Ndt & E International最新文献

In this work, active thermography has been evaluated for detecting impacts on polycarbonate parts produced by additive manufacturing with different fillers and under various impact energies. Polycarbonate is a material with very good impact resistance, very useful in sectors where security is critical (e.g., aeronautics, vehicle engineering, ballistics, defense, etc.). The impacts were specifically generated on the back face (non-visible) of the part, using a standardized test under controlled energy conditions. Specifically, flash thermography was used, and different processing techniques was applied. The most favorable results were obtained by principal component analysis (PCA). From a qualitative perspective, the proposed method allows to detect and evaluate the impact from the back side of the part (non-impacted side) taking into account the different material fillings. From a quantitative point of view, by using parametric and non-parametric tests, it can be shown that there are statistically significant differences between the image levels in the defect zone and the non-defect zone, and it is even possible to establish a correlation between the medians of the detected levels and the impact energy.

Rigid magnetic field sensors such as anisotropic magnetoresistive (AMR), giant magnetoresistive (GMR) and Hall sensors have been used for years and have become industry standard for electromagnetic non-destructive testing (NDT). Recent technological developments in the field of flexible electronics allow for the fabrication of reshapeable magnetic field sensors on flexible substrates via thin-film deposition or printing. The magnetic properties of these sensors have comparable characteristics to industry-standard rigid magnetic field sensors, with the added ability of adapting to the surface of complex components and scanning in contact with the sample surface. This improves defect detectability and magnetic signal strength by minimizing the scanning lift-off (LO) distance. In this article flexible AMR sensors mounted on a rotative mechanical holder were used to scan a semi-circular ferromagnetic sample with 3 reference defects via magnetic flux leakage (MFL) testing, thus demonstrating the applicability of this type of sensors for the scanning of curved samples. In order to benchmark the performance of these sensors in comparison to industry standard rigid magnetic field sensors, a ferromagnetic sample with 10 reference defects of different depths was scanned employing flexible AMR and rigid GMR sensors. Defects with depths ranging from $110\mu$m up to $2240\mu$m were detected with an signal-to-noise ratio (SNR) of 2.7 up to 27.9 (for flexible AMR sensors) and 6.2 up to 72.3 (for rigid GMR sensors), respectively. A 2D magnetometer mapping of the sample with a spatial scanning step of $10\times 50\mu$m${}^2$ (flexible AMR) and $16\times 100\mu$m${}^2$ (rigid GMR) was obtained. The results show that this type of sensor can be used for high-resolution and high-detail mapping of defects on the surface of planar and non-planar ferromagnetic samples since the scanning lift-off distance is equal to the substrate thickness of $20\mu$m for in-contact scanning. The SNR comparison between flexible and rigid sensors shows that the performance of the flexible AMR sensors employed is not very far behind the performance of the rigid GMR sensors used.

Phased array ultrasonic testing (PAUT) is an advanced technique used for non-destructive testing (NDT) to detect and assess the integrity of materials or structures. In composite materials with significant acoustic attenuation, electrical noise significantly impacts PAUT detection accuracy, highlighting a crucial issue. This paper presents a comprehensive analysis of electrical noise, explains the relationship between electrical noise and inspection parameters, and proposes recommendations to reduce it. A time-varying filter empirical mode decomposition (TVF-EMD) joint wavelet thresholding method is proposed for denoising electrical noise after time-corrected gain (TCG). The ultrasonic echo signal goes through TVF-EMD decomposition, resulting in intrinsic mode functions (IMFs). Energy entropy is utilized to identify the signal-dominant IMFs, and wavelet thresholding is applied to further reduce noise within these selected IMFs. The proposed method effectively removes noise and ensures signal integrity by validating simulated and experimental signals.

The sensing instrumentation and testing operations routinely implemented in-situ to monitor the condition of both paved (flexible, rigid) and unpaved roads are critically reviewed: image acquisition, appraisal of surface profile and skid resistance, measurement of stress, strain and deflection, execution of tomography tests, evaluation of environmental parameters as well as determination of traffic volume. Further, this state-of-the-art review sheds light on the financial aspects and cost spectra of the different diagnostic procedures. Finally, a systematic literature review highlights trends in recent research and documents that scientific studies have mainly focused on remote imaging, deflection and tomography measurements.

Ultrasonic inspection is an environmentally friendly and easily deployable nondestructive testing (NDT) method widely used for defect detection of critical components in the industry. Phased array ultrasonic testing (PAUT) is one of the most advanced ultrasonic inspection methods, which gives volume inspection with increased resolution and coverage, improving inspection efficiency. Because of the weld structure echoes and the abstract nature of ultrasound images, especially facing meters and feature-changing weld joints with different thicknesses and welding methods in shipbuilding, the analysis of the PAUT weld data still relies on experienced rater random inspections. Rating complex welded products process is lengthy, costly, and prone to introduce human error during the manual rating but challenges automatic detection. To automatically segment defects in PAUT data, this work shows a combination of PAUT data of ship weld and three-dimensional (3D) U-net architecture. Combining PAUT imaging principles with welding and scan processes, a PAUT volumetric image dataset, including different thicknesses and scan angles, is established. We pioneered the application of 3D U-net architecture to segment defects in PAUT volume data. We found that U-net architecture with two encoding stages will perform better in segmenting defects in PAUT data, and region-based loss mainly improves the accuracy. Furthermore, a lightweight U-net architecture containing skip-connection and residual blocks is proposed with precision and efficiency improvement. The validation results show that the proposed U-net architecture offers a feasible solution to the problem of segmenting defects from PAUT data with a Dice accuracy of 90.9 %. Segmentation results help to locate and measure defects. This method makes locating and sizing defects in PAUT weld data possible within a fraction of a second.

Lock-in thermography (LIT) is a type of active thermography capable of detecting and evaluating the subsurface defects in composite materials. The phase or amplitude difference between the defect and sound regions can quantitatively determine the size and depth of defects. One limitation of LIT is that the optimal identification of defects located at specific depths is dispersed within phase images acquired at varying excitation frequencies. If the depth of the defects within the specimen is unknown, it is difficult to determine the excitation frequencies to achieve optimal contrast for all defects and display them in a single image. To address this challenge, a multi-frequency fused method based on lock-in thermography is proposed to improve the quality of defect detection. Initially, the optimal thermal wave excitation frequencies and the number of detection times are determined based on the theoretical solution. Subsequently, phase images at various excitation frequencies are extracted and enhanced using a specified scheme. Finally, we develop an unsupervised encoder-decoder network that combines dense connections and residual modules to fuse these phase images into a single image containing defects at various depths. An experiment is conducted to detect carbon fiber reinforced polymer (CFRP) laminate containing defects with different depths and sizes. The results demonstrate that the proposed method can broaden the detection range of defect depths and improve the quality of the inspected images, providing superior performance compared to traditional sequential image processing methods.

Robotic inspection of complex geometry components using immersion ultrasonic techniques is relevant for many ultrasonic Non-Destructive Testing (NDT) applications in different industries. To image large component, ultrasonic probe is manipulated around the component immersed in water using a robotic guided system to create a tiled image of the entire component. Due to the mechanical vibrations of the high-speed robotic arm, the probe position coordinates provided by the robotic system are not precise enough to ensure an accurate reconstruction (stitching) of a composite image from all individual images. In this work, we propose a stitching method specifically designed to create a single 2D image of the surface of an inspected component from a stack of Total Focusing Method (TFM) images. This stitching method uses Iterative Closest Point (ICP) registration to estimate a 2D rigid transformation between two consecutive 2D images, by maximizing the overlap between the surface geometries extracted from each image. The capabilities of this imaging technique are illustrated by various simulated and experimental results carried out in a water tank. Significant improvements in surface image quality, leading to accurate surface reconstruction, are shown for vertical vibrations with displacements of more than two operating wavelengths and for rotational vibrations with deviation angles of less than 1°. The results also show that the resolving power of the ICP algorithm decreases for strong rotational vibrations.

Delaminations are flat subsurface defects parallel to the sample surface. Recently we have demonstrated that lock-in infrared thermography, with optical excitation, allows sizing the geometrical parameters (length, depth and thickness) of a semi-infinite delamination. Here, we analyse the ability of this technique to resolve several parallel and semi-infinite delaminations. First, we develop an analytical method (based on the thermal quadrupoles) together with a numerical formulation to calculate the surface temperature of a sample containing several semi-infinite parallel delaminations. We verify that both methods provide the same temperature values, indicating their consistency. Then, we study the ability of lock-in infrared thermography to resolve two close delaminations. In particular we focus on two main configurations: two non-overshadowed delaminations and two superimposed delaminations. Next, after analysing the inverse problem in terms of residual function minimization, we develop a dedicated parametric estimation procedure able to retrieve the geometry of the studied defects. Finally, we test this procedure with synthetic temperature amplitude and phase data to retrieve the geometrical parameters of both delaminations.

A new active thermography scheme is here introduced, referred as ”‘Multi-Frequency Thermography”’, which uses an optimized multi-tone signal for simultaneously implementing lock-in analysis on a discrete and arbitrary set of linearly spaced frequencies. Such a signal, which modulates the intensity of the heating source here being a LED system in the visible range, results from the non-trivial summation of a desired number of odd and even harmonics of a fundamental tone, each of them having a specific initial phase value but equal amplitude, so as to deliver the same energy amount for all the chosen frequencies. In this way, a discrete set of thermal waves having different diffusion lengths are simultaneously excited within the inspected sample to probe different depths into it. With respect to standard lock-in thermography, it is demonstrated that the proposed approach can extract amplitude and phase features for all the excited frequencies from a single measurement, which lasts as long as a lock-in implemented at the fundamental tone. Both quantitative and qualitative comparisons with standard lock-in thermography are here reported, showing an excellent agreement. Hence, this new active thermography scheme can provide several advantages in practical implementations of thermography nondestructive evaluation.

This study is based on the principles of acoustoelasticity, analyzing the variation in sound wave time-of-flight(TOF) under different conditions using the critical refracted longitudinal(L_CR) wave method. A simulation model was developed using the COMSOL finite element simulation software to mimic the propagation of L_CR wave in a stress-free plate. The model was then subjected to uniaxial loading, and the change in wave TOF was observed by varying the angle between the stress direction and the sound wave propagation direction under constant load. The results were compared with theoretical calculations, showing a high degree of agreement, validating the accuracy of the designed model. Subsequently, during the tensile testing, the influence of different uniaxial loads and angle variations on the TOF of L_CR wave was observed. Upon comparing the experiment data with theoretical calculations, a high degree of consistency in the trend of variation is observed, this demonstrates that the detection platform established in this study is feasible for the assessment of residual stresses in practice.