Russian Journal of Nondestructive Testing最新文献_第5页

Measuring the Degree of Anisotropy of Electrical Properties of Epoxy Resin–Magnetic Fluid–Carbon Nanotube Composite 环氧树脂-磁流体-碳纳米管复合材料电性能各向异性程度的测定

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830924603453

A. E. Postelga, S. V. Igonin

引用次数: 0

Reconfigurable Reflector Based Ultrasonic Waveguide for Temperature Measurement 基于可重构反射器的温度测量超声波导

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830924603313

Arun Valabhoju, Suresh Periyannan

{"title":"Reconfigurable Reflector Based Ultrasonic Waveguide for Temperature Measurement","authors":"Arun Valabhoju, Suresh Periyannan","doi":"10.1134/S1061830924603313","DOIUrl":"10.1134/S1061830924603313","url":null,"abstract":"An ultrasonic reconfigurable reflector technique was introduced in the waveguide sensor to monitor the temperature of the pipe surface. Researchers used mostly cylindrical wire waveguides to measure fluid level, rheology, and temperature. However, the strip waveguides have flat surfaces that can show a better coupling effect with ultrasonic (transducer) sources. Also, the strip sensor can lie/lay easily on the measurement region and have more surface contact. This sensor development considered the S0 wave mode in the thin strip as a pulse-echo approach using a single transducer at 0° orientation with the waveguide axis. We considered echogenic features (clamp-reflectors) to develop the distributed temperature sensors in the ultrasonic strip waveguide. Here, the reflector types “screw & clamp” were introduced to obtain the desired strength of amplitudes from each reflector which can be helpful in the signal’s peak tracking. We compress the waveguide at appropriate locations using a screw-clamp setup to obtain a suitable ultrasonic reflection without removing the material (notch reflector). We obtained change in time of flight (δTOF) between consequent reflectors at various temperatures and compared it with the co-located conventional thermocouple for calibrating the waveguide sensor. Then, we used the calibrated single-strip waveguide with a reconfigurable reflector to measure temperatures at multiple locations on the pipe surface. We performed multiple experimental trials to check for the sensors’ repeatability. The single-strip waveguide sensor developed comprises non-destructive reflectors that are easy to use, reconfigurable, durable, and cost-effective. Measuring the in-situ properties of any structure at various locations could be highly feasible.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 2","pages":"186 - 196"},"PeriodicalIF":0.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145164389","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

Preload Detection System Based on Ultrasonic Energy Transmission for Attached Joint Structures 基于超声能量传递的附着节点结构预紧力检测系统

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S106183092460309X

Guanbing Ma, Qi Wang, Maocheng Hong, Ruding Xia, Yue Zhao, Ming Li, Tao Song, Jun Zhang

{"title":"Preload Detection System Based on Ultrasonic Energy Transmission for Attached Joint Structures","authors":"Guanbing Ma, Qi Wang, Maocheng Hong, Ruding Xia, Yue Zhao, Ming Li, Tao Song, Jun Zhang","doi":"10.1134/S106183092460309X","DOIUrl":"10.1134/S106183092460309X","url":null,"abstract":"In the aerospace industry and nuclear power plants, bolt preload is a crucial metric for assessing the quality of installation and the state of service of the flange connection parts of pressure vessels. The primary technique for determining the preload force is the ultrasonic stress measurement method based on pulse time-of-flight. However, the current ultrasonic preload measuring approach is no longer applicable for unique bolted structures like pointed bolts and high acoustic attenuation bolts, as it is unable to receive the bolt end face echo. This work aims to address this issue by proposing a detection system based on interlayer ultrasonic energy transfer-based bolt preload measurement method. The ultrasonic energy transmission model of the sandwich’s rough interface is built using both classical contact theory and ultrasonic propagation theory. When paired with a finite element simulation, this model shows a linear relationship between the sandwich’s ultrasonic transmission signal energy and the bolt preload force. The relationship between the ultrasonic transmission energy and the bolt preload force under the ultrasonic frequency contact surface roughness and other factors was systematically investigated. A testing platform was set up to conduct the ultrasonic energy transmission test on the preload force of the bolt interlayer. According to the test results, there is a good linear relationship between the ultrasonic transmission signal energy and bolt preload obtained under various groups of parameters, R2 is greater than 0.97, and the bolt preload measurement error range for flange bolts is between –5.4% and 5.6%. These findings suggest that the method presented in this paper has a promising future.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 2","pages":"175 - 185"},"PeriodicalIF":0.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1134/S106183092460309X.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145164418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Infrared Thermography Detection of Defects in CFRP Based on a Time-Domain Nonlinear Regression Algorithm 基于时域非线性回归算法的CFRP缺陷红外热像检测

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830924603490

Chiwu Bu, Weiliang Bai, Xin Huang, Peng Chen, Runhong Shen, Rui Li, Guozeng Liu, Qingju Tang

{"title":"Infrared Thermography Detection of Defects in CFRP Based on a Time-Domain Nonlinear Regression Algorithm","authors":"Chiwu Bu, Weiliang Bai, Xin Huang, Peng Chen, Runhong Shen, Rui Li, Guozeng Liu, Qingju Tang","doi":"10.1134/S1061830924603490","DOIUrl":"10.1134/S1061830924603490","url":null,"abstract":"Carbon fiber reinforced polymer (CFRP) has been extensively utilized in the aerospace industry due to their light weight and high strength, however, they are susceptible to defects such as delamination and debonding during service. To enhance material safety, reliability and defect detection efficiency in infrared non-destructive testing (NDT), this study treats each pixel in the thermal image of the specimen surface as an independent entity. Temporal thermal wave signal features are extracted, and after non-dimensional processing, the features are mapped back to each pixel to reconstruct the characteristic distribution on the specimen surface, leading to the proposal of the dynamic thermal regression (DTR) algorithm. The DTR technology, along with the dynamic thermal tomography (DTT) and thermal signal reconstruction (TSR) techniques, were applied to the original infrared image sequences. The results demonstrate that applying these image processing techniques significantly enhances defect detection in CFRP. Furthermore, the DTR technique effectively reduces the acquisition time for infrared NDT image sequences, shortens the sequence length, and thereby improves the efficiency of infrared NDT.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 2","pages":"244 - 255"},"PeriodicalIF":0.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145164513","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

Research on Leakage Monitoring and Recognition Method of High-Pressure Hydrogen Valves 高压氢气阀泄漏监测与识别方法研究

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830924603283

Yi Qin, Zhe Yang, Zetian Kang, Qian Wu, Yuchen Wang, Anfeng Yu, Huan Liu, Yun Luo

{"title":"Research on Leakage Monitoring and Recognition Method of High-Pressure Hydrogen Valves","authors":"Yi Qin, Zhe Yang, Zetian Kang, Qian Wu, Yuchen Wang, Anfeng Yu, Huan Liu, Yun Luo","doi":"10.1134/S1061830924603283","DOIUrl":"10.1134/S1061830924603283","url":null,"abstract":"High-pressure hydrogen valves are subjected to the instantaneous impact of hydrogen flow and repeated start-stop action during service, and there is a potential risk of leakage. This paper investigates monitoring and identification of hydrogen valves leakage to ensure their operational reliability. Firstly, an acoustic signal monitoring system was built based on a high-pressure hydrogen gas-tightness test platform, and the time-domain feature of valves under different leakage conditions was analyzed. Secondly, the frequency-domain feature is extracted using a combination of variational modal decomposition and wavelet packet decomposition. Ultimately, the backward propagation network (BP) and convolutional neural network (CNN) are used to recognize patterns of acoustic signals, with the time-domain and frequency-domain parameters as feature inputs independently. The results show that the accuracy of BP and CNN networks based on frequency domain features has significantly improved, 93.33 and 91.67%, respectively. This paper obtained the feature extraction and pattern recognition method for hydrogen valves, which provides a reference for accurate and efficient recognition of the leakage condition of high-pressure hydrogen valves in the service process.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 2","pages":"151 - 163"},"PeriodicalIF":0.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145164417","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 2D Magnetostatics Inverse Problem for a Uniformly Magnetized Body 均匀磁化体的二维静磁反问题

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830925700020

V. V. Dyakin, O. V. Kudryashova, V. Ya. Raevskii

引用次数: 0

An Ultrasonic Signal Recognition Method for Roll Defects Based on C-GAN and CNN-Attention 基于C-GAN和CNN-Attention的轧辊缺陷超声信号识别方法

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830924603349

Jinhong Lian, Yinlong Zhu, Wei Chen, Ying Liu, Xiaoan Yan

{"title":"An Ultrasonic Signal Recognition Method for Roll Defects Based on C-GAN and CNN-Attention","authors":"Jinhong Lian, Yinlong Zhu, Wei Chen, Ying Liu, Xiaoan Yan","doi":"10.1134/S1061830924603349","DOIUrl":"10.1134/S1061830924603349","url":null,"abstract":"This paper proposes a roll defect recognition method based on C-GAN and CNN-Attention, addressing the challenges of limited data and low recognition accuracy in ultrasonic defect detection for rolls. Initially, an ultrasonic testing experimental system is employed to inspect artificially prepared roll defect samples, leading to the collection of actual defect data. Subsequently, a C-GAN data augmentation model is developed to learn the distribution patterns of various defects, generating high-quality new samples that align with the distribution of each defect type, thereby expanding the training dataset. Utilizing this augmented data, a convolutional neural network defect classification method that incorporates an attention mechanism is designed to further enhance prediction accuracy. By integrating an attention module to assign weights to each feature channel, improved feature representations are achieved, optimizing the learning mechanism of the CNN. The model attains a recognition accuracy of 95.83%, demonstrating the effectiveness of this method in roll defect recognition applications.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 2","pages":"197 - 208"},"PeriodicalIF":0.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145163914","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

Hysteresis Interference of Defect Fields 缺陷场的迟滞干涉

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830925700019

V. V. Pavlyuchenko, E. S. Doroshevich

引用次数: 0

Enhancing Deep Hole Defects Visibility in Ultrasonic Detection for Thick-Walled Polyethylene Pipes via Time-Frequency Energy Concentration 时频能量集中法提高厚壁聚乙烯管材超声检测中深孔缺陷可见性

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-06-10 DOI: 10.1134/S1061830924603374

Chaolei Chen, Huaishu Hou, Shiwei Zhang, Mingxu Su, Zhifan Zhao, Chaofei Jiao

{"title":"Enhancing Deep Hole Defects Visibility in Ultrasonic Detection for Thick-Walled Polyethylene Pipes via Time-Frequency Energy Concentration","authors":"Chaolei Chen, Huaishu Hou, Shiwei Zhang, Mingxu Su, Zhifan Zhao, Chaofei Jiao","doi":"10.1134/S1061830924603374","DOIUrl":"10.1134/S1061830924603374","url":null,"abstract":"Ultrasonic testing of thick-walled polyethylene pipes is challenged by energy loss, resulting in weak echo signals from deep defects. To enhance the detection of these weak signals, a time-frequency energy concentration method is presented. The fractional adaptive superlet transform combines multiple wavelet transform results with distinct bandwidths through geometric averaging, providing superior time-frequency analysis capabilities than single wavelet transforms. However, its time-frequency representation exhibits the issue of instantaneous frequency deviation. The proposed method addresses the issue via instantaneous frequency-embedding, leading to improved accuracy in instantaneous frequency estimation. Numerical signal analysis reveals higher accuracy in instantaneous frequency estimation using this method, compared to other time-frequency processing methods. When applied to detecting deep defects in thick-walled polyethylene pipes, the method shows an 18.9% increase in weak signal enhancement capability compared to the continuous wavelet transform. Finally, the results demonstrate the method’s accuracy in clarifying instantaneous frequency changes and enhancing instantaneous amplitudes of weak signals, offering a promising approach for the detection of deep defects in thick-walled polyethylene pipes.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 2","pages":"164 - 174"},"PeriodicalIF":0.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145163915","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

Application of Periodic Laser Heating and Phase-Sensitive Thermography for Thickness Gaging of Coatings 应用周期性激光加热和相敏热成像技术测量涂层厚度

IF 0.9 4区材料科学

Russian Journal of Nondestructive Testing Pub Date : 2025-04-21 DOI: 10.1134/S1061830924603325

A. G. Divin, Yu. A. Zakharov, D. Yu. Golovin, N. A. Karpova, A. I. Tyurin, A. A. Samodurov, S. V. Karpov, V. V. Rodaev, I. A. Zakharov

{"title":"Application of Periodic Laser Heating and Phase-Sensitive Thermography for Thickness Gaging of Coatings","authors":"A. G. Divin, Yu. A. Zakharov, D. Yu. Golovin, N. A. Karpova, A. I. Tyurin, A. A. Samodurov, S. V. Karpov, V. V. Rodaev, I. A. Zakharov","doi":"10.1134/S1061830924603325","DOIUrl":"10.1134/S1061830924603325","url":null,"abstract":"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.","PeriodicalId":764,"journal":{"name":"Russian Journal of Nondestructive Testing","volume":"61 1","pages":"115 - 124"},"PeriodicalIF":0.9,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852501","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