Ndt & E International最新文献

{"title":"Flaw sizing with plane wave imaging (PWI) – total focusing method (TFM) and deep learning for reactor pressure vessel","authors":"Gonçalo Sorger ,&nbsp;Iikka Virkkunen ,&nbsp;Christer Söderholm","doi":"10.1016/j.ndteint.2025.103332","DOIUrl":"10.1016/j.ndteint.2025.103332","url":null,"abstract":"<div><div>Developments in machine learning and deep convolutional networks (CNNs) have enabled automated assessment of nondestructive evaluation (NDE) data. Ultrasonic data is especially challenging for automated evaluation due to its complexity, multi-channel nature, and volume. Typical flaw signals have low signal to noise ratio, particularly diffraction signals critical for sizing. This study presents a proof-of-concept on the application of deep CNNs, specifically U-net and Swin-U-net, for flaw sizing in ultrasonic data from a nuclear test block with realistic flaw simulations. The segmentation CNNs extract flaw signals, enabling the identification of the deepest crack tip echo, mimicking human inspection. This mimics the process used by human inspectors. Two distinct CNNs are trained: U-net and a transformer-based Swin-U-net. A novel data reconstruction method is proposed that combines plane wave imaging (PWI), synthetic aperture focusing (SAFT) and total focusing method (TFM) to provide a unified volume reconstructed view. Both networks provide good segmentation performance allowing accurate sizing, despite noisy data and complex flaw signals.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103332"},"PeriodicalIF":4.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of passive intermodulation test for detecting corrosion in reinforcing bars","authors":"Sangho Lee ,&nbsp;Joo-Hyung Lee ,&nbsp;Changbin Joh ,&nbsp;Jae-Hyun Park ,&nbsp;Imjong Kwahk","doi":"10.1016/j.ndteint.2025.103333","DOIUrl":"10.1016/j.ndteint.2025.103333","url":null,"abstract":"<div><div>The passive intermodulation (PIM) test is a nondestructive test utilizing the nonlinear reflections of electromagnetic (EM) waves to identify material deterioration. This study explored the feasibility of the PIM test for detecting corrosion in reinforced concrete (RC) structures. First, the principle of the PIM was explained, and the devised PIM test equipment was described. Subsequently, the PIM test was performed on rebar, plain concrete, and RC specimens with various corrosion degrees. The results indicated that plain concrete generated large PIM signals, attributed to a nonuniform permittivity distribution, whereas the rebar specimens exhibited small or no PIM signals, resulting from relatively linear reflections. The RC specimens exhibited smaller PIM signals than plain concrete, suggesting that the rebar inside the concrete reduced the PIM signals by linearly reflecting a part of EM waves. Rebar corrosion further reduced the PIM signals owing to the scattering of EM waves. Therefore, rebar corrosion can be identified through smaller PIM signals compared with the surrounding region. Furthermore, the effect of rebar contact nonlinearity on the PIM signals was investigated using contacted rebars. The results indicated that corrosion reduced the PIM signals even with the contacted rebars. Therefore, the PIM test is feasible for detecting rebar corrosion.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103333"},"PeriodicalIF":4.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-quality, low-quantity: A data-centric approach to deep learning performance optimization in digital X-Ray radiography","authors":"Bata Hena ,&nbsp;Ziang Wei ,&nbsp;Clemente Ibarra-Castanedo ,&nbsp;Xavier Maldague","doi":"10.1016/j.ndteint.2025.103327","DOIUrl":"10.1016/j.ndteint.2025.103327","url":null,"abstract":"<div><div>The accuracy of identifying defects using specialized deep learning models can be affected by the circumstances in which the training data is curated. This is especially evident in digital X-ray radiography, where the depiction of flaws is significantly impacted by the exposure conditions. This study examines the effect of curating high-quality data on deep learning models. The variation in contrast-to-noise ratio (CNR), which is a crucial metric of image quality between features of interest and an adjacent normal background, has been found to be a key factor in model generalization in digital X-ray radiography applications. By making systematic alterations to exposure conditions during data curation, it was possible to obtain several representations of flaws in each test component with varying contrast-to-noise ratios (CNR) in the resultant radiographs. To evaluate the efficacy of the model under various conditions, two distinct datasets were curated. Dataset 1 was obtained by acquiring images with a consistent exposure setting on 140 test samples. The samples contained 4 morphologically distinct classes of flat bottom holes with seven different depths and sizes. The contrast-to-noise ratio (CNR) representations of flaws in this dataset can be attributed only to differences in depth in Dataset 1. Additionally, Dataset 2 was curated with an expanded range of CNR values by methodically adjusting exposure settings during image acquisitions. Hence, only 42 % of the test pieces from Dataset 1, which had three distinct depths of flat bottom holes, were used. Each of the two datasets was used to separately train YOLOv8 for instance segmentation and U-net for multi-class semantic segmentation. Each model was trained under the same conditions, and their performances were assessed using test sets from both dataset groups. The model trained on Dataset 1 exhibited a notable decline in performance when evaluated on test sets from Dataset 2, suggesting a lack of generalization ability. Conversely, the model that was trained using Dataset 2 consistently achieved high accuracy on both test sets, demonstrating impressive performance and successful generalization. This work shows that the generalization abilities of deep learning models may be improved by varying the contrast-to-noise ratio (CNR) of features in the training data. This finding paves the way for practical applications in digital X-ray radiography.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103327"},"PeriodicalIF":4.1,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal damage detection in FRP-strengthened reinforced concrete structures using ultrasonic guided waves","authors":"Yuqiao Cao ,&nbsp;Chang Jiang ,&nbsp;Ching Tai Ng ,&nbsp;Scott T. Smith","doi":"10.1016/j.ndteint.2025.103329","DOIUrl":"10.1016/j.ndteint.2025.103329","url":null,"abstract":"<div><div>This paper presents a study on the application of guided waves for detecting early-stage thermal damage in concrete structures strengthened with externally bonded fibre-reinforced polymer (FRP) composite plates. A theoretical model is firstly introduced, which includes both linear and nonlinear elastic coefficients in order to describe the material properties and behaviour of FRP plates. Thermal damage in turn is simulated by increasing the nonlinear elastic coefficients while a nonlinear parameter is proposed to quantify the extent of thermal damage. A user-defined subroutine is then presented for a three-dimensional (3D) finite element model that has the capability to simulate wave propagation behaviour across various frequencies. Experimental investigations are then reported on a carbon FRP (CFRP)-strengthened concrete beam, where thermal damage is induced by heating a specific area of the CFRP surface using a radiant heater. The sensitivity of the proposed nonlinear parameter for detecting various levels of the thermal damage is experimentally demonstrated. The study validates and demonstrates the reliability and sensitivity of the nonlinear guided wave method for early-stage detection of thermal damage in FRP-strengthened concrete structures.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103329"},"PeriodicalIF":4.1,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative evaluation of interfacial layer properties in bimetallic composite circular tubes using bounded ultrasonic beam scattering methodology","authors":"Jiangcheng Cai,&nbsp;Mingxi Deng","doi":"10.1016/j.ndteint.2025.103330","DOIUrl":"10.1016/j.ndteint.2025.103330","url":null,"abstract":"<div><div>Bimetallic composite circular tubes are widely acknowledged as promising candidates for future applications in pipeline engineering, owing to their blend of high performance, lightweight properties, and cost-effectiveness. However, during the engineering application of bimetallic composite circular tubes, the interface state between the cladding and substrate tubes undergoes changes. This paper presents a novel ultrasonic detection methodology for quantitatively assessing interfacial layer mechanical properties in bimetallic composite circular tubes. Our approach unveils distinct scattering patterns displayed by a bounded ultrasonic beam when interacting with these composite tubes featuring interfaces. Through finite element simulations and experimental measurements, we illustrate that when the bounded ultrasonic beam impinges obliquely upon the composite tube at a specific critical angle, the sound pressure amplitude of the scattered field shows significant variations corresponding to different levels of mechanical properties of the adhesive layer. In contrast, minor changes are observed at non-critical incident angles. Our method demonstrates remarkable effectiveness in detecting the mechanical properties of the adhesive layer. Compared to conventional ultrasonic inspection techniques, our approach provides exceptional sensitivity and stability in quantitatively evaluating the changes of interfacial layer properties, thus representing a valuable addition to non-destructive testing methods for composite structures.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103330"},"PeriodicalIF":4.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatigue life prediction for CFRP laminates using multi-mode Lamb wave velocity and Bayesian model selection","authors":"Lingyao Cen,&nbsp;Chongcong Tao,&nbsp;Chao Zhang,&nbsp;Hongli Ji,&nbsp;Jinhao Qiu","doi":"10.1016/j.ndteint.2025.103326","DOIUrl":"10.1016/j.ndteint.2025.103326","url":null,"abstract":"<div><div>This paper proposed a new approach for fatigue life prediction of carbon fiber reinforced polymer (CFRP) laminates using Bayesian model selection and multi-mode Lamb wave velocity. It is aimed to overcome the difficulties of large dispersity observed when testing of the material, caused by both complex damage mechanisms and fluctuation of data measurement due to the high damping property of CFRP. Specifically, both S₀ and A₀ mode Lamb wave velocities were recorded during a controlled tensile fatigue experiment under various load severities. Considering the possible underlying damage mechanisms, two stiffness degradation models are employed to describe the evolution trend of the collected velocity data of the two modes, respectively, forming effectively four sub models. Then Bayesian evidence is calculated by nested sampling (NS) algorithm to evaluate the strength of each sub model, the sub model with the strongest evidence is selected, the significance of which against other unselected sub models is also evaluated by Jeffrey's scale. Based on this, the fatigue life is predicted using the selected sub model, which shows good accuracy and consistency, and the effectiveness of model selection with multi-mode Lamb wave velocity is validated through a comparison between the results. Finally, a ‘most conservative’ strategy is also tested and compared for the safety requirement in practical application.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103326"},"PeriodicalIF":4.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rail crack size measurement based on magneto-optical imaging in multi-layer lift-off","authors":"Junwei He ,&nbsp;Guili Xu ,&nbsp;Junpu Wang ,&nbsp;Fuju Yan ,&nbsp;Jiuhao Ge ,&nbsp;Zhenyuan Xiao","doi":"10.1016/j.ndteint.2025.103323","DOIUrl":"10.1016/j.ndteint.2025.103323","url":null,"abstract":"<div><div>In the current method of crack size measurement using magnetic flux leakage detection technology, it is difficult to quantitatively analyze the detected magnetic flux leakage data due to the unstable character of the sensor lift-off position. To solve this problem, based on the forward inference of the leakage magnetic field of crack, a method of magnetic field acquisition in multi-layer lift-Off is proposed, and a magneto-optical imaging detection system is designed and built, so as to achieve high-precision measurement of rail crack parameters. Firstly, in the forward analysis, by borrowing the classical magnetic dipole theory, the relationship between the crack parameters and the peak value of the magnetic leakage field as well as its position is analyzed. Secondly, a magneto-optical image acquisition system with a lift-off interval of 10 <span><math><mrow><mi>μ</mi><mi>m</mi></mrow></math></span> is designed, which can effectively remove the influence of the light source system and magnetic domains on the imaging quality. Finally, a rail with standard processed 0.4 mm wide cracks is selected as experimental objects for crack measurement experiments. The crack width is obtained by fitting the peak gray value position curve under different lift-off, and the measurement accuracy reaches 25 <span><math><mrow><mi>μ</mi><mi>m</mi></mrow></math></span>, and the relative measurement error is found to be less than 7.5% in the comparison of several data sets. At the same time, in many groups of different crack depth measurement experiments, it is found that the measurement accuracy of crack depth measurement using the peak gray value is 0.5 mm.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103323"},"PeriodicalIF":4.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of selection matrix capture for micro defects laser ultrasound imaging using multi-parameter genetic algorithm","authors":"Long Chen ,&nbsp;Zenghua Liu ,&nbsp;Zhenhe Tang ,&nbsp;Jian Duan ,&nbsp;Yanping Zhu ,&nbsp;Zongjian Zhang ,&nbsp;Xiaoyu Liu ,&nbsp;Cunfu He","doi":"10.1016/j.ndteint.2025.103325","DOIUrl":"10.1016/j.ndteint.2025.103325","url":null,"abstract":"<div><div>Ultrasonic testing plays a crucial role in detecting early structural damage and identifying micro-defects, particularly in processes like additive manufacturing and welding. The full matrix capture (FMC) method, leveraging laser ultrasound technology, excels in imaging sub-millimeter micro defects. However, its extensive data acquisition time hinders real-time imaging. To address this, a selection matrix capture approach is adopted to reduce data collection and enhance detection speed. Specifically, a multi-parameter genetic algorithm (MPGA) is proposed to optimize sparse array layouts. This optimization is based on theoretical detection sensitivity means and standard deviations, evaluating array layout quality. The imaging method combined multi-scale principal component analysis with phase weighting techniques. Experiments on sub-millimeter defects, including side drilling holes (SDH), blind holes (BH), and spherical holes (SH), were conducted. Results showed that, compared to random and uniform sparsity, the genetic algorithm optimized sparse array provided superior imaging as sparsity decreased. Effective defect detection was achieved with only 5 %–20 % of full matrix data.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103325"},"PeriodicalIF":4.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of ultrasonic tomography in concrete using non-linear paths through bio-inspired algorithms","authors":"Vinícius Moura Giglio,&nbsp;Vladimir Guilherme Haach","doi":"10.1016/j.ndteint.2025.103324","DOIUrl":"10.1016/j.ndteint.2025.103324","url":null,"abstract":"<div><div>This paper aims to challenge the conventional approach of ultrasonic computerized tomography in concrete structures by using bio-inspired algorithms (genetic algorithms and ant colony optimization) to determine non-linear wave paths for generating tomographic images. Numerical UPV tests were conducted in two phases followed by an experimental validation. Initially, all algorithms were used to determine the shortest paths of ultrasonic waves, considering a known velocity map in a continuous medium. The time of flight (TOF) and wave trajectories were analyzed by adjusting the parameters of the bio-inspired algorithms. In the subsequent phase, the algorithms were evaluated for their efficiency in generating tomographic images of concrete cross sections through an iterative path update process. An experimental specimen was constructed, and ultrasonic tests were conducted to validate the proposed approach. The results demonstrated that all evaluated methods could determine paths that were faster than a straight line. Moreover, they exhibited the capability to generate improved images with enhanced precision regarding particle size and location. This conclusion highlights the potential of using bio-inspired algorithms as a promising alternative for optimizing ultrasonic wave paths and enhancing the accuracy of tomographic imaging.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103324"},"PeriodicalIF":4.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-line detection of pouch foil damage in batteries during manufacturing using lamb waves","authors":"Patrick Swaschnig ,&nbsp;Johannes Kofler ,&nbsp;Reinhard Klambauer ,&nbsp;Alexander Bergmann","doi":"10.1016/j.ndteint.2025.103322","DOIUrl":"10.1016/j.ndteint.2025.103322","url":null,"abstract":"<div><div>This study presents a novel approach to detect damaged pouch foils in lithium-ion batteries by analyzing changes in their mechanical properties using Lamb waves. A contactless measurement system combining an electromagnetic acoustic transducer (EMAT) and a laser vibrometer was developed and tested during the back-end production process of batteries. Three data analysis methods – signal amplitude difference, time-of-flight (ToF) analysis, and root mean square error (RMSE) analysis – were evaluated. Proof-of-principle measurements showed that all three methods effectively detected damage in the absence of the back-end process, confirming that pouch foil damage changes the mechanical properties and thus the propagation of Lamb waves in a battery. This approach integrated into the production line could significantly improve the safety, reliability, and performance of lithium-ion batteries through real-time monitoring and quality control. Since the measurement system is contactless, it represents a practical and non-invasive solution for different stages of battery production.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"152 ","pages":"Article 103322"},"PeriodicalIF":4.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}