Ndt & E International最新文献

In this study, we present an extension of the virtual wave concept to enable photothermal reconstruction from temporal non-uniform pulsed thermography data. Therefore, we introduce a generalized discrete transformation kernel, which allows to account for arbitrary temporal sampling strategies. First, we show the evidence of the proposed strategy for analytical temperature signals. Moreover, we demonstrate the advantages of the strategy for simulated temperature signals, obtained from an orthotropic sample with defect interfaces at various depth positions. For experimental verification, we apply pulsed thermography in the pulse-echo configuration for a carbon fiber-reinforced polymer sample with different embedded defects. It can be shown that efficient time sampling in the virtual wave concept allows a significant reduction in the number of data points compared to uniform sampling, without compromising the quality of the reconstruction results.

In this study, we proposed an electromagnetic induction testing method for measuring the electrical properties of carbon fiber reinforced thermoplastics (CFRTPs) along the through-thickness direction. The effectiveness of the transmission method, wherein the coil is placed opposite to the object to be measured, was demonstrated through finite element analysis and experimental measurements. The simulation results indicated that the output voltage of an interlaminar non-electrically conductive specimen exceeded that of an interlaminar conductive specimen due to the electromagnetic shielding effect. In the experiments, the impedance along the through-thickness direction depended on the lamination configuration and the presence of the PA-6 layer. Our findings indicate that the proposed method can be used to measure the changes in the electrical properties of CFRTP along the through-thickness direction.

Currently, ultrasonic tomography is widely used for quantifying the status of damage/flaw in various materials including metal, concrete, and composite. It is capable of visualizing the internal damage or flaws by reconstructing the velocity of ultrasound. For most cases, the conventional ultrasonic tomography is adapted for slice-based investigations. Though 3D image can be generated by slice-based method, the involvement of multi-scan interpolation caused high computational cost and unexpected errors. Moreover, for 3D imaging, two essential factors are dominant: (i) reconstructing the velocity; and (ii) scheme of forming up the 3D image. To this end, this study proposed to develop a novel volumetric ultrasound imaging strategy with high accuracy. To obtain more accurate Time-of-Flight (TOF) for ultrasonic velocity, an improved method based on cumulative kurtosis is proposed. With the proposed method, the adverse influence of internal complexity within samples on ultrasound was reduced. The proposed novel volumetric ultrasound imaging strategy was verified numerically and experimentally. Finally, the performance of the proposed method has been evaluated by the comparison of three-dimensional imaging results with different inclusion. Additionally, the parametric study was conducted using path average velocity, voxel velocity, and image accuracy. The results show a positive correlation between the number of voxels and imaging accuracy. However, as the number of voxels increases, the errors introduced by the Simultaneous Algebraic Reconstruction Technique (SART) increase. The influential factors on the imaging accuracy were discussed, such as inclusion eccentricity, the relationship among the reduced volume imaging quantity, and accuracy in voxel inversion result. For further application, the recommendations were also provided.

Ultrasonic reflection coefficient is the key to contact state evaluation of mechanical devices. Edge blurring can lead to contact state (such as stress concentrations) measurement errors. This reduces the reliability of performance evaluations and introduces potential security risks. In this study, an edge blurring suppression method based on matching pursuit algorithm was proposed. Firstly, the interference signal prediction model is built based on the Nakagami model. Then, a blurred signal separation algorithm based on matching pursuit is proposed to obtain the effective signal. Finally, the reflection coefficient with and without edge blurring effect were obtained. The simulation results show that the maximum relative error of the reflection coefficient is reduced from 219 % to 15 %. The effectiveness of the proposed method is also verified by experiments. The experimental results show that the relative error of the reflection coefficient after edge blurring suppression is reduced from 64 % to 16 %. This indicates that the proposed method can effectively suppress edge blurring, which provides an effective method for edge blurring suppression in various application fields of ultrasonic measurement and improve the reliability of product quality evaluation.

Lightning strikes pose a significant challenge for aircraft and wind turbine blades with Carbon Fiber Reinforced Polymer (CFRP) structures, requiring reliable damage detection techniques. Non-destructive evaluation (NDE) methods, including X-ray and Ultrasonic Testing, are effective in identifying material damage in aircraft. However, X-ray requires access to both sides of the structure, and UT requires a coupling medium between the transducer and the structure, as well as a relatively smooth surface, making both methods less feasible for routine aircraft maintenance. Other NDE techniques, such as eddy current testing and infrared thermography, can detect damage on the side struck by lightning but lack the precision needed for a comprehensive assessment. To address these challenges, this paper introduces a two-stage Fusion-Translation network (FTnet), which integrates NDE 4.0 innovations, including data fusion and advanced imaging algorithms, to optimize the NDE process. By integrating infrared and eddy current data, FTnet characterizes lightning-induced damage with enhanced depth and contour detail, demonstrating superior performance over existing methods in both qualitative and quantitative evaluations. The implementation of FTnet marks an advancement in NDE 4.0, potentially enhancing aircraft safety and streamline maintenance protocols by providing a more reliable and comprehensive assessment of lightning strike damage.

Pearlitic steels are important engineering materials in various high-strength applications. Their mechanical properties are influenced by microstructure control using chemical composition and/or thermomechanical processing. In the current study, a novel, non-destructive technique is presented for the characterisation of key microstructure parameters that are essential for strength, both at room temperature and during dynamic heat treatment. The pearlite interlamellar spacing in a 0.81 wt% C steel has been accurately measured at room temperature using an electromagnetic (EM) sensor. Furthermore, the spheroidisation process in 100Cr6 pearlitic steel has been monitored at elevated temperatures. A strong linear relationship between the EM sensor signal and the pearlite interlamellar spacing is demonstrated, indicated by an R² value of 0.91. Additionally, the capability of this method to track the spheroidisation process in real-time during constant heat treatment offers potential avenues for process optimisation in pearlitic steels.

This study explores the relationship between surface defect imaging in deep-water concrete dams and the wavelength of the light source, aiming to improve concrete defect image quality by varying the wavelength. The underwater optical imaging model of concrete dam surfaces was developed by applying the principle of object reflection and the underwater optical propagation model. This model reflects the effect of different light wavelengths on underwater concrete defect imaging. Through a self-designed underwater optical darkroom test platform, defect image acquisition tests were conducted under various color light conditions. The results reveal the significant influence of light source wavelength on images captured in both air and water. Furthermore, under the same initial illuminance, blue light significantly enhanced the average gray value, sharpness, contrast, and the number of feature points in underwater defect images, exhibiting increments of 2.97 times, 0.48 times, 2.70 times, and 2.95 times, respectively, compared to white light. These findings can serve as a reference for the selection of color-light for the non-destructive testing of surface defects in actual underwater concrete dams.

Studying and understanding adhesion characteristics between a coating and its substrate is important for improving the reliability of a thin film’s adhesion. To the best of the authors’ knowledge, this work studies for the first time a specific electro-adhesion process using Laser-Ultrasonics. An electric field source is applied to a convenient sample composed of a polyvinyl chloride (PVC) layer on an aluminum (Al) substrate. The aim is to investigate the impact of different electro-adhesion levels on the propagation of surface acoustic waves (SAW), which are generated by a pulsed laser and detected using an interferometer. This non-destructive and non-contact experimental setup allows us to determine the surface modes dispersion curves for each adhesion level. A theoretical model is developed to numerically solve the dispersion relation in order to analyze the influence of the interface quality on the dispersion curves. These ones have also been obtained by the finite element method (FEM) allowing us to predict the shape of the experimental signals. This research paves the way for future studies of specific adhesion phenomena across different materials.

Ultrasonic nondestructive techniques can be useful tools in the microstructural classification of metallic alloys. Among the most common techniques for characterizing materials, backscattered signal analysis stands out because it does not require a back surface echo. This study classifies five ASTM A36 steel samples with varying grain sizes using ultrasonic waves. For each sample, ultrasound signals were obtained using two ultrasonic array probes with center frequencies of 5 and 10 MHz. An extensive feature engineering process was conducted using the tfresh package in Python, which extracts a wide range of features from time series data, transforming raw ultrasound signals into a structured format. Seven machine learning models were evaluated based on accuracy, precision, recall, and F1 score, with performances ranging from 70 to 100%. The XGBoost model exhibited the best performance with 10 MHz probe signals, achieving 100% accuracy. An additional validation test was conducted to evaluate the models’ generalization capability, considering inter-specimen variabilities. Despite a slight reduction in prediction metrics, the XGBoost model maintained good performance, with accuracy between 89% and 100% across all frequencies. Such findings demonstrate that backscattered grain noise can effectively identify grain sizes provided that an adequate machine learning model is used.

In this work we explore the capabilities of Talbot-Lau grating interferometry (TLGI) radiography for the inspection of porosity in structural specimens of cyanate ester carbon fiber reinforced polymer. The influence of system resolution and varying specimen thicknesses on mean values and standard deviations (STDV) in all three image modalities acquired by TLGI are addressed. Results show that mean absorption contrast (AC) values are highly affected by specimen thickness and strong negative correlation (r ≤ −0.8) is found only after correction via preliminary thickness measurements. Although dark-field contrast (DFC) is affected by changes in specimen thickness as well, the signal can be corrected by normalization with the inherently available AC. Consequently, strong positive correlation with porosity was found both in high- and low-resolution imaging (r = 0.83 and 0.71 respectively). Without the need for high image resolution or thickness measurements, the normalized DFC is a promising option for large field of view inspections. Investigations of STDV revealed strong positive correlations between porosity and AC STDV as well as differential phase contrast (DPC) STDV (r = 0.95 and 0.92 respectively) but high image resolution is required. Furthermore, results suggest increased robustness against variations in specimen thickness of AC and DPC STDV analyses.