Journal of Nondestructive Evaluation最新文献

The major objective when applying non-destructive testing (NDT) in civil engineering is the detection of defects such as honeycombs. Defects can impair the service life of structures and could lead in the worst case to fatal failures. All structures such as bridges, tunnels, locks etc. are unique objects with variation in geometry, dimensions, materials, environmental condition, load scenarios etc. Thus, the interpretation of NDT data is challenging and the validation of the NDT method, the training of inspectors and the reliability analysis of NDT rely on mock-ups with known defect situations mimicking the type of defect as realistic as possible. The considered defect sizes inside the mock-ups should cover the transition zone between detectable and non-detectable to properly evaluate the capability of the inspection system. However, knowledge about the limits of an inspection system is mostly non-existent. To overcome this limitation, this study applies realistic numerical simulations for ultrasonic testing in reinforced concrete performed with the elastodynamic finite integration technique (EFIT) to identify this transition zone. First, the study shows the development and the validation of a numerical representation of concrete considering the implementation of a qualitatively realistic noise level. Additionally, the accurate representation of the sources during ultrasonic testing is confirmed by an investigation of the radiation characteristic for dry point contact ultrasonic transducers. The simulation outcome enabled the design of a mock-up, which explores the detection limits for honeycombs during ultrasonic testing under different boundary conditions. A case study demonstrates the applicability of the design scheme based on numerical simulation. In the real specimen designed with the assistance of numerical simulations, (68mathrm{%}) of the implemented defects are detectable, proving the effectiveness of the design methodology.

In order to understand the delamination growth under mode II loading from the perspective of composite damage mechanisms, this study conducted in-depth research on the damage evolution of laminated plates using acoustic emission (AE) technology and signal analysis methods. Delamination mainly includes two stages: initiation and propagation, in which the initiation is the more important stage in the process of material delamination. Three damage modes of laminated materials during loading were identified by combining peak frequency statistics of AE signals with continuous wavelet transform (CWT). The initial time and stage of delamination can be determined by two methods. (1) The evolution process of damage mechanisms can be characterized by the fast fourier transform (FFT) of AE signals in several time periods. (2) The cumulative energy of three damage modes separated by variational mode decomposition (VMD) can be used to characterize the damage evolution process. The initial time determined by integrating several methods is much earlier than the occurrence time of the interlaminar fracture toughness value defined by ASTM standard. The strain energy release rate (SERR) determined at the initial time of delamination is taken as a design reference, which will be of guiding significance for ensuring the safety of laminates.

The paper deals with the non-destructive experimental testing of the reinforced concrete beams under progressive corrosion. A series of experiments using electrical potential, ultrasound and low-frequency vibrations techniques are reported. Electrical potential and natural frequencies were used to characterise and monitor the corrosion process at its initial state. The P-wave velocity measurements were proved to be effective in quantitative assessment of the level of corrosion as it progresses. The possibility of early detection of damage using a proposed damage index and diagnostic framework is promising for possible applications in the non-invasive diagnostics of reinforced concrete elements.

The extension of conventional computed tomography known as spectral computed tomography involves utilizing the variations in X-ray attenuation, driven by spectral and material dependencies. This technique enables the virtual decomposition of scanned objects, revealing their elemental constituents. The resultant images provide quantitative information, such as material concentration within the scanned volume. Enhancements in results are achievable through methods that capitalize on the strong correlation among decomposed images, effectively minimizing noise and artifacts. The Rigaku nano3DX submicron tomograph uses a dual-target source, which allows the generation of two distinct X-ray spectra through different target materials. This configuration holds promise for high-resolution applications in spectral tomography, particularly for low-Z materials, where it offers high contrast in the acquired images. The potential of this setup in the context of spectral computed tomography is explored in this contribution, delving into its applications for materials characterized by low atomic numbers.

In the present paper, magnetic Barkhausen noise (MBN) measurements have been carried out to evaluate the hardness and ferrite grain size of API X70 steel. All samples were austenitized at 900–1200 °C for 0.5 h followed by air-cooling identically to develop different ferrite grain size. The microstructure examinations were determined by Scanning Electron Microscope (SEM). The average ferrite grain size in each sample was estimated using ImageJ open-source software. Hardness measurements were performed using durometer device. Measurements of MBN were conducted using MikroMach (Micromagnetic Materials Characterization) system. The microstructure observation shows that the increase in the austenization temperature (AUT) causes an increase in the ferrite grain size as well as their change in shape from polygonal to acicular. The results of mechanical tests showed that the increase in the austenization temperature leads to an increase in the hardness of the X70 steel. Actually, MBN method can be used to evaluate the changes in hardness and ferrite grain size in ferromagnetic materials. The sample with the lowest austenitic temperature has the highest Barkhausen noise amplitude (BNA); in contrast, the sample which contains the highest austenitic temperature has the lowest BNA; furthermore, when the austenization temperatures increases, the signal of the coercive field Hc shifts to the higher values of magnetic field. Additionally, BNA decreases, and Hc increases whenever hardness and ferrite grain size increases. In this way, a good correlation was found between MBN parameters, ferrite grain size, and hardness values. The realized experimental setup can be used for online evaluate steel microstructures and quality control of ferromagnetic materials in some industrial applications.

Millimeter wave operates within a wavelength range of 1mm to 10mm and can penetrate through various non-metallic materials, such as the paperboard and plastic films commonly used in cigarette packaging boxes. In comparison to X-ray devices, millimeter wave imagers have the added advantage of not emitting ionizing radiation and having lower electromagnetic radiation output than the standard limit for mobile phone. Given these characteristics, we believe that utilizing millimeter wave imaging technology for detecting missing carton in packaged cigarette boxes could be a viable solution. The paper presents the fundamental imaging theory and showcases some images of cigarette boxes. The results demonstrate that our millimeter wave imager can produce clear images of packaged cigarette boxes with missing carton. We anticipate that this system has significant potential for application in machine vision for tobacco and other similar industries.

The new brake disc was evaluated for microstructure and hardness by the conventional destructive tests and non-destructive Barkhausen noise method (BNM). Ten non-destructive measurements were carried out in different areas of a brake disc, which were then cut out and made into metallographic test samples. Qualitative and quantitative analysis of graphite precipitates was performed to assess their volume in material matrix, anisotropy and size. Subsequently, graphs showing the relationships between selected stereological parameters of graphite precipitates and parameters determined from the RMS envelope of Barkhausen noise were elucidated. Similar relationships between hardness and parameters coming from non-destructive tests were carried out. Magnetic parameters that specified the size of a graphite precipitate was selected. In addition, repeatability studies using BNM were carried out in the areas of the material with the smallest and largest average size of graphite precipitates. A linear relationship between amplitude of BN and length of graphite flakes was found. The paper presents the possibilities of assessing the volume and size of graphite precipitates, as well as cast iron hardness using BNM.

Neutron imaging technology is a novel non-destructive testing technique that combines nuclear technology with digital imaging technology. Neutron radiation has significant advantages in detecting light elements and isotopes, making it complementary to X-ray imaging. This paper focuses on lithium-ion batteries and addresses the high level of speckle noise and the low brightness and clarity of neutron projection images. To improve the image quality of neutron projection images, this study proposes methods for noise suppression and image enhancement. Firstly, the median filtering algorithm is utilized to remove speckle noise in the image, and then the gradient operator is applied to sharpen the image and reduce the blurring effect caused by the filtering algorithm. In terms of image enhancement, the quality of the image is improved from two aspects: brightness adjustment and edge sharpening, aiming to enhance image details and improve image contrast. This study tests the algorithm using real neutron projection images and compares it with seven typical image processing algorithms, using peak signal-to-noise ratio, image feature similarity index, average gradient, and no-reference structural clarity as evaluation indicators for image quality. The experimental results show that the proposed method can effectively remove speckle noise in neutron projection images of lithium batteries, significantly improve image clarity and contrast. Compared with the comparative methods, the proposed method has the best edge-preserving ability, the highest signal-to-noise ratio, and clearer image details. In addition, testing with neutron projection images of three non-lithium battery samples demonstrates the good universality of the proposed method in enhancing neutron projection images.

Eddy current testing is one of the conventional non-destructive testing (NDT) technologies which is widely used in metal defects detection. Defect imaging by eddy current tomography (ECT) has advantages of visualization of defects, large detection area, fast detection speed and avoiding mechanical scanning imaging error. Sensitivity matrix is crucial in reconstructing defect images of metal materials by ECT. This article presents a sensitivity matrix of high conductivity initial estimate for ECT detecting metal materials. A 4(times )4 eddy current planar coil array and a 2 mm thickness titanium plate with defects were designed by both simulation and experiment. Based on the proposed sensitivity matrix, reliability of ECT forward problem linearization was analyzed and image reconstruction with two typical regularization methods ((L_1) and (L_2)) were investigated. Both simulation and experiment results show that ECT forward problem linearization was more accurate and reliable with the proposed sensitivity matrix especially at higher frequency. And (L_1) regularization method was verified to be more suitable to reconstruct image of small defects in metal materials. This work expands the original assumption of ECT forward problem linearization, which is of great significance to improve the metal defect image accuracy of ECT.

Acoustic emission (AE) technology is an effective method for monitoring the quality of carbon fiber reinforced plastic (CFRP) laser cutting. It is a challenge to decipher the formation mechanism because of the heterogeneity and anisotropy of CFRP. By analyzing the characteristics of AE signals and the images captured by the high-speed camera under different parameters, four types of AE signal sources were found: high-strength carbon fiber fractures, uniform resin ablation, photochemical fractures, and plasma plume impact. Kerf depth can be accurately identified by measuring the amplitude of the AE signal, and the experimental results verify that the error between the predicted and the experiment values is less than 0.1 mm. The laser defocusing amount, the width of the Heat-affected zone (HAZ), and the overall cutting time can be accurately determined by measuring the Root Mean Square (RMS) of the AE signal. The focus position can be adjusted before the laser cutting, decreasing the width of HAZ from 211.3 μm to 131.5 μm and the time of through-hole cutting from 245 s to 207 s.