a period of 1 to 56 days of curing. Based on the collected data, an empirical relationship was developed to predict strength using three key parameters: porosity (n), cement index (C_i), and curing time (T_C). Nomograms were created using this relationship, allowing strength to be easily predicted. Additionally, the study presents correlations between the proposed model and deformation parameters, as determined by both destructive testing (DT) and non-destructive testing (NDT), including the E₅₀ modulus, E_UPV, and G_UPV. The statistical validation of the determined empirical relationship showed a MAPE value of 15.928% and an RMSE value of 0.318 MPa. The results confirm the accuracy of the developed model and the derived correlations. Full article

Ensuring the structural integrity of mechanical components is a key challenge in industries such as automotive, aerospace, and energy. Conventional techniques for defect identification, including non-destructive testing (NDT) and the Finite Element Method (FEM), offer reliable solutions—yet FEM often requires intensive modeling work and high computational cost. To streamline the detection process, this study proposes a method based on orthogonal moment transforms applied to digital images. This fast and automated technique is particularly suited for integration into industrial vision systems. The approach consists in encoding the visual features of a component using continuous orthogonal moments (e.g., Zernike, Chebyshev, or Fourier), and analyzing the extracted descriptors to identify irregularities associated with surface cracks or structural flaws. Full article

This paper presents a relevant and timely study on the application of thermal loaded digital shearography for crack classification in glass fiber reinforced plastic (GFRP) structures, particularly air-cooled condenser (ACC) fan blades. A thermal loaded digital shearography system was applied to measure strain concentration caused by the cracks at different fatigue cycles. A thermomechanical model was introduced to estimate the heating temperature and the time to ensure heat can reach to the desired depth and that both shallow and deep cracks can be detected. In order to correlate the information of strain concentration in the shearograms to the different stages of cracks, fatigue testing with dynamic three-point bending was conducted. The fatigue tests demonstrated how the strain concentration evolved in the shearograms, while the crack developed from the early (no noticeable strain concentration), to the middle (strain concentration is forming), to the late stage (significant strain concentration is found). The relationships between the degrees of strain concentration in the shearograms and the different stages of cracks can be obtained from testing of the artificial cracks. Using the rules and experimental results obtained from artificial samples, digital shearography was applied to classify the crack stages in parts of ACC fan blades from industry. The combination of artificial crack testing, fatigue loading experiments, and validation with CT scans demonstrates a comprehensive approach and provides potential guidance for industry to determine criticality and maintenance criteria. Full article

This paper reviews recent advances in machine learning (ML) algorithms to improve the postprocessing and interpretation of thermographic data in non-destructive testing (NDT). While traditional NDT methods (e.g., visual inspection, ultrasonic testing) each have their own advantages and limitations, thermographic techniques (e.g., pulsed thermography, laser thermography) have become valuable complementary tools, particularly in inspecting advanced materials such as carbon fiber-reinforced polymers (CFRPs) and superalloys. These techniques generate large volumes of thermal data, which can be challenging to analyze efficiently and accurately. This review focuses on how ML can accelerate defect detection and automated classification in thermographic NDT. We summarize currently popular algorithms and analyze the limitations of existing workflows. Furthermore, this structured analysis provides an in-depth understanding of how artificial intelligence can assist in processing NDT data, with the potential to enable more accurate defect detection and characterization in industrial applications. Full article

The degree of anisotropy and heterogeneity in coarse-grained materials significantly affects ultrasonic propagation behavior and scattering. This paper proposes a vector coherent factor threshold total focusing imaging method (VCF-T-TFM) for austenitic stainless steel, based on material properties, through a combination of simulation and experimentation. Three types of austenitic stainless steel weld test blocks with varying degrees of heterogeneity were selected containing multiple side-drilled hole defects, each with a diameter of 2 mm. Full-matrix data were collected using a 32-element phased array probe with a center frequency of 5 MHz. The grain size and orientation of the material were quantitatively observed via electron backscatter diffraction (EBSD). By combining the instantaneous phase distribution of the TFM image, the coarse-grained material coherence compensation value (C_A) and probability threshold (P_T) were optimized for different heterogeneous regions, and the vector coherence imaging threshold (γ) was adjusted. The defect imaging results of homogeneous material (carbon steel) and three austenitic stainless steels with different levels of heterogeneity were compared, and the influence of coarse-grained, anisotropic heterogeneous structures on the imaging signal-to-noise ratio was analyzed. The results show that the VCF-T-TFM, which considers the influence of material properties on phase coherence, can suppress structural noise. Compared to compensation results that did not account for material properties, the signal-to-noise ratio was improved by 97.3%. Full article

This study aims to address the challenges posed by uneven energy amplitude and a low signal-to-noise ratio (SNR) in the total focus imaging of coarse-crystalline elastic anisotropic materials. A novel method for acoustic field correction vector-coherent total focus imaging, based on the materials’ properties, is proposed. To demonstrate the effectiveness of this method, a test specimen, an austenitic stainless steel nozzle weld, was employed. Seven side-drilled hole defects located at varying positions and depths, each with a diameter of 2 mm, were examined. An ultrasound simulation model was developed based on material backscatter diffraction results, and the scattering attenuation compensation factor was optimized. The acoustic field correction function was derived by combining acoustic field directivity with diffusion attenuation compensation. The phase coherence weighting coefficients were calculated, followed by image reconstruction. The results show that the proposed method significantly improves imaging amplitude uniformity and reduces the structural noise caused by the coarse crystal structure of austenitic stainless steel. Compared to conventional total focus imaging, the detection SNR of the seven defects increased by 2.34 dB to 10.95 dB. Additionally, the defect localization error was reduced from 0.1 mm to 0.05 mm, with a range of 0.70 mm to 0.88 mm. Full article

Non-destructive testing (NDT) and non-destructive evaluation (NDE) are essential tools for ensuring the structural integrity, safety, and reliability of critical systems across the aerospace, civil infrastructure, energy, and advanced manufacturing sectors. As engineered materials evolve into increasingly complex architectures such as fiber-reinforced polymers, fiber–metal laminates, sandwich composites, and functionally graded materials, traditional NDT techniques face growing limitations in sensitivity, adaptability, and diagnostic reliability. This comprehensive review presents a multi-dimensional classification of NDT/NDE methods, structured by physical principles, functional objectives, and application domains. Special attention is given to hybrid and multi-material systems, which exhibit anisotropic behavior, interfacial complexity, and heterogeneous defect mechanisms that challenge conventional inspection. Alongside established techniques like ultrasonic testing, radiography, infrared thermography, and acoustic emission, the review explores emerging modalities such as capacitive sensing, electromechanical impedance, and AI-enhanced platforms that are driving the future of intelligent diagnostics. By synthesizing insights from the recent literature, the paper evaluates comparative performance metrics (e.g., sensitivity, resolution, adaptability); highlights integration strategies for embedded monitoring and multimodal sensing systems; and addresses challenges related to environmental sensitivity, data interpretation, and standardization. The transformative role of NDE 4.0 in enabling automated, real-time, and predictive structural assessment is also discussed. This review serves as a valuable reference for researchers and practitioners developing next-generation NDT/NDE solutions for hybrid and high-performance structures. 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 review explores the applications of room temperature semiconductor detectors, with a focus on Cd(Zn)Te based detection systems, in non-destructive testing and evaluation (NDT&E). Cd(Zn)Te detectors, which operate efficiently at ambient temperatures, eliminate the need for cryogenic cooling systems and offer high energy and spatial resolution, making them ideal for a wide range of NDT&E applications. Key performance parameters such as energy resolution, spatial resolution, time resolution, detector efficiency, and form factor are discussed. The paper highlights the utilization of Cd(Zn)Te detectors in various imaging and spectroscopic applications, including nuclear threat detection and non-proliferation, archaeological NDT, and Unmanned Aerial Vehicle radiological surveying. Cd(Zn)Te detectors hold significant promise in NDT&E due to their high-resolution imaging, superior spectroscopic capabilities, versatility, and portability. Full article