Ndt & E International最新文献

{"title":"Defect detection in wind turbine blades applying Convolutional Neural Networks to Ultrasonic Testing","authors":"Julen Mendikute ,&nbsp;Itsaso Carmona ,&nbsp;Iratxe Aizpurua ,&nbsp;Iñigo Bediaga ,&nbsp;Ivan Castro ,&nbsp;Lander Galdos ,&nbsp;Jose Luis Lanzagorta","doi":"10.1016/j.ndteint.2025.103359","DOIUrl":"10.1016/j.ndteint.2025.103359","url":null,"abstract":"<div><div>The significance of wind-turbine blade safety operation has risen in the context of recent advances in wind energy generation. In this context, Non-Destructive Inspection Technologies (NDT), in particular those derived from Ultrasonic Testing (UT) methods, have proven to be key. Non-destructive evaluation (NDE) analysis has traditionally been performed by a qualified inspector who interprets the acquired signal. However, the emerging digital revolution has brought with it many advances in Artificial Intelligence (AI) and has demonstrated its potential in the field of NDE. AI has allowed to automate and improve traditional techniques in the tasks of data pre-processing, defect detection, defect characterization, and property measurement. Moreover, it has proven to be highly valuable in situations where it is not possible to apply traditional gate methods.</div><div>In this paper, the feasibility of using Deep Learning (DL) techniques for the detection of defects in wind-turbine blades (in the Cap zone and in the Cap-Web zone) is analyzed. For this purpose, supervised learning techniques have been used and three case studies were analyzed: two-class classifications for Cap zone, two-class classifications for Cap-Web zone, and four-class classifications have been performed. Several Convolutional Neural Network (CNN) architectures have been proposed, reaching 90% accuracy in all three case studies. These results lay the groundwork for the initial steps in applying AI techniques during the automated inspection of complex wind blade components.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"154 ","pages":"Article 103359"},"PeriodicalIF":4.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550433","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":"Nondestructive characterization of contaminant-induced material softening in epoxy polymers using nonlinear ultrasonic measurements","authors":"Do-Kyung Pyun ,&nbsp;Daniel J. Barnard ,&nbsp;Leonard J. Bond","doi":"10.1016/j.ndteint.2025.103364","DOIUrl":"10.1016/j.ndteint.2025.103364","url":null,"abstract":"<div><div>Epoxy polymer-based materials are widely used in structural assemblies due to their efficient and robust bonding capabilities. Nondestructive testing tools are needed to assess joint quality, and ideally strength, as contaminants, and some other defects, introduced during the manufacturing process can potentially cause material softening of the epoxy, leading to the degradation of the structural integrity of the bonded components. The application of the nonlinear response with ultrasonic methods used to characterize the epoxy material itself has been underexplored. This study investigates the use of an ultrasonic second-harmonic generation (SHG) method to characterize contaminant-induced material softening in epoxy polymers, with the contaminant being a release agent. The nonlinearity parameter associated with SHG was measured with varying contamination levels. To validate the effectiveness of the SHG method, nonlinear resonant ultrasonic spectroscopy (NRUS) was employed to independently assess the variation in material softening with the increase of contamination levels. Additionally, tensile testing was conducted on contaminated samples to establish a correlation between mechanical strength and the nonlinear parameter related to the degradation due to the material softening. This study demonstrated that the SHG technique is a promising nondestructive evaluation method for detecting contaminant-induced degradation in epoxy materials.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103364"},"PeriodicalIF":4.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535052","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":"A physics-informed clustering approach for ultrasonics-based nondestructive evaluation","authors":"Michail Skiadopoulos ,&nbsp;Evan P. Bozek ,&nbsp;Lalith Sai Srinivas Pillarisetti ,&nbsp;Daniel Kifer ,&nbsp;Parisa Shokouhi","doi":"10.1016/j.ndteint.2025.103362","DOIUrl":"10.1016/j.ndteint.2025.103362","url":null,"abstract":"<div><div>We propose a physics-informed clustering (PIC) algorithm tailored for ultrasonic non-destructive evaluation. Ultrasonic pulse-echo testing is used to measure the wave speed and wave amplitude decay of additively manufactured AlSi10Mg samples with programmatically induced pores and varying total volumetric porosities. The standard k-means clustering algorithm is coupled with the Independent Scattering Approximation (ISA) model to group together samples of similar porosity based on their ultrasonic response. The performance of the proposed PIC algorithm across varying seeds and numbers of clusters is compared to that of the standard k-means algorithm with random and k-means++ initializations. We demonstrate that the proposed PIC algorithm yields a more favourable clustering in terms of Pearson correlation coefficient and mean squared error given the ground-truth porosity labels. Our case study suggests that using a physics equation to inform a clustering algorithm can improve the clustering outcome.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"154 ","pages":"Article 103362"},"PeriodicalIF":4.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550435","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-service fatigue crack monitoring through baseline-free automated detection and physics-informed neural network quantification","authors":"Yuhang Pan,&nbsp;Zahra Sharif Khodaei,&nbsp;Ferri M.H. Aliabadi","doi":"10.1016/j.ndteint.2025.103360","DOIUrl":"10.1016/j.ndteint.2025.103360","url":null,"abstract":"<div><div>Online monitoring and quantification of fatigue cracks are essential for ensuring engineering structural integrity. Current structural health monitoring (SHM) methods, which have demonstrated potential to be applicable in service are either baseline or can only be applied on ground, which increases maintenance costs and risks of undetected rapid crack propagation. This paper proposes a reliable in-service method for online crack detection and growth assessment, providing early warning for maintenance. This novel approach extracts the third harmonic parameter <span><math><msup><mrow><mover><mrow><mi>γ</mi></mrow><mrow><mo>ˆ</mo></mrow></mover></mrow><mrow><mo>′</mo></mrow></msup></math></span>, defined as the ratio of the fundamental frequency amplitude (<span><math><msub><mrow><mi>A</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>) to the cube of the third harmonic amplitude (<span><math><msub><mrow><mi>A</mi></mrow><mrow><mn>3</mn></mrow></msub></math></span>), from the fatigue response. A dynamic piecewise linear (DPL) method is then employed for automatic online crack detection. Results from four specimens demonstrate the method’s capability for real-time detection of cracks below 2 mm during operation. Additionally, a physics-informed Long Short-Term Memory (PI-LSTM) model is developed to quantify the crack online, achieving an average RMSE of 0.498 mm on six datasets, outperforming traditional methods like pure LSTM and Paris’ Law with RMSE values of 3.205 mm and 3.641 mm, respectively. This study provides a cost-effective, reliable solution for in-service crack monitoring using external excitation signals, enhancing structural maintenance and safety.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103360"},"PeriodicalIF":4.1,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520973","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":"A comprehensive evaluation of the low-velocity impact behaviour of intraply hybrid flax/basalt composites using infrared thermography and terahertz time-domain spectroscopy techniques","authors":"Pengfei Zhu ,&nbsp;Hai Zhang ,&nbsp;Stefano Sfarra ,&nbsp;Fabrizio Sarasini ,&nbsp;Rubén Usamentiaga ,&nbsp;Gunther Steenackers ,&nbsp;Clemente Ibarra-Castanedo ,&nbsp;Xavier Maldague","doi":"10.1016/j.ndteint.2025.103361","DOIUrl":"10.1016/j.ndteint.2025.103361","url":null,"abstract":"<div><div>Low-velocity impacts severely jeopardize the structural reliability of polymer composites. In view of this, a thorough evaluation of the impact damage of the polypropylene (PP) composites reinforced with an ecofriendly intraply flax/basalt hybrid fabric was performed based on infrared thermography (including pulsed thermography, linear scanning thermography) and terahertz time-domain spectroscopy (THz-TDS) techniques. However, the main problem is the lack of multi-source fusion technique regarding more than two sensors, and the discussions regarding homologous fusion (pulsed thermography and linear scanning thermography), and non-homologous fusion (infrared thermography and THz-TDS). In this work, a comprehensive evaluation for the impact resistance of hybrid polymer composites was conducted, including detecting the uneven resin distribution and exploring new multi-sources fusion strategy. The experimental results demonstrate the superior capability of multi-source fusion techniques.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"154 ","pages":"Article 103361"},"PeriodicalIF":4.1,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550434","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":"Predictive probability of detection curves for ultrasonic testing","authors":"Ana E. Menéndez Orellana,&nbsp;Alexander Mendler,&nbsp;Simon Schmid,&nbsp;Christian U. Grosse","doi":"10.1016/j.ndteint.2025.103346","DOIUrl":"10.1016/j.ndteint.2025.103346","url":null,"abstract":"<div><div>The probability of detection (POD) is one of the most meaningful ways to quantify the detectability of damage, because it considers the statistical variability in the measurements. Predictive probability of detection (P-POD) curves are particularly efficient, as they generate POD curves based on a series of measurements from undamaged specimens, without having to run a series of destructive tests. P-POD methods are model-assisted, but instead of generating synthetic data, a sensitivity matrix is extracted from the model, and the measurement uncertainties are quantified based on experimental tests. However, so far, they have only been applied to global structural health monitoring applications. This paper sets out to apply the P-POD method to ultrasonic testing for the first time, and to experimentally validate the predictions for contact-based and air-coupled measurements. For that purpose, a contact ultrasound study is carried out, where changes of circular reflectors from their nominal values are evaluated in a polyamide cuboid based on the maximum reflected wave amplitude. Moreover, an air-coupled ultrasonic test is performed to determine thickness changes of a carbon fiber-reinforced polymer plate based on time-of-flight considerations. In both cases, the predicted POD is compared with empirical tests. The results show that the P-POD accurately predicts the POD with very small absolute deviations between predicted and actual POD. Since P-POD methods require analytical models that relate measured damage indicators to material changes, a separate study is added to demonstrate how the model-based uncertainty can be quantified using confidence intervals, and how it can be distinguished from data-driven uncertainties. As mentioned above, the POD can be predicted based on undamaged specimens, and that is why the P-POD method is an appropriate tool to optimize user-defined signal processing parameters before scanning the objects. To demonstrate this, different onset pickers are analyzed in a comparative study, where the one based on the Akaike information criterion led to a POD up to 38% higher than other pickers.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103346"},"PeriodicalIF":4.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535054","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":"Material parameter inversion using cross-entropy optimization based on Lamb Wave dispersion spectra","authors":"Ruben Burger ,&nbsp;Markus Heilig ,&nbsp;Christian U. Grosse ,&nbsp;Datong Wu","doi":"10.1016/j.ndteint.2025.103345","DOIUrl":"10.1016/j.ndteint.2025.103345","url":null,"abstract":"<div><div>For plate-like structures, non-destructive testing using ultrasonic Lamb waves has found many applications as oscillation modes and dispersion properties depend directly on the elastic material parameters. However, the dispersive nature of these modes complicates the analysis in the temporal–spatial domain. Instead, the frequency–wavenumber domain has proven advantageous because it allows the separation of simultaneously excited modes. Inversion of dispersion information to determine material properties is still a matter of research.</div><div>This paper proposes an algorithm based on the cross-entropy method which has been proven successful for many challenging optimization problems. This algorithm is used to determine the elastic properties (specific Lamé parameters) and the layer thickness of isotropic samples directly from the dispersion data of Lamb waves. This allows a full characterization of the elastic properties of the material in the case of known density. A cost function is developed that works directly on the raw dispersion data, requiring no thresholding or mode detection. The convergence of this method is shown to be wide with parameter search ranges of 300% or more.</div><div>The properties of the cost function were investigated by parameter study. The algorithm is evaluated through finite element simulations of Lamb wave propagation in three different isotropic materials. The findings indicate an average error of less than 1%. Measurement data for four samples (two steel plates; fused silica and lithium niobate wafers) show a strong correlation with literature values for the elastic parameters. The estimated thicknesses align with the measured values within the <span><math><mrow><mn>5</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span> and are in agreement with literature values.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103345"},"PeriodicalIF":4.1,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465289","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":"Deep learning meta architecture to detect spatially coherent coarse grain regions in ultrasonic data","authors":"Frederik Elischberger ,&nbsp;Xiaoyi Jiang","doi":"10.1016/j.ndteint.2025.103342","DOIUrl":"10.1016/j.ndteint.2025.103342","url":null,"abstract":"<div><div>This study introduces a novel methodology for detecting coarse grain volumina in ultrasonic data. The approach is based on the premise that the grain structure in metals produces ultrasonic grain noise, which can then be utilized to extract information about the grain structure. To achieve the detection of coarse grain fully embedded in finer grain material, three distinct deep learning models based on convolutional neural networks, recurrent neural networks and transformers, all derived from a shared meta architecture, were implemented and trained using ultrasonic Full-A-scan data. The proposed method was applied to a substantial dataset of synthetically manufactured coarse grain volumina, collected using a conventional single probe ultrasonic immersion system. Additionally, two baseline approaches were implemented and compared against the deep learning methods for experimental evaluation. The uncertainty of the deep learning approach was quantified using the model agnostic Monte Carlo Dropout technique, enabling the classification of predictions into high- and low-confidence categories. This research highlights the potential of deep learning in enhancing safety-critical systems and emphasizes the necessity for explainability in such domains.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103342"},"PeriodicalIF":4.1,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436770","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":"Resin curing monitoring method for steel epoxy sleeves using circumferential SH guided waves","authors":"Gaofeng Ma,&nbsp;Xiaokang Yin,&nbsp;Hongyuan Zhang,&nbsp;Yusheng Zhao,&nbsp;Longhui Ma,&nbsp;Ziheng Zhang,&nbsp;Xin'an Yuan,&nbsp;Wei Li","doi":"10.1016/j.ndteint.2025.103356","DOIUrl":"10.1016/j.ndteint.2025.103356","url":null,"abstract":"<div><div>Steel Epoxy Sleeves (SES) have been widely used for damage repair in oil and gas pipelines. During the resin injection process, accurate assessment of resin curing helps to determine the injection speed and the vacuum duration, thereby avoiding the formation of defects (such as bubbles and cavities) within the resin layer. In this paper, a resin curing monitoring method using Circumferential Shear Horizontal (CSH) guided waves is proposed. This method accurately assesses the resin's curing state by integrating the attenuation of the direct waves of CSH0 mode and the variation characteristics of the Reflected Waves from the Second Interface (RWSI). Periodic Permanent Magnet Electromagnetic Acoustic Transducers (PPM EMAT) were used to generate the CSH0 mode guided waves, and a monitoring experiment was conducted on the fabricated SES specimens for 11.5h. Three stages corresponding to the sol state, gel state, and glass state of the resin were characterized by the attenuation of CSH0 Wave. Additionally, RWSI emerged after 8h of curing, with both its amplitude and frequency gradually increasing, while its arrival time progressively advanced. The changes in RWSI facilitate a more detailed assessment of resin curing during the glassy state.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103356"},"PeriodicalIF":4.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419952","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":"An efficient method for output prediction of a surface eddy current probe in the presence of an axial fatigue crack in a conducting cylindrical rod","authors":"R. Azizpour,&nbsp;H. Behzadipour,&nbsp;S.H.H. Sadeghi","doi":"10.1016/j.ndteint.2025.103354","DOIUrl":"10.1016/j.ndteint.2025.103354","url":null,"abstract":"<div><div>This paper proposes an efficient method for analyzing the output signal of a surface eddy current probe during scanning a fatigue crack in a conductive cylindrical test specimen. The proposed method addresses all facets of typical eddy current testing practice, accounting for variations in metal conductivity and permeability, the arbitrary shape of the excitation coil and operating frequency. In this method, we initially employ the equivalence theorem to replace the crack opening with equivalent magnetic and electric current densities. Then, using appropriate dyadic Green's functions, the governing volume integral equations (VIEs) are formulated. Finally, the method of moments is utilized to solve the VIEs. This is done by expanding the unknown current densities in terms of dully selected basis functions of compatible with the problem, and hence, reducing the integral equations to a matrix equation. It is shown that the diffusion characteristics of the electromagnetic field in conductors enables one to adopt entire domain basis functions of polynomial form that remarkably reduces the computation burden in the formation of the resultant matrix equation. The validity and computational efficiency of the proposed method are verified through comparison of simulation results with experimental data and those obtained using a commercially available finite-element code.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"153 ","pages":"Article 103354"},"PeriodicalIF":4.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427702","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}