Nondestructive Testing Research Articles

Conservation Treatment in the Process of Strengthening the Stone Architecture of Kazimierz Dolny (Poland)

ABSTRACT A crucial task in modern rock engineering involves studying mechanical properties of rocks used as elements of stone objects, focusing on how susceptible they are to processes that lead to degradation. In Kazimierz Dolny, several factors contribute to severe damage. Their identification made it possible to look at the effects of their action on the rock, both external — during field observations, and internal — during laboratory tests. The laboratory experiments were carried out with the aim of determining the geomechanical strength characteristics of the siliceous carbonate rock. The influence of specific climate-related factors (thermal shock and exposure to SO2 in the presence of moisture) on the deterioration of the rock was assessed. These tests were conducted on samples that were either air-dried or treated with preservative agents. The activity and effectiveness of these agents were evaluated based on results obtained from non-destructive ultrasonic tests, the percentage of weight loss, and destructive strength tests. The discussion revolves around the implications of the results obtained from the laboratory experiments. It explores the significance of the identified climate-related factors in the deterioration of siliceous carbonate rock and effectiveness of proposed preventive solutions, considering the diverse outcomes observed in tests.

Automatic defect detection in infrared thermal images of ancient polyptychs based on numerical simulation and a new efficient channel attention mechanism aided Faster R-CNN model

In recent years, the preservation and conservation of ancient cultural heritage necessitate the advancement of sophisticated non-destructive testing methodologies to minimize potential damage to artworks. Therefore, this study aims to develop an advanced method for detecting defects in ancient polyptychs using infrared thermography. The test subjects are two polyptych samples replicating a 14th-century artwork by Pietro Lorenzetti (1280/85–1348) with varied pigments and artificially induced defects. To address these challenges, an automatic defect detection model is proposed, integrating numerical simulation and image processing within the Faster R-CNN architecture, utilizing VGG16 as the backbone network for feature extraction. Meanwhile, the model innovatively incorporates the efficient channel attention mechanism after the feature extraction stage, which significantly improves the feature characterization performance of the model in identifying small defects in ancient polyptychs. During training, numerical simulation is utilized to augment the infrared thermal image dataset, ensuring the accuracy of subsequent experimental sample testing. Empirical results demonstrate a substantial improvement in detection performance, compared with the original Faster R-CNN model, with the average precision at the intersection over union = 0.5 increasing to 87.3% and the average precision for small objects improving to 54.8%. These results highlight the practicality and effectiveness of the model, marking a significant progress in defect detection capability, providing a strong technical guarantee for the continuous conservation of cultural heritage, and offering directions for future studies.

Monitoring of damage evolution in carbon fiber reinforced polymer composites by electrical impedance tomography

Electrical impedance tomography (EIT) has been widely investigated as a nondestructive testing method for carbon fiber reinforced polymer (CFRP) composites. However, the performance of EIT method on the damage process monitoring of the composites is lack of investigation. Herein, quasi-static indentation tests were utilized to introduce damage on CFRP laminates. The damage evolution process was monitored by EIT, while the potential of distinguishing the elastic deformation stage from the plastic stage was analyzed with the aid of acoustic emission. It was found that the changes in conductivity first appeared in the non-central region. With the accumulation of damage, the conductivity changes gradually extended to the center region. The reconstructed damage images were in the crossover shape, which was consist with the micro-CT results that showed the fracture of fibers in ±45° direction. This work further promotes the application of EIT in damage process monitoring of CFRP components.

Research on FPC coils with limited turns in planar electromagnetic tomography

Electromagnetic tomography (EMT) is a non-destructive testing method that reconstructs electrical parameter distribution based on boundary electromagnetic measurement data along electromagnetic rotation projection. The coil is a critical component of the EMT system, used to excite and detect changing magnetic fields. The performance of excitation-detection with specific coils directly affects the quality of the reconstructed image. The traditional EMT coils are wound coils. The excitation-detection performance of the coils is enhanced by increasing the number of turns to obtain better imaging quality. A larger coil volume has better sensitivity, but it cannot meet the space constraints of many applications. To solve this problem, this paper proposes a method using extremely thin FPC coil arrays as EMT sensors. To verify the feasibility of FPC coil imaging with a limited number of turns, firstly, this article analyses the excitation-detection capabilities of FPC coil with 1 to 12 turns through a combination of simulation and experiment. Secondly, the impact of excitation-detection capability on the EMT sensitivity matrix was studied. Finally, a 4×4 8-Turns FPC coil sensor was designed for image reconstruction experiments. The experimental results show that FPC coils with limited turns can be used for image reconstruction and to solve the problem of planar nondestructive testing in a small space.

Circumferential multi-point corrosion status assessment of steel cables considering self-magnetic flux leakage superposition effect

With the advantages of convenient operation and efficient detection, the self-magnetic flux leakage (SMFL) has become an important technology for non-destructive testing of ferromagnetic materials. However, the multi-point corrosion status of steel cable structures is still difficult to precisely assess. In this study, the SMFL theoretical model for the circumferential distribution of steel cable corrosion was established, and the measurement experiment of circumferential multi-point corrosion status was carried out. The results show that the area of circumferential distribution region S, the accumulated magnetic field intensity A and ellipticity e are all positively and quadratically correlated with the corrosion ratio α and defect angle θ of steel cables. Moreover, the magnetic field superposition effect shows an exponential decay trend with the defect interval angle Δφ. The maximum deviation rate of A was less than 10 % under different multi-point corrosion distributions, verifying the principle of magnetic field superposition. Finally, the assessment method based on the effect was proposed, which could accurately and systematically diagnose the circumferential multi-point corrosion status in steel cables.

Mechanical Analysis through Non-Destructive Testing of Recycled Porous Friction Course Asphalt Mixture

This study assessed the mechanical performance of porous asphalt mixtures, specifically the porous friction course (PFC), incorporating 10% Reclaimed Asphalt Pavement (RAP) and rubberized asphalt. Three different methods were investigated to evaluate the stiffness of the mixtures: the resilience modulus (RM) test at a single temperature and loading frequency, the complex modulus |E*| test from compressive loading conducted at various temperatures and frequencies, and the impact resonance (IR) tests performed at three temperatures with five impacts applied to the mixture. The results demonstrated that the RAP-containing mixture exhibited a higher resilience modulus at all tested temperatures, indicating greater stiffness compared to the mixture without RAP. Additionally, the IR and |E*| tests revealed similar behavior between the two evaluated mixtures. These findings suggest that both quasi-static and vibrational tests are suitable for characterizing the stiffness of porous asphalt mixtures due to the similarity in the viscoelastic parameters of the two investigated mixtures. This study provides important insights into the practical and scientific application of recycled and modified materials in porous asphalt mixtures.

Construction of a stable YOLOv8 classification model for apple bruising detection based on physicochemical property analysis and structured-illumination reflectance imaging

Effective and accurate detection of bruises at all stages has always been a challenge in non-destructive grading of apples. In this study, the visible structured-illumination reflectance imaging (SIRI) combing with deep learning method was proposed to identify bruised ‘Fuji’ apples at four different time stages (0, 6, 12 and 24 h). The macroscopic/microscopic structures and physicochemical properties of bruised tissue were measured and analyzed to determine the relationship between bruising time and these properties, as well as how they affect the accuracy of bruising detection. Results indicated that classification accuracy increased with the decrease of water and total phenolic content of the bruised tissue, as well as with the increase of color browning and bruised area. The YOLOv8 model achieved the highest detection accuracy (99.5 %) and stability. This research enhances understanding of apple bruise optics and aids in developing advanced nondestructive testing techniques.

A zero-shot quantitative evaluation model for subsurface defects size based on ultrasonic nondestructive testing

Existing defect quantitative evaluation models requires collecting and labeling all types of defect data for training. However, such models have a poor ability for new defect, and collecting and labeling data is a costly task. A zero-shot evaluation model is proposed to solve the questions. First, a Wavelet Packet Transform-based method is developed to convert defect ultrasonic signals into time–frequency images. Second, we define defect semantics from length, width, and height to describe defects of different sizes. Third, the ResNet with embedded Brownian Distance Covariance matrix and multi-dimension parallel framework is designed to extract the image features. Then, an autoencoder is trained to embed the defect semantic into the feature space. Finally, the dimension of defect is evaluated by measuring the similarity between the features and the category centroids. Experimental results reveal that our model has better ability to evaluate the dimensions of new defect compared to others models.

Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review.

Non-destructive testing (NDT) techniques play a crucial role in industrial production, aerospace, healthcare, and the inspection of special equipment, serving as an indispensable part of assessing the safety condition of pressure equipment. Among these, the analysis of NDT data stands as a critical link in evaluating equipment safety. In recent years, object detection techniques have gradually been applied to the analysis of NDT data in pressure equipment inspection, yielding significant results. This paper comprehensively reviews the current applications and development trends of object detection algorithms in NDT technology for pressure-bearing equipment, focusing on algorithm selection, data augmentation, and intelligent defect recognition based on object detection algorithms. Additionally, it explores open research challenges of integrating GAN-based data augmentation and unsupervised learning to further enhance the intelligent application and performance of object detection technology in NDT for pressure-bearing equipment while discussing techniques and methods to improve the interpretability of deep learning models. Finally, by summarizing current research and offering insights for future directions, this paper aims to provide researchers and engineers with a comprehensive perspective to advance the application and development of object detection technology in NDT for pressure-bearing equipment.

A tunable spatial coherence imaging with ultrasonic array for defects in composites

ABSTRACT Ultrasonic phased array detection technology is a promising non-destructive testing (NDT) method that has been widely used for defect detection. Due to the high attenuation characteristics of ultrasonic wave propagation in carbon fibre reinforced polymer (CFRP) and the directivity of the array elements, the possibility of false or missed detection for defects that are far from the array elements or located very close together will increase. In addition, the total focusing method (TFM) employs only the defect information contained in the full matrix capture (FMC) dataset while ignoring the spatial information of the array signals, leading to image mixed with artefact and noise. An improved method called p-weighted-TFM (p-WTFM) is proposed. First, this method scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase unchanged. Second, channel summation with energy compensation and directional correction will be realised. Finally, the signal dimensionality is restored by p-th power. Experimental results show that the p-WTFM can use any rational p-value to flexibly adjust image quality. Specially, this method can accurately distinguish adjacent defects spaced 1 mm apart with p value of 2.5, and it can also detect two defects located 10 mm deep with p value of 3.0.

Adaptation of an Eddy Current Model for Characterizing Subsurface Defects in CFRP Plates Using FEM Analysis Based on Energy Functional

In this work, a known Eddy Current (EC) model is adapted to characterize subsurface defects in carbon fiber-reinforced polymer (CFRP) plates intended for the civil aerospace industry. The considered defects include delaminations, microcracks, porosity, fiber breakage, and the simultaneous presence of these defects. Each defect is modeled as an additive variation in the material’s electrical conductivity tensor, allowing for a detailed mathematical representation of the defect’s influence on the CFRP’s electromagnetic behavior. The additivity of the variations in the conductivity tensor is justified by the assumption that the defects are not visible to the naked eye, implying that the material does not require non-destructive testing. The adapted EC model admits a unique and stable solution by verifying that all analytical steps are satisfied. To reconstruct 2D maps of the magnetic flux density amplitude, a FEM formulation is adopted, based on the energy functional because it ensures a stable and consistent numerical formulation given its coercivity. Moreover, the numerical approach allows precise and reliable numerical solutions, enhancing the capability to detect and quantify defects. The numerical results show that the obtained 2D maps are entirely superimposable on those highlighting the distribution of mechanical stress states known in the literature, offering a clear advantage in terms of detection costs. This approach provides an effective and economical solution for the non-destructive inspection of CFRP, ensuring accurate and timely defect diagnosis for maintaining structural integrity.

NIR spectroscopy for quality assessment and shelf-life prediction of kiwifruit

In this study, a non-destructive quality testing method along with shelf-life prediction of Xu Xiang ready-to-eat kiwifruit were developed using near-infrared spectroscopy (NIR) techniques. Several traditional quality indicators (hardness, soluble solids content, and dry matter) were evaluated. Partial least squares regression (PLS) was used to predict the intrinsic quality attributes of the samples. Competitive adaptive reweighted sampling algorithm (CARS) and uninformative variable elimination (UVE) algorithm were used to select the characteristic wavelengths. Prediction models for hardness, soluble solids content and dry matter were developed. The results showed that the prediction ability of the models could be improved by screening the characteristic wavelengths of CARS and UVE. Among them, the CARS-SNV-PLS model based on soluble solids had the best prediction ability (RMSEP of 0.430 and Rp2 of 0.958). Then, an NIR-based residual shelf-life prediction model was obtained by linking the measured quality indicators to the residual shelf-life, which was well validated with an RMSEP of 1.64 and an Rp2 of 0.939. Therefore, this study demonstrated the potential of combining CARS, SNV, and PLS for the non-destructive testing of ready-to-eat kiwifruit to provide technical support and solution.

Round robin experiment to detect, size, and characterize flaws in the welds of existing hydraulic steel structures using phased array ultrasonic testing

Limited information exists on the ability of nondestructive testing techniques to detect, size, and characterize flaws in existing hydraulic steel structures (HSS). Round robin experiments were conducted using phased array ultrasonics to inspect welded steel specimens representing joints in existing HSS. Technicians detected 83% of the flaws scanned, but detection rates varied widely by flaw and technician. Uncertainty in flaw size estimates, represented by 90% confidence bounds on the ratio of estimated to actual length or height, ranged from 0.52 to 2.10 for length and 0.32 to 3.59 for height. Planar, volumetric and laminar flaws were accurately characterized 80% of the time.

Elimination of the methodological error in measuring linear parameters of electrical cables for intrinsically safe systems

The necessity of monitoring the linear electrical parameters of cables for intrinsically safe applications is described and it is indicated that the manufacturer or supplier of cables must ensure that the cable parameters comply with current standards. The problem of unproductive consumption of cable products during its control is considered. It is noted that standard measurement methods for such a linear parameter as inductance are correct when using cable samples, the length of which is much shorter than the construction lengths. An analytical model of a cable line as an electrical facility with distributed parameters is investigated. The reason for the introduction of a limit on the length of the cable is shown, caused by the transition from a complete to a simplified model traditionally used in some standards.A systematic method for measuring the linear parameters of cables is proposed, based on an unconventional – reverse – solution, which consists in switching from the measured secondary parameters to the calculation of primary parameters. In this case, the secondary parameters are measured in accordance with the well – known standardized idling – short circuit method. The proposed method is practically free from the limitation of the length of cable samples. This allows you to control all finished cable products without cutting off samples for measurements. The measurement error does not exceed the limit set by the standards equal to 1 %. The results obtained provide non-destructive testing during acceptance tests of cable products intended for intrinsically safe systems.

Experimental and Simulation Study on Failure of Thermoplastic Carbon Fiber Composite Laminates under Low-Velocity Impact.

Numerous studies have demonstrated that under low-velocity, low-energy impact conditions, although the surface damage to fiber-reinforced composite laminates may be minimal, significant internal damage can occur. Consequently, a progressive damage finite element model was specifically developed for thermoplastic carbon fiber-reinforced composite laminates subjected to low-speed impact loads, with the objective of analyzing the damage behavior of laminates under impacts of varying energy levels. The model utilizes a three-dimensional Hashin criterion for predicting intralayer damage initiation, with cohesive elements based on bilinear traction-separation law for predicting interlaminar delamination initiation, and incorporates a damage constitutive model based on equivalent displacement to characterize fiber damage evolution, along with the B-K criterion for interlaminar damage evolution. The impact response of laminates at energy levels of 5 J, 10 J, 15 J, 20 J, and 25 J was analyzed through numerical simulation, drop-hammer experiments, and XCT non-destructive testing. The results indicated that the simulation outcomes closely correspond with the experimental findings, with both the predicted peak error and absorbed energy error maintained within a 5% margin, and the trends of the mechanical response curves aligning closely with the experimental data. The damage patterns predicted by the numerical simulations were consistent with the results obtained from XCT scans. The study additionally revealed that the impact damage of the laminates primarily stems from interlaminar delamination and intralayer tensile failure. Initial damage typically presents as internal delamination; hence, enhancing interlaminar bonding performance can significantly augment the overall load-bearing capacity of the laminate.

Debonding of piezoelectric transducers for residue-free ultrasonic non-destructive testing

ABSTRACT Components made of fibre-reinforced polymers (FRP) are prone to different types of damages such as delamination or matrix cracks, which can be critical for a component’s functionality. In classical ultrasonic nondestructive testing (NDT), lamb waves (LW) are frequently used to detect imperfections due to their favourable propagation characteristics over long distances. The LW are often excited by piezoelectric transducers, which are either bonded onto the component’s surface using comparatively stiff adhesives so to ensure loss-free LW coupling into the component or laminated directly into the FRP. In both cases the a priori nonseparable connection between the transducer and the substrate may itself be considered a defect when the component is put into service. In addition, laminating the transducers directly into the matrix is accompanied by both additional production effort and corresponding effects on thermomechanical component properties. To provide a cost-effective solution for NDT applications, the study focused on the development of a residue-free bonding concept for piezoelectric transducers. To this end, a total of three application approaches involving 14 commercially available adhesives and one dilatant material were investigated in different rounds of experimental testing. During the scientific campaign, the authors finally identified an adhesive that guarantees both lossless ultrasonic coupling and residue-free bonding, paving the way for much more process control and reusage of tested components for future NDT processes.

Evaluation of 3D printed 316L stainless steel microstructure and mechanical property by laser ultrasonics

ABSTRACT In this paper, the laser ultrasonic non-destructive testing technology was used to detect the microstructure and mechanical properties of selective laser melting (SLM) 316 L stainless steel after post-treatment. The microstructure and mechanical properties of additively manufactured 316 L stainless steel were measured by Scanning electron microscopy (SEM), Electron backscatter diffraction (EBSD), tensile testing, etc. The laser ultrasonic longitudinal wave signal characteristic values were coupled with the microstructure and mechanical properties of SLM 316 L stainless steel. The results show that: The yield strength has a good correlation with wave speed and attenuation. With the increase of holding temperature and holding time, the grain size increases, the low angle grain boundary decreases, the yield strength gradually decreases from 409 MPa to 359 MPa, the wave velocity increases from 5579 m/s to 5700 m/s, and the frequency domain attenuation coefficient increases from 0.13 dB/mm to 0.16 dB/mm, the central frequency domain is about 10 MHz. The ultimate tensile strength is related to the frequency domain attenuation. The ultimate tensile strength decreases with the increase of the frequency domain attenuation coefficient. It can provide a reference for the evaluation of mechanical properties by laser ultrasonic testing.

Laser Non-Destructive Test to Find Aluminum Metal Physical Properties

Laser Non-Destructive Test to Find Aluminum Metal Physical Properties

Sensory Perception Systems and Machine Learning Methods for Pesticide Detection in Fruits

In this study, an electronic tongue (E-tongue) and electronic nose (E-nose) systems were applied to detect pesticide residues, specifically Preza, Daconil, Curzate, Bricol, Accros, Amistar, and Funlate, in fruits such as cape gooseberries, apples, plums, and strawberries. These advanced systems present several advantages over conventional methods (e.g., GC-MS and others), including faster analysis, lower costs, ease of use, and portability. Additionally, they enable non-destructive testing and real-time monitoring, making them ideal for routine screenings and on-site analyses where effective detection is crucial. The collected data underwent rigorous analysis through multivariate techniques, specifically principal component analysis (PCA) and linear discriminant analysis (LDA). The application of machine learning (ML) algorithms resulted in a good outcome, achieving high accuracies in identifying fruits contaminated with pesticides and accurately determining the concentrations of those pesticides. This level of precision underscores the robustness and reliability of the methodologies employed, highlighting their potential as alternative tools for pesticide residue detection in agricultural products.

Terahertz Spectroscopy in the Field of Food Safety: A Review

with the continuous improvement of people's living standards, food quality and safety problem has caused the wide attention of the whole society, the traditional food quality detection method has certain limitations, terahertz spectral technology (THZ) is a new spectral detection technology, its strong perspective, efficient spectral resolution ability, special fingerprint and nondestructive, in the field of food quality and safety detection has important application value. Due to the high efficiency of food quality and the need for accurate nondestructive testing, automated nondestructive testing for food quality and safety has aroused great interest from the food sector. Faster, accurate, reliable and simplified techniques are needed to classify good quality. With their unique low-energy, penetrating, rapid and non-destructive techniques are widely used as a non-destructive and cost-effective method in the food sector. This paper summarizes the principles and instruments of terahertz spectrum, and introduces the research progress of terahertz spectral detection in food, analyzes the problems in the field of food quality and safety detection, and discusses the future development trend of terahertz spectral technology.