Russian Journal of Nondestructive Testing最新文献

Determination of Optimal Parameters of Guided Wave Excitation for Non-contact Ultrasonic Inspection of Anisotropic Composite Plates 各向异性复合材料板非接触超声检测中导波激励最佳参数的确定

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925700147

O. A. Ermolenko, E. V. Glushkov, N. V. Glushkova

{"title":"Determination of Optimal Parameters of Guided Wave Excitation for Non-contact Ultrasonic Inspection of Anisotropic Composite Plates","authors":"O. A. Ermolenko, E. V. Glushkov, N. V. Glushkova","doi":"10.1134/S1061830925700147","DOIUrl":"10.1134/S1061830925700147","url":null,"abstract":"The present study is carried out within the framework of a semi-analytical computer model. The model is based on the solution of a three-dimensional boundary value problem concerning the interaction of the acoustic field generated by an air-coupled ultrasonic transducer with a composite plate made of fiber-reinforced pregs. The investigation focuses on the influence of composite’s anisotropy and the tilt of the non-contact transducer on the directivity diagrams, frequency response, and dispersion properties of the guided waves excited in the plate. The wave field is described by the solution of the coupled problem for the system source–acoustic-medium–composite-plate obtained in the form of the inverse Fourier transform path integrals of the waveguide Green’s matrix and source parameters. The residual technique and the stationary phase method gives an explicit physically visual representation for the guided waves excited contactlessly in the composite plate. Utilizing this framework, the optimal transducer tilt angles for exciting waves of the desired type at specific center frequencies are determined. Numerical results demonstrating the dependence of the amplitude–frequency characteristics of the excited waves and the optimal transducer tilt angle on the sample’s structure and elastic properties are presented.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 6","pages":"610 - 619"},"PeriodicalIF":0.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011604","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

Matched Filter-Based Post Processing Approach for Active Infrared Thermography for Nondestructive Testing and Evaluation of Carbon Fibre Reinforced Polymer Materials 基于匹配滤波的碳纤维增强高分子材料主动红外热成像无损检测与评价后处理方法

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925603940

Suresh Kumar Bhambhu, Vanita Arora, Ravibabu Mulaveesala

{"title":"Matched Filter-Based Post Processing Approach for Active Infrared Thermography for Nondestructive Testing and Evaluation of Carbon Fibre Reinforced Polymer Materials","authors":"Suresh Kumar Bhambhu, Vanita Arora, Ravibabu Mulaveesala","doi":"10.1134/S1061830925603940","DOIUrl":"10.1134/S1061830925603940","url":null,"abstract":"This article reports on the effectiveness of infrared thermography (IRT) in detecting blind holes of varying depth and diameter in carbon fiber reinforced polymer (CFRP) sample. It utilises halogen lamps as the heat source and implements three excitation techniques: pulse thermography (PT), lock-in thermography (LT) and frequency modulation thermal wave imaging (FMTWI); along with that, it compares two post-processing approaches, cross-correlation (CC) and frequency domain phase (FDP) on the obtained thermal images. The signal-to-noise ratio (SNR) is considered a figure of merit for evaluating the effectiveness of each technique and its associated post-processing approaches. The results demonstrate that the CC post-processing technique consistently outperforms the FDP method in enhancing defect visibility and improving SNR values across all excitation techniques and configurations. This research highlights the potential of IRT as a reliable, non-destructive testing method for detecting and characterising defects in a chosen CFRP test sample.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 6","pages":"704 - 714"},"PeriodicalIF":0.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011834","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

Recognition of Reflector Type Using Neural Network Based on TOFD Echoes 基于TOFD回波的神经网络反射器类型识别

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925600285

E. G. Bazulin, L. V. Medvedev

引用次数: 0

Testing of the Technical Condition of Concrete Products and Structures by the Method of Acoustic–Electrical Transformations 用声电变换法检测混凝土制品和结构的技术条件

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925600121

V. F. Gordeev, A. A. Bespal’ko, S. G. Shtalin, S. Yu. Malyshkov, Junhua Luo

{"title":"Testing of the Technical Condition of Concrete Products and Structures by the Method of Acoustic–Electrical Transformations","authors":"V. F. Gordeev, A. A. Bespal’ko, S. G. Shtalin, S. Yu. Malyshkov, Junhua Luo","doi":"10.1134/S1061830925600121","DOIUrl":"10.1134/S1061830925600121","url":null,"abstract":"The article discusses the possibility of using the acoustic-electrical transformation method to detect cracks and mechanical compressive strength of concrete. Numerical and experimental studies of changes in the parameters of the electromagnetic response of model samples of concrete made of a cement-sand mixture with a crack to a deterministic pulsed acoustic impact are presented. It is shown that the presence of a crack is determined by changes in the amplitude-frequency parameters of the electromagnetic response from the sample. An example of determining the locations of weakening of the mechanical strength of a concrete construction beam based on the parameters of electromagnetic signals is given. The results of comparative tests for determining the mechanical compressive strength of concrete, obtained using a calibrated sclerometer and an acoustic-electric method, are shown. The results of monitoring the mechanical strength of concrete structures of an operating bridge crossing over a river are also presented based on the parameters of the electromagnetic response that arise during impact probing with acoustic pulses.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 6","pages":"620 - 632"},"PeriodicalIF":0.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011837","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

An Ultrasonic Echo Defect Recognition Method for Oil and Gas Pipelines Combining CNN-LSTM and Multi-Head Self-Attention Mechanism 结合CNN-LSTM和多头自关注机制的油气管道超声回波缺陷识别方法

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925603526

Zhanming Zhang, Minghui Wei, Zheng Wang

{"title":"An Ultrasonic Echo Defect Recognition Method for Oil and Gas Pipelines Combining CNN-LSTM and Multi-Head Self-Attention Mechanism","authors":"Zhanming Zhang, Minghui Wei, Zheng Wang","doi":"10.1134/S1061830925603526","DOIUrl":"10.1134/S1061830925603526","url":null,"abstract":"Oil and gas pipelines are crucial infrastructures in the oil and gas industry, responsible for transporting resources and connecting supply and demand. However, the complex operational environment, influenced by external and internal factors, leads to varying degrees of damage or structural failures as service time increases. If these defects are not identified and repaired promptly, they can result in serious safety incidents, endangering lives and property. To address the problems of uneven recognition accuracy and insufficient generalization ability of traditional oil and gas pipeline defect recognition and classification methods under different working conditions, the paper utilizes convolutional neural network (CNN) to extract spatial features from the ultrasonic echo sequences, which are then cascaded to long short-term memory (LSTM) network to mine the temporal features hidden within the ultrasonic echo sequences. Next, by employing a multi-head self-attention mechanism to dynamically adjust weights based on feature importance, the accuracy of defect identification and classification is improved. Validation using actual ultrasonic echo data from pipeline defects shows that the accuracy rates for identifying and classifying signals with no defects, as well as with defects at depths of 2, 5, and 8 mm, are 94, 89, 100, and 100%, respectively. The corresponding precision, recall, and F1-score all exceed 90%, significantly outperforming traditional methods. Furthermore, under the multi-condition noise resistance and generalization validation, the model consistently maintains an accuracy rate of over 90%, demonstrating robust noise resistance and strong generalization capabilities.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 6","pages":"633 - 653"},"PeriodicalIF":0.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011605","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

Ultrasonic-Based Impact Energy Level Prediction in Composite Materials Using Sequential Backward Selection and Adaptive Neuro-Fuzzy Inference System 基于顺序逆向选择和自适应神经模糊推理系统的复合材料超声冲击能级预测

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925603575

A. Lourari, A. Bouzar Essaidi, B. El Yousfi, L. Rebhi

{"title":"Ultrasonic-Based Impact Energy Level Prediction in Composite Materials Using Sequential Backward Selection and Adaptive Neuro-Fuzzy Inference System","authors":"A. Lourari, A. Bouzar Essaidi, B. El Yousfi, L. Rebhi","doi":"10.1134/S1061830925603575","DOIUrl":"10.1134/S1061830925603575","url":null,"abstract":"Accurately predicting impact energy levels in glass fiber-reinforced polymer (GFRP) composites is crucial for assessing material performance under varying impact conditions. This study presents a novel methodology that integrates sequential backward selection (SBS) and adaptive neuro-fuzzy inference system (ANFIS) to enhance the precision of impact energy estimation using non-destructive evaluation techniques. The proposed approach begins with the application of controlled impact energies to composite specimens, followed by ultrasonic inspection using the Mistras system to acquire B-scan and C-scan images. These images are subsequently converted into representative signals, from which key indicators are extracted. To optimize computational efficiency and improve predictive accuracy, SBS is employed to systematically select the most relevant features, minimizing redundancy and noise. The refined feature set is then used as input for an ANFIS model, which effectively captures nonlinear relationships between ultrasonic data and impact energy levels. The results demonstrate the potential of integrating advanced machine learning techniques with ultrasonic non-destructive evaluation for precise and reliable impact energy prediction in composite materials. This methodology provides a robust framework for structural health monitoring and predictive maintenance in industries where composite integrity is a critical concern.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 6","pages":"654 - 669"},"PeriodicalIF":0.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011784","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 Gamma Level Gauging at High Temperature and Pressure Using a New Calibration Technique in the Petrochemical Industry 石化行业高温高压伽马测量新技术的应用

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925603435

S. Z. Islami rad, R. Gholipour Peyvandi

{"title":"The Gamma Level Gauging at High Temperature and Pressure Using a New Calibration Technique in the Petrochemical Industry","authors":"S. Z. Islami rad, R. Gholipour Peyvandi","doi":"10.1134/S1061830925603435","DOIUrl":"10.1134/S1061830925603435","url":null,"abstract":"The ability to precisely determine the level and height of liquids in industrial reactors and vessels that operate at high pressure and temperature plays a crucial role in the petrochemical, oil, and steel industries. Since the exact measurement of fluid or liquid levels is impossible due to high pressures and temperatures in vessels, a technique has been presented to calibrate gamma level gauges. To achieve this aim, the nuclear level gauge of a petrochemical stripper was simulated using Monte Carlo N-Particle eXtended (MCNPX) in real and operational conditions in the oil district in two stages. First, the nuclear level gauge consisting of a source, detector, and vessel (stripper), including water and air for calibration, was simulated with different height percentages. The results were compared, analyzed, and validated with experimental data in operational conditions. According to the results, the mean relative error (MRE%) was less than 6.71% and the root mean square error (RMSE) was predicted to be 0.01. The results showed that the acquired data from the simulation are in good agreement with real data (experimental). Then, the level gauge and stripper containing urea and gases at high temperature and pressure, and with similar height percentages in the first stage, were simulated. The results, which are completely consistent with the experimental findings, were converted into the required format and input into the nuclear electronic system for final calibration.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 6","pages":"715 - 723"},"PeriodicalIF":0.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011835","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

Analysis of the Influence Factors on the Dynamic Response of a Lined Tunnel Embedded in an Inhomogeneous Half-Space Subjected to SH Waves SH波作用下非均匀半空间衬砌隧道动力响应影响因素分析

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925603885

Song-Chol Ri, In-Gu Jo, Hyo-Song Jong, JongHyok Ri

引用次数: 0

Modeling and Experimental Study of Thermal Equivalents of Impact Damage in Composites during the Development of Reference Samples in Thermal Testing 热测试参考样品开发过程中复合材料冲击损伤热当量的建模与实验研究

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925700160

V. P. Vavilov, A. O. Chulkov, O. A. Ganina

引用次数: 0

Relationship between Magnetic Parameters and the Recrystallization Degree During Annealing of Predeformed Nickel 预变形镍退火过程中磁性参数与再结晶程度的关系

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-09-08 DOI: 10.1134/S1061830925700159

E. A. Putilova, K. D. Malygina, L. S. Goruleva, V. N. Kostin, O. N. Vasilenko, V. N. Perov

引用次数: 0