Russian Journal of Nondestructive Testing最新文献

This nondestructive technique involves obtaining the speeds of P-waves based on frequencies measured using the impact-echo method (IEM). Once the P-wave is generated, the sensor captures the horizontal displacement signal from the concrete surface. P-waves are used to estimate the compressive strength of concrete. Test results demonstrate that the velocity of P-waves is sensitive to changes in concrete strength at each age. This approach is capable of calculate the P-wave velocity with relative ease, thereby enabling the prediction of compressive strength. These measured values were used to verify the accuracy of the IEM. The proposed IEM was verified using concrete specimens produced with drilling-core for different strength grades. The results indicate that the proposed method can significantly enhance the preciseness of strength evaluation. Therefore, the P-wave based method is appropriate for in situ structures with features of portable, speed, convenience, and nondestructive of the proposed method.

This paper describes the process of nondestructive testing of a Dewar vessel in a cryogenic setup for studying the physical characteristics of PPMS-9 materials using a mass spectrometric method. The methodology enabled the detection and localization of a leak, as well as an estimation of its size, which was approximated to be that of a circular hole with a diameter of approximately 0.6 microns. Following the application of Stycast epoxy adhesive to repair the defect, the evaporation rate of liquid helium was normalized.

This study proposes a deep learning-based damage recognition method using vibration excitation of flange bolts, focusing on damage feature extraction and classification control of vibration signals, which holds significant value for health monitoring applications. To address noise and nonlinear features in acoustic emission signals, the Mel-frequency cepstral coefficient (MFCC) is used for feature extraction. The ResNet-50 model is improved by integrating the convolutional block attention module (CBAM) and squeeze-and-excitation (SE) modules to enhance recognition accuracy. This innovative approach effectively overcomes the limitations of traditional methods in complex signal processing, improving both the precision and reliability of the recognition process. Experimental results show that the method performs excellently in bolt damage identification with an accuracy rate exceeding 98%, validating its effectiveness and robustness in acoustic emission signal analysis and damage detection. Furthermore, the method demonstrates strong versatility, capable of adapting to damage monitoring tasks under various working conditions, providing reliable technical support for the engineering application of bolt health monitoring in complex environments.

In recent years, the application scenarios of cylindrical concrete structures have gradually diversified, such as the piers of high-speed railway bridges and the shafts of tunnels. Although this type of structure has superior load-bearing capacity, various types of damage, such as holes and cracks, may occur during both the pouring and service periods. These damages threaten the safety of the building structure. Therefore, conducting damage detection on cylindrical concrete structures is of great significance.This paper proposes a damage imaging identification method for cylindrical concrete structures based on guided wave tomography technology. This method does not require the analysis of multimodal characteristics when ultrasonic guided waves propagate in cylindrical structures.This paper mainly studies the following: (1) Establishing a simulation model of cylindrical concrete structures; (2) Conducting damage imaging recognition research by comparing three-dimensional cylindrical structures to plate-shaped structures; (3) Using the spectral difference of the signal before and after damage as the damage factor for damage identification; (4) Investigating the problems of damage imaging recognition and location in cylindrical concrete structures through simulations and experiments. After research, the radial errors of damage imaging positioning obtained by the simulation and experiment using the method proposed in this paper are 10.47 and 10.59 mm, respectively. These results are of great significance for the damage detection research of cylindrical concrete structures.

In ultrasonic inspection, digital aperture focusing (DAF) is increasingly being used to reconstruct reflector images. The reliability of inspection is determined by the quality of the DAF image—signal-to-noise ratio, ability to reconstruct the image of the entire reflector boundary, and resolution. Various methods are used to achieve super-resolution of echoes: maximum entropy method, methods of building autoregressive signal models, compressive sensing (CS) method, etc. To use these methods, it is important to know the impulse response of the ultrasound system, which can be measured or obtained using “blind” deconvolution methods used in image and signal processing. In this paper we consider the minimum entropy deconvolution (MED) method for estimating the impulse response of an ultrasonic flaw detector and achieving the effect of image super-resolution, where knowledge of the transfer function of the system is critical. The effectiveness of the proposed method is confirmed by the results of model experiments.

Aluminum plates are widely used in various industrial fields such as aerospace and automotive manufacturing, and their structural integrity directly affects the safe operation and service life of equipment. Therefore, research on damage identification of aluminum plates is of great significance. This study explores the identification of aluminum plate damage based on guided waves and correntropy spectral density. Guided waves have advantages such as long propagation distance and sensitivity to small defects, and can be used as effective excitation signals for detecting aluminum plate damage. The correntropy spectral density can extract damage related feature information from complex signals, improve the accuracy of damage identification, and have a certain degree of noise resistance. By arranging sensors on aluminum plates, collecting guided wave signals, processing and analyzing the signals using relevant entropy spectral density, a damage identification model for aluminum plates is constructed. The experimental results show that this method can accurately identify the location and degree of damage to aluminum plates, and has significantly improved recognition accuracy and anti-interference ability compared to traditional methods. This study provides a new technological approach for efficient and accurate detection of aluminum plate damage, which has important practical value for ensuring the safe and stable operation of related industrial equipment.

Pipeline structures are widely used in many fields and play an extremely important role in social life. However, they are prone to damage during service. If not detected and addressed promptly, such damage can lead to serious consequences. Therefore, to timely assess the health status of pipeline structures, this paper presents a method for identifying pipeline damage using guided waves. This method is based on a two-dimensional probabilistic damage imaging algorithm, which is transformed into a cylindrical coordinate system through coordinate transformation. By combining the spectral peak differences in the response signals before and after pipeline damage, the method achieves damage identification and imaging. The effectiveness of the method was validated through simulations and experiments. The results showed that the damage localization errors were 9.82 mm in simulations and 14.72 mm in experiments, respectively. These results demonstrate significant value for pipeline damage detection research.

This paper presents the design and modeling of a rotating eddy current array (ECA) system tailored for efficient detection and sizing of defects in complex and multilayer aerospace structures. The proposed system integrates a transmit/receive coil configuration with a rotating scanning mechanism, enhancing sensitivity, spatial resolution, and inspection coverage. Detailed descriptions of the sensor architecture, multiplexing strategy, and excitation parameters are provided, along with schematic illustrations of the system design. Simulation results demonstrate the system’s ability to detect defects regardless of rivet size or layer geometry, indicating uniform sensitivity and improved robustness. These findings confirm the system’s potential for reliable and rapid non-destructive evaluation of aerospace components, particularly in geometrically complex environments.

The length of the irregular head and tail regions of medium and thick plates is a crucial factor affecting steel yield. This paper proposes a shearing length calculation method based on multi-modal edge feature fusion to address the limitations of current detection methods in shape recognition and length calculation accuracy. First, high-resolution industrial cameras capture the surface images of the steel plate, and motion distortion errors are corrected to accurately obtain the outer edge profile. Then, a dual-objective optimization model is designed, integrating width consistency criteria and edge linearity constraints, ensuring precise adaptive positioning of the shearing position. Finally, the shearing length of the irregular head and tail regions is calculated using the constructed cutting guide lines, and a polynomial regression error correction model is applied to improve calculation accuracy and stability, yielding the effective plate length. Experimental results show that the maximum error in detecting the shearing length of the head and tail is less than 1mm, with a 0.4% increase in steel utilization. The method has engineering application value by adjusting and optimizing rolling process parameters based on the shape and length of the irregular regions.

Deviation from the nominal wall thickness of a pipe—both during manufacturing and in operation—is a critical factor affecting the durability of equipment. This study proposes a model of acoustic wave propagation across a pipe cross section with eccentricity. The model forms the theoretical basis for a method of integral assessment of wall thickness nonuniformity in small-diameter pipes. The method is implemented using a specialized flexible piezoelectric transducer based on polyvinylidene fluoride (PVDF) on several samples of seamless pipes with varying thickness and validated by the results of local ultrasonic thickness gaging.