Russian Journal of Nondestructive Testing最新文献_第3页

Memory-Efficient Approach to Modeling Piezoelectric Immersion Ultrasonic Testing of Tubes 基于记忆效率的管道压电浸没超声检测建模方法

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S1061830926600061

Liangxue Cai, Huan Zhang, Yuejun Zheng, Jianwen Liu, Zhengqi Diao, Guangli Xu

{"title":"Memory-Efficient Approach to Modeling Piezoelectric Immersion Ultrasonic Testing of Tubes","authors":"Liangxue Cai, Huan Zhang, Yuejun Zheng, Jianwen Liu, Zhengqi Diao, Guangli Xu","doi":"10.1134/S1061830926600061","DOIUrl":"10.1134/S1061830926600061","url":null,"abstract":"During ultrasonic internal inspection experiments, environmental fluctuations and operational errors inevitably introduce deviations in the results, while the obtainable parametric data remain limited. Therefore, it is necessary to conduct ultrasonic internal inspection simulations and establish a digital R and D platform for ultrasonic inspection devices to enhance the accuracy and generalizability of the results. However, simulating ultrasonic internal inspection is an extremely complex process. At a detection frequency of 5 MHz, solving the constructed 3D model demands substantial computational resources, including memory exceeding 1 TB and extended runtime. To address this challenge, a simulation model for ultrasonic internal inspection of volumetric defects with circumferential symmetry in wave propagation was developed using COMSOL software, based on process parameters from an actual piezoelectric ultrasonic inspection experimental platform. The actual inspection process was divided into three stages: ultrasonic emission, propagation and reception. Corresponding 3D, 2D and 3D simulation models were established, along with parameter transfer methods between each stage. The model’s accuracy was verified by comparing simulation and experimental results in four aspects: waveform similarity, amplitude variation rate, dominant peak frequency and wall thickness. By turning the whole into parts, the simulation model for a single inspection consists of 26 combined simulations, each with significantly reduced memory requirements—enabling execution on standard computers. The established model effectively and clearly describes the entire internal inspection process.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 6","pages":"747 - 760"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CTFT-based Approach for Parameter Identification in Reinforced Concrete 基于ctft的钢筋混凝土参数识别方法

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S1061830925605434

Ling Huang, Yueqi Wang, Baoluo Li

{"title":"CTFT-based Approach for Parameter Identification in Reinforced Concrete","authors":"Ling Huang, Yueqi Wang, Baoluo Li","doi":"10.1134/S1061830925605434","DOIUrl":"10.1134/S1061830925605434","url":null,"abstract":"Reinforced concrete structures are critical to numerous infrastructures, making quality inspection essential. Electromagnetic induction techniques, such as pulsed eddy current (PEC), are widely applied in nondestructive testing (NDT) due to their high metal sensitivity and strong anti-interference capability. However, electromagnetic induction signals exhibit strong local perturbations, complex temporal nonlinearities, and significant time–frequency coupling. Existing methods often depend on neural networks that struggle to capture such nonlinear temporal patterns, or require additional sensors, which increase complexity and cost. To this end, this paper constructs a hybrid dataset of simulated and experimental data and proposes CTFT, an end-to-end regression model integrating CNN, Multi-stage Sparse Transformer, Task-Specific Attention (TSA), and Frequency Encoding. By synergizing CNN’s local feature extraction with Transformer’s global modeling, the model effectively adapts to the characteristics of electromagnetic induction data. A task-specific attention mechanism is introduced to adaptively fuse branch features, while a mean-based sparse attention and multi-stage aggregation strategy mitigate the quadratic computational cost of Transformers. Furthermore, a frequency-encoding mechanism embeds excitation frequency priors, enhancing modeling under multi-frequency conditions. Optimized via a ‘simulation pre-training and mixed-data fine-tuning’ strategy, the model achieved ±1 mm accuracies of 92.65% for rebar diameter and 97.07% for cover thickness. With ±2 mm accuracies reaching 98.93 and 99.05%, the model demonstrates superior performance and significant engineering potential.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 6","pages":"824 - 840"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Infrared Thermography for Quality Assurance in Welding and Additive Manufacturing: Review and Case Perspectives 红外热成像在焊接和增材制造中的质量保证：回顾和案例展望

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S1061830926600188

S. Kumar

{"title":"Infrared Thermography for Quality Assurance in Welding and Additive Manufacturing: Review and Case Perspectives","authors":"S. Kumar","doi":"10.1134/S1061830926600188","DOIUrl":"10.1134/S1061830926600188","url":null,"abstract":"Infrared Thermography (IRT) has emerged as a powerful non-contact technique for real-time process monitoring, defect detection, and quality assurance in advanced manufacturing. Its rapid, full-field imaging capability makes it particularly suitable for dynamic thermal processes such as welding and metal additive manufacturing (AM). Over the past two decades, IRT has progressed from a primarily qualitative inspection method to a quantitative diagnostic and control tool, supported by advances in detector technology, calibration methodologies, data analytics, and artificial intelligence. This paper presents a structured review of IRT applications in welding and additive manufacturing, addressing radiative heat transfer considerations, emissivity-related measurement uncertainty, defect-induced thermal signatures, and integration with process modelling and machine learning frameworks. A comparative evaluation of thermographic implementation in welding and AM is provided, highlighting process-specific challenges and limitations. The review also identifies key constraints related to emissivity variation, defect detectability limits, and measurement uncertainty, while outlining future research directions toward digital twin integration and intelligent manufacturing systems.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 6","pages":"848 - 863"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thickness Measurement and Anomaly Detection in Transmission Belts using Adaptive Dual-Scale Analysis 基于自适应双尺度分析的传送带厚度测量与异常检测

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S106183092560515X

Xinyu Zheng, Zejin Liu, Junyi Wang, Yuanshan Lin, Zhijun Li, Yuanhua Sun, Lanlan Pan

{"title":"Thickness Measurement and Anomaly Detection in Transmission Belts using Adaptive Dual-Scale Analysis","authors":"Xinyu Zheng, Zejin Liu, Junyi Wang, Yuanshan Lin, Zhijun Li, Yuanhua Sun, Lanlan Pan","doi":"10.1134/S106183092560515X","DOIUrl":"10.1134/S106183092560515X","url":null,"abstract":"Abnormal variations in transmission belt thickness are a critical cause of mechanical transmission failure, efficiency reduction, and abnormal noise, necessitating highly accurate and automated detection methods. With technological advancements, 3D point cloud detection has emerged as a superior solution, overcoming the limitations of 2D imaging by enabling precise defect quantification and demonstrating strong robustness in complex working conditions. This paper proposes a novel automated method for detecting abnormal thickness mutations in transmission belts. High-density 3D point cloud data are acquired using a line laser sensor and preprocessed for analysis. To improve computational efficiency, a uniform slicing method is employed to reduce data dimensionality, while reference baselines are established along both edges of the pulley to provide geometric benchmarks for thickness calculation. To address interference from industrial markings and noise, an adaptive window adjustment strategy combined with curvature constraints is applied to extract feature points on the belt’s backside, and a neighborhood consistency-weighted model is designed to refine thickness computation. Furthermore, to account for inherent thickness non-uniformity in transmission belts, a dual-scale median difference analysis and dynamic thresholding mechanism are proposed, enabling cooperative detection of local mutations and global trends for anomaly identification. Experimental results demonstrate that the proposed method achieves a maximum absolute thickness measurement error of 0.029 mm, a repeatability error of ±0.01 mm, and an average detection time of 0.65 s. The anomaly detection accuracy reaches 94.4%, with an average processing time of 2.09 s. The method exhibits high robustness and measurement precision, meeting practical inspection requirements and providing robust technical support for transmission belt maintenance and quality control.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 6","pages":"864 - 878"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Direct and Inverse Problems of Magnetostatics for Uniformly Magnetized Bodies 均匀磁化体的静磁学正逆问题

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S1061830926601340

V. Y. Raevskii, O. V. Kudryashova

{"title":"Direct and Inverse Problems of Magnetostatics for Uniformly Magnetized Bodies","authors":"V. Y. Raevskii, O. V. Kudryashova","doi":"10.1134/S1061830926601340","DOIUrl":"10.1134/S1061830926601340","url":null,"abstract":"The paper describes the basic schemes for solving direct and inverse magnetostatic problems based on the fundamental integro-differential equation of magnetostatics, both for the general case of arbitrary magnetization of a magnet, arising when it is placed in the field of external sources, and for the case of its uniform magnetization. It is shown that the schemes presented in the paper for solving these problems for uniformly magnetized bodies, although requiring the creation of conditions to ensure such magnetization, nevertheless allow one to avoid many fundamental problems of general schemes, significantly simplify them, and propose a number of new effective algorithms. An algorithm is described and justified that reduces the solution of the direct problem for a magnet with a defect in the case of uniform magnetization to the solution of direct problems for “defect-freeˮ magnets. This algorithm significantly expands the database of various geometric shapes of magnets and defect shapes in them, for which, under their uniform magnetization, an algorithm for an analytical or numerical-analytical method for solving the direct problem of magnetostatics exists.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 6","pages":"793 - 802"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel Monitoring Method for Damage Evolution in GFRP Bolted Joints Using Bolt Inclination as a Local Kinematic Indicator 基于螺栓倾角作为局部运动指标的GFRP螺栓连接损伤演化监测新方法

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S1061830926600474

Y. Faci, A. Djilali, O. M. Tazerout, A. Mebtouche

引用次数: 0

Attention-Guided Adaptive Compressed Sensing for Laser Ultrasonic Signal Reconstruction 激光超声信号重构的注意引导自适应压缩感知

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-09-22 DOI: 10.1134/S1061830926600115

Kaizheng Wang, Haitao Wang, Yi Jiang, Shuping Wang, Shengping Wu, Xianming Yang

{"title":"Attention-Guided Adaptive Compressed Sensing for Laser Ultrasonic Signal Reconstruction","authors":"Kaizheng Wang, Haitao Wang, Yi Jiang, Shuping Wang, Shengping Wu, Xianming Yang","doi":"10.1134/S1061830926600115","DOIUrl":"10.1134/S1061830926600115","url":null,"abstract":"Laser ultrasonic (LU) testing is a high-resolution, non-contact nondestructive evaluation technique with considerable potential for surface defect inspection in additive manufacturing (AM) components. However, reliable LU imaging typically requires dense spatiotemporal sampling, resulting in excessive data volume and computational burden. Although compressed sensing (CS) provides an effective framework for sampling reduction, conventional random measurement strategies fail to exploit the intrinsic structural characteristics of LU signals. In particular, laser ultrasonic surface wave signals exhibit pronounced non-uniform energy distribution in the time domain, where defect-sensitive information is mainly concentrated in direct arrivals, defect-induced scattering, and interface reflections. Under low sampling rates, random measurements are therefore prone to losing critical information. To address this issue, an attention-guided adaptive CS method is proposed for LU signal reconstruction. By integrating prior energy distribution knowledge with a convolutional attention mechanism, a content-aware measurement matrix is constructed to preferentially sample information-rich signal segments. An end-to-end one-dimensional convolutional neural network is further developed to reconstruct high-quality ultrasonic signals from compressed measurements. Experimental results obtained from LU inspection of TC4 titanium alloy specimens with surface defects demonstrate that, at a compression ratio of 40%, the proposed method consistently outperforms conventional approaches in terms of reconstruction accuracy and imaging reliability, highlighting its effectiveness for efficient LU-based surface defect inspection.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 6","pages":"761 - 775"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of Fatigue Cracks in Aluminum Alloys Based on Back Propagation Neural Network 基于反向传播神经网络的铝合金疲劳裂纹识别

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-08-27 DOI: 10.1134/S1061830925605732

Shi-jie Jin, Xue-ying Xing, Ya-nan Yang, Xiao-ying Liu, Zhong-bing Luo

{"title":"Identification of Fatigue Cracks in Aluminum Alloys Based on Back Propagation Neural Network","authors":"Shi-jie Jin, Xue-ying Xing, Ya-nan Yang, Xiao-ying Liu, Zhong-bing Luo","doi":"10.1134/S1061830925605732","DOIUrl":"10.1134/S1061830925605732","url":null,"abstract":"Aluminum alloys in service are affected by cyclic load to form fatigue cracks, even leading to structure failure. The fatigue cracks have narrow widths with insufficient signal-to-noise ratio (SNR) during ultrasonic testing, which is not beneficial to defect identification. In this paper, back propagation neural network (BPNN) and Shapley additive explanation (SHAP) are combined to determine the fatigue cracks in aluminum alloys accurately and efficiently. The simulated and experimental array signals were collected by full matrix capture (FMC), and the top 60% strong-response signals were selected to build datasets for model training and prediction. Then, 18 key features were determined by SHAP as input to train the BPNN model for identifying fatigue cracks. The prediction results show that the recognition accuracy is as high as 98.4%. In addition, the established BPNN model yields high recognition accuracy for both simulated and experimental signals with different SNRs. Finally, the presence or absence of fatigue cracks can be determined with an accuracy rate of 98.5%, even changing the proportion of the experimental signals with strong-response amplitudes.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 5","pages":"633 - 648"},"PeriodicalIF":1.3,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148823025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Efficiency Optimization Strategy for Wedge Two-Layer Medium Total Focusing Method Imaging: Simulation and Experimental Verification 楔形两层介质全聚焦法成像效率优化策略：仿真与实验验证

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-08-27 DOI: 10.1134/S1061830925605628

Yongyun Long, Qian Xu, Xinkuan Zhao, Muattar Saydi

{"title":"The Efficiency Optimization Strategy for Wedge Two-Layer Medium Total Focusing Method Imaging: Simulation and Experimental Verification","authors":"Yongyun Long, Qian Xu, Xinkuan Zhao, Muattar Saydi","doi":"10.1134/S1061830925605628","DOIUrl":"10.1134/S1061830925605628","url":null,"abstract":"Accelerated algorithms and imaging studies of the total focusing method (TFM) technique are more common in the case of longitudinal waves or a single target medium. A wedge two-layer medium using full matrix capture (FMC) is of great interest for detecting and quantifying crack-like defects. However, the huge amount of FMC data to be post-processed makes computing the point of the incidence significantly time-consuming, therefore, a time-efficient technique for finding the incidence point is critical. In this work, the segmental-search method (SSM) is presented to quickly determine the point of incidence at a planar refractive interface between a two-layer medium. The constraint that the point of incidence be between the transmitting element and the pixel is imposed to minimize the processing time of the SSM. Meanwhile, optimization methods for discrete step sizes in the search interval and TFM grid size are proposed to improve the SSM-based TFM imaging speed. Finally, based on the simulated results, actual detection experiments and a series of similar analyses are conducted to verify the effectiveness of the optimization strategy. The results indicate that the proposed efficiency optimization strategy can quickly determine the incident point and reasonably select the imaging grid size without affecting the imaging quality, and further improve the TFM imaging speed.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 5","pages":"584 - 598"},"PeriodicalIF":1.3,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148823010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation and Experiment on Stress Detection Based on Ultrasonic Nonlinear Effect 基于超声非线性效应的应力检测仿真与实验

IF 1.3 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2026-08-27 DOI: 10.1134/S1061830925606336

Ting Ma, Guocheng Xu, Juan Dong, Xiaopeng Gu, Guanghao Zhou, Hongxiao Wang, Mingfu Shao

{"title":"Simulation and Experiment on Stress Detection Based on Ultrasonic Nonlinear Effect","authors":"Ting Ma, Guocheng Xu, Juan Dong, Xiaopeng Gu, Guanghao Zhou, Hongxiao Wang, Mingfu Shao","doi":"10.1134/S1061830925606336","DOIUrl":"10.1134/S1061830925606336","url":null,"abstract":"This study systematically investigated the variation of the second-order relative nonlinear coefficient (β′) of critically refracted longitudinal (LCR) waves at different propagation distances and loads, based on ultrasonic nonlinear effects, in combination with finite element simulations and experimental methods. In the subsequent tensile experiments, the stability of the measurement system was verified by analyzing the amplitudes of the fundamental and second-harmonic components across different specimens under various excitation voltages, as well as the variation patterns of the β′. Utilizing this system, the β′ and sound velocity obtained under different sampling rate conditions were further analyzed. Compared with the strict reliance of the sound velocity method on high-frequency sampling and precise time-delay measurement, β′ can achieve highly sensitive measurement under conventional sampling conditions. Finally, under the condition of a sampling rate of 10 GHz, the variation trends of β′ and sound velocity under different stress states and their sensitivity to stress were studied.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"62 5","pages":"649 - 665"},"PeriodicalIF":1.3,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148823026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0