Russian Journal of Nondestructive Testing最新文献

The method of phase-sensitive laser thermography has high sensitivity and allows for monitoring the uniformity and thickness of coatings made of various materials. The use of robotic manipulators as scanning devices enables thorough automated inspection of surfaces of complex-shaped test objects. The article provides information on a prototype of a robotic complex for laser phase-sensitive thermography based on a five-axis robotic manipulator, a laser with a power of up to 8 W and a wavelength of 450 nm, as well as a COX CG640 thermal imager. Methods for processing experimental data to determine the thickness of coatings made of low thermal conductivity materials are proposed. To test the approach, calibration blocks made of aluminum oxide with a polypropylene coating in the range of 40 to 500 μm were manufactured. It has been found that the nonuniformity of the coating is best determined by the distribution of the phase of temperature oscillations with a frequency of 0.1–1 Hz.

Surface treatment technology has widened its horizon over various applications; from metal surfaces to modern high-tech polyurethanes Metallic hardware of satellite launch vehicles is applied with single and multilayer thermal barriers and other special metallic coatings to meet harsh environments and unflinching functional requirements. Tactile nondestructive evaluation and metrology methods are generally used to assess the thickness of these coatings. However, these cumulative methods cannot be relied upon for the individual layer thickness of multilayer coated components. The X-ray fluorescence method has emerged as a tool for the qualitative and quantitative determination of the layer thicknesses irrespective of single or multilayer coating. In addition to the Fundamental Parameter mode with and without the calibration standard, this study experiments with a new empirical mode with two calibration standards. It also investigates the consistency of  X-ray fluorescence measurements and the effects of infinite thickness and impurities on the coating thickness. As the X-ray fluorescence assessment of the underneath coatings shows large deviations, a simulation study is discussed to determine the correction factor to be applied at the specified thickness ranges. This study highlights the comparative advantages of the X-ray fluorescence method over the other conventional methods. This study also proves that the empirical mode is a promising X-ray fluorescence method for a better assessment of intermediate and undercoat thickness on multilayer coated metallic substrate in a single exposure.

The possibility of detecting specific structural defects in dissimilar welded joints—carbide and decarburized ferrite interlayers—by the acoustic emission (AE) method is investigated. These interlayers are formed in dissimilar welded joints of austenitic and pearlitic steels during welding and subsequent operation.

Deterioration characteristics analysis and the estimation of the deterioration grade of textile relics are the premise of accurate restoration and protection. Therefore, in order to identify the deterioration characteristics of textile relics and develop a micro-non-destructive method for estimating the deterioration grade of textile relics, In this study, scanning electron microscopy (SEM), Fourier infrared spectroscopy (FTIR) and X-ray diffraction (XRD), which require very little sample, were used to systematically investigate the degradation characteristics of textiles under different hydrolysis conditions, and based on this, a method suitable for estimating the degradation grade of precious textile relics was proposed. Results illustrated that regardless of textiles’ type, the more obvious the decline in appearance and mechanical properties, the more obvious the corresponding changes in infrared spectrum and X-ray diffraction, indicating that the changes at the molecular level in the molecular structure and crystallinity correlate well with the changes in the macroscopic properties such as appearance morphology and mechanical properties. Balancing the convenience of operation, the preciousness of textile relics and the quantification of results, the ratio of the strongest diffraction peak in X-ray diffraction detection as an evaluation index to estimate the degree of deterioration of textile relics was most reasonable and had potential for widespread use in predicting the deterioration of textile relics within collections. The study was not only useful to understand the degradation mechanisms that textiles undergo under moist burial environments, but also valuable to support the textile conservation tasks currently being performed in museums to preserve our heritage.

Steels are susceptible to changes in their properties due to thermal effects; characterizing these changes in real time is one of the most pressing needs in the industry. The industrial ultrasound method is presented as a nondestructive technological alternative for mechanical characterization through direct correlation with acoustic properties. Therefore, the objective of the research was to correlate acoustic properties with hardness measurements in a mechanical construction steel induced to small microstructural changes by heat treatments. For this purpose, nine experimental tests were planned through the factorial interaction of the heating temperature in the austenitic region of 870, 920 and 970°C, and the cooling medium, inside the furnace, still air and oil. Each sample was characterized by Vickers hardness tests, optical metallography and ultrasound using the pulse-echo technique with longitudinal waves. The results and statistical tests showed significant changes in hardness and acoustic attenuation coefficient due to the effect of the microstructural change produced in the samples according to the imposed thermal cycle. The experimental data, arranged in a contour plot, show that hardness exhibits a negative correlation with respect to the velocity and attenuation coefficient; both acoustic parameters show a tendency to decrease and hardness to increase as the martensitic structures in the steel increase. The correlation obtained is presented as an alternative to non-destructive testing aimed at mechanical characterization using ultrasonic acoustic measurements.

Hot rolled steel strips play an important role in the fields of construction, automobile manufacturing, energy, shipbuilding and petrochemicals, etc. Their high strength, corrosion resistance and plasticity make them an indispensable material in industrial manufacturing. Surface defect detection is an indispensable process in hot rolling production line, which is of great significance to improve the quality of hot rolled steel strip. The current detection accuracy of small target defects on the surface of hot rolled steel strips is low and cannot meet the real-time detection needs of enterprises. To solve this problem, we propose a steel strip surface defect detection method based on YOLOv8, named TBD-YOLO. First, the downsampling mechanism from YOLOv7 (V7downsample) is referenced to replace the downsampling modules in the backbone and neck networks to enhance detection accuracy. Second, a modified bidirectional feature pyramid network (mod_BiFPN) is designed for the neck to perform weighted fusion of multi-scale feature maps. Finally, a novel task-aligned detection head (TDH) is developed to improve the classification and localization performance of the detection head. Extensive experimental results demonstrate that, compared to the original YOLOv8 model, the detection method proposed in this paper has achieved a 7.8% increase in mean Average Precision at Intersection over Union 0.5 (mAP@0.5) value, effectively enhancing the detection capability for small target defects on hot-rolled steel strips surface. Moreover, the frames per second (FPS) has reached 79.8, meeting the real-time detection requirements of industrial sites.

During eddy current testing, most defects observed in conductive materials are generally interpreted as loss of material. However, there are other types of defects that initially appear as material loss, but can later be filled with polluting substances. These polluted conductive substances will entirely or partially fill the volume of the primary defect. It is therefore essential to take this type of defect into the modeling by representing them as electrically conductive volumes. These defects include impurities, inclusions and micro-welds…etc. For this study, the focus lies on investigating a rectangular shaped defect aligned with the direction of the fibers. The defect occupies 25 to 200% respectively of the total longitudinal conductivity of a four-ply CFRP plate. To achieve this, a circular multi-coils sensor was developed. We investigated electromagnetic phenomena using a three-dimensional (vec {A} - {v}) formulation, and then we resolved this later using a numerical approach called the finite element method. The cartography of the induced currents densities in the presence of the defect are depicted and the simulation results obtained from the normalized impedance are plotted in the polar diagram. This investigation demonstrates through numerical simulation that this type of defect must be taken into consideration in order to complete the developed models.

In oil and gas pipeline inspections, the performance of the inline ultrasonic internal detector depends on the transmission and reception of ultrasonic echo signals by its transducer. Wave propagation is affected by environmental noise, particularly from high-pressure background noise and pressure wave transmission. The detector’s passage through girth weld seams induces significant pressure fluctuations, which are essential for locating the detector. Considering these factors is crucial for signal analysis. To address this, experiments with a frequency modulation control system were conducted on an experimental platform. Nine simulation experiments focused on the detector’s operation through circumferential weld seams, collecting high-frequency pressure and ultrasonic echo signal data. The analysis targeted the impact of pressure changes on wall thickness measurement accuracy. Notable pressure fluctuations occurred when the detector passed girth weld seams, with a maximum change of 1.36 MPa in Experiment 7# at the 4th weld seam. Experiment 9# showed the highest noise amplitude of  0.00013 and 0.00302 when passing the 1st girth weld seam, and the highest average speed, 0.13 m/s, was recorded in Experiment 5#. Despite these variations, they minimally affected the inspection tool’s accuracy, confirming its reliability under environmental influences.

This paper addresses the challenge in traditional laser ultrasonic methods, where the detection of surface defects in metal materials is often hindered by noise, and a novel approach that combines laser ultrasonics with Duffing oscillators to achieve a high signal-to-noise ratio for weak defect signals on metal surfaces is proposed. By leveraging the sensitivity of the Duffing oscillator’s chaotic system to initial conditions and its noise immunity, we can accurately identify the location of weak defects. Simulation results confirm the effectiveness and stability of this method for detecting surface defects in metal sheets.

A method for defect recognition in printed circuit boards using neural networks is discussed. An analysis of various neural network architectures is performed to identify the most effective one. An approach to data filtering simulating the operation of a microtomograph using convolutional autoencoders is also presented. The quality of the proposed approaches was evaluated using the mean Average Precision (mAP) metric for YOLOv8 and Faster R-CNN models.