Research and Review Journal of Nondestructive Testing最新文献_第4页

Improvement of 3D-Active Thermography by using Artificial Intelligence 利用人工智能改进3d主动热成像技术

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28065

J. Rittmann, M. Kreutzbruck

{"title":"Improvement of 3D-Active Thermography by using Artificial Intelligence","authors":"J. Rittmann, M. Kreutzbruck","doi":"10.58286/28065","DOIUrl":"https://doi.org/10.58286/28065","url":null,"abstract":"\u0000For the one-dimensional case of heat propagation in active thermography the thickness of the investigated specimen can be directly reconstructed using known evaluation methods such as laser flash analysis or thermographic signal reconstruction and observation of a characteristic time. Concerning the multidimensional case diffusive effects have a strong impact on the heat propagation of the thermal wave, which leads to misinterpretations when evaluating the thickness especially at deep-lying edges and inhomogeneities in a specimen. The deeper a defect is located in the component, the more diffuse it is perceived in a change in surface temperature. Within this paper, heat flux simulations and real measurements of pulse thermography of different defect geometries are used to train a neural network for depth-resolved defect interpretation. The defect geometries are based on geometries of real impact damages in composites and were realistically obtained from a micromechanical fracture simulation. The neural network is based on an encoder-decoder approach where the temperature values of the cooling curve after a pulse-shaped excitation serve as input information. Segmentation is performed as a function of the backwall geometry. By training several thousand defect geometries using an encoder-decoder network, it was possible for the first time to directly infer the backwall geometry of a component without additional information about the component. Finally, it is shown how simulations can support the inversion of thermal waves for 3D-thermography of real measurements by an artificial intelligence system.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125284509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mimicking dam upstream slope scenarios in acrylic tanks for ultrasonic evaluation 在丙烯酸水箱中模拟大坝上游坡面情况进行超声波评价

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28224

T. C. Dourado, Alex Justen, Ericles de Jesus dos Santos, G. C. Morais, M. K. M. de Assis, Mariana Luiza Flavio, R. Mayworm, S. Miqueleti, A. Alvarenga, R. Costa-Felix

{"title":"Mimicking dam upstream slope scenarios in acrylic tanks for ultrasonic evaluation","authors":"T. C. Dourado, Alex Justen, Ericles de Jesus dos Santos, G. C. Morais, M. K. M. de Assis, Mariana Luiza Flavio, R. Mayworm, S. Miqueleti, A. Alvarenga, R. Costa-Felix","doi":"10.58286/28224","DOIUrl":"https://doi.org/10.58286/28224","url":null,"abstract":"\u0000Monitoring to support the integrity of structures immersed in water has been a challenge for dam engineers and other construction technicians for decades. In addition, it is known that the planning and execution of these activities are often linked to high costs and risk assessment. Non-destructive methods can act in these tasks with the production of useful information for a more optimized decision making. Ultrasound (US) is a wellknown tool that works with the emission and reception of wave signals. US stands out mainly for providing low radiation to operators, high resolution and flexibility in defining sensor arrays. Data acquisition can be performed even in immersed and tilted geometry environments. This article presents benchtop measurements from an approach focused on the microscale study of upstream slopes of earth dams. The model was developed to simulate the approximate geometry and composition of a dam slope. Traditional ultrasonic acquisition techniques are applied using immersion transducers. The investigations carried out in a model with dimensions of 30 cm, 30 cm and 100 cm, rip rap under 2H:1V inclination, central frequency of the transducer of 2.25 MHz and depth of water for measurement of up to 20 cm, demonstrated the ability to classify the ultrasonic reflection in contact between water and the different types of interfaces that mimic typical dam materials. Lessons learned from this microscale development should be tested in a controlled reservoir model before moving to field applications. The perspective of this study is to generate information capable of composing a database for machine learning and subsequently assist in decision-making for engineering solutions that act in maintenance, safety and predictive interventions in dam bodies.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128756320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated honeycomb detection during Impact Echo inspections in concrete using AI trained by simulation data 使用模拟数据训练的人工智能在混凝土冲击回波检测过程中自动检测蜂窝

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28149

Florian Dethof, S. Kessler

{"title":"Automated honeycomb detection during Impact Echo inspections in concrete using AI trained by simulation data","authors":"Florian Dethof, S. Kessler","doi":"10.58286/28149","DOIUrl":"https://doi.org/10.58286/28149","url":null,"abstract":"\u0000The Impact Echo method is well established in the civil engineering world of NDT for defect detection and thickness estimation in thick and highly reinforced concrete structures. For most applications of Impact Echo however, only the resonance frequency of the measured time signal is evaluated, meaning that most information is neglected. Here, artificial intelligence (AI) in the form of machine learning can help to classify signals based on multiple input parameters and therefore make use of the additional information stored in the measured signals. As the most powerful classification models need labelled input data, this usually marks a problem since labelled NDT data sets are rarely available for concrete structures. One solution to overcome this problem is the use of numerical simulations. In the past, numerical simulations showed that they are capable to produce realistic synthetic data for Impact Echo testing in concrete specimens. In this study, numerical simulations of Impact Echo measurements were conducted using the Elastodynamic Finite Integration technique (EFIT) to create training data for machine learning models. The measurements were carried out on two concrete specimens (17 cm and 50 cm thickness) containing honeycombs. Using the simulation data, multi-layer perceptron (MLPNN) and convolutional neural networks (CNN) are trained and tested on measured data from each specimen for performance. Results showed that an accurate honeycomb detection using machine learning was only possible in some cases with many false alarms arising near the specimen edges.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134531371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Physics-informed Neural Network for Pulsed Thermography- Based Defect Detection 基于脉冲热成像的缺陷检测的物理信息神经网络

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28158

tung-Yu Hsiao, Y. Yao

{"title":"A Physics-informed Neural Network for Pulsed Thermography- Based Defect Detection","authors":"tung-Yu Hsiao, Y. Yao","doi":"10.58286/28158","DOIUrl":"https://doi.org/10.58286/28158","url":null,"abstract":"\u0000The non-destructive testing technique of pulsed thermography has been widely used in materials to detect defects due to its low cost, large detection area, and rapid implementation. After conducting experiments, data processing is often necessary to reduce the influences of noise and non-uniform backgrounds and highlight defect information. However, during the analysis, physical information is usually ignored. In addition to thermographic data analysis, numerical simulations are also popular for analytical studies based on physical information, but they don’t fully utilize the experimental data. To address this, a new method was proposed using a physics-informed neural network (PINN) for thermographic data processing. PINN combines the prediction capabilities of deep neural networks with physical laws presented as partial differential equations and boundary conditions, allowing for both experimental data and physics information to be utilized in modelling. In pulsed thermography, the heat transfer is governed by Fourier's law of heat conduction in a three-dimensional system. However, there is a lack of temperature measurements in the depth direction. The proposed method solves this problem by using collocation points generated from Latin hypercube sampling. The PINN model provides a good estimation of the backgrounds in the thermograms, and the features of surface/subsurface defects are highlighted by subtracting the estimated backgrounds from the original thermograms. In the case study, the performance of the proposed method was found to be effective.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133892380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 formation processes of informative features in eddy current probes with pulsed excitation mode 脉冲激励模式涡流探头信息特征的形成过程分析

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28086

I. Lysenko, Y. Kuts, V. Uchanin, A. Protasov

{"title":"Analysis of formation processes of informative features in eddy current probes with pulsed excitation mode","authors":"I. Lysenko, Y. Kuts, V. Uchanin, A. Protasov","doi":"10.58286/28086","DOIUrl":"https://doi.org/10.58286/28086","url":null,"abstract":"\u0000The modern pulsed eddy current (EC) technique for flaw detection in structure inspections of aircraft and automotive elements, or other responsible constructions is typically carried out in aperiodic mode. At the same time, the unstable characteristic points of the EC signal usually used as informative parameters can restrict the potential of this excitation mode due to influence measurement errors. The article considers an application of the pulsed EC method of NDT based on the oscillatory mode. To obtain the conditions concerned with different modes of EC probe response oscillations, an equivalent scheme of the “testing object – EC probe” system was developed. The conditions represent the signal formation process and allow analyzing it for impedance and differential probes. The obtained mathematical model of the probe signals allowed for the dependence of proposed signal parameters on the characteristics of the testing object to be evaluated due to simulation. According to this, the frequency and attenuation coefficient of natural oscillations are proposed as the informative parameters. Also, the simulation results are used for developing enhanced algorithmic software for determining and analyzing the EC signals. The proposed informative parameters are experimentally investigated using a set of specimens. The obtained experimental and simulation results are correlated and it confirms the possibility of the proposed methodology to enhance the inspection procedures related to the specimen’s parameters measurements as well as the detected defect sizing.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128599250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A study on the wave propagation on weld joints by the use of feature-guided wave mixing 基于特征导波混频的焊接接头波传播研究

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28151

Jaesun Lee, Aslam Mohammed

{"title":"A study on the wave propagation on weld joints by the use of feature-guided wave mixing","authors":"Jaesun Lee, Aslam Mohammed","doi":"10.58286/28151","DOIUrl":"https://doi.org/10.58286/28151","url":null,"abstract":"\u0000The concentration of the wave energy around certain features such as bends, stiffeners, and welds in plate-like structures has been identified as feature-guided waves (FGW). In practice, these features can be useful for assessing defects in or near them. The propagation characteristics of FGW propagating along a feature such as a welded joint have been extensively studied. However, most of them are based on the linear acoustic response of materials that generally results in the amplitude and phase variations of the input signal. Compared to linear methods, nonlinear ultrasonic techniques have shown to be effective in characterizing the microstructural changes in engineering materials. In this paper, a wave mixing method is employed to investigate the nonlinear acoustic response of FGWs propagating in a welded joint. The dispersion characteristics of weldguided modes are first revealed via the eigenfrequency analysis of an unbounded welded plate by using the finite element method. The nonlinear response of FWGs is studied through 3D finite element (FE) simulations. A pair of a weld-guided modes of different frequencies are identified and allowed to mix within the welded joint to generate second-order harmonic waves. The current study reveals that the mixing of FGWs could be effectively used for the evaluation of material nonlinearity in welded joints.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117149769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

THz computed tomography for non-destructive testing 用于无损检测的太赫兹计算机断层扫描

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28225

Peter Fosodeder, M. Pfleger, S. van Frank, C. Rankl

引用次数: 0

Temperature-Controlled in-situ Tensile Tests of Polymer Tape with Single Particles 单颗粒聚合物带的温控原位拉伸试验

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28104

S. Heupl, J. Maurer, J. Kastner

引用次数: 0

A High-Speed Ultrasound Full-Matrix Capture Acquisition System for Robotic Weld Inspection 用于机器人焊缝检测的高速超声全矩阵捕获采集系统

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28163

M. Lewandowski, P. Karwat, Piotr Jarosik, Jakub Rozbicki, M. Walczak, Hanna Smach

{"title":"A High-Speed Ultrasound Full-Matrix Capture Acquisition System for Robotic Weld Inspection","authors":"M. Lewandowski, P. Karwat, Piotr Jarosik, Jakub Rozbicki, M. Walczak, Hanna Smach","doi":"10.58286/28163","DOIUrl":"https://doi.org/10.58286/28163","url":null,"abstract":"\u0000Phased-Array Ultrasonic Technique is traditionally used for the non-destructive inspection of welds and supported by industrial-grade inspection equipment. FullMatrix Capture (FMC) with Total Focusing Method (TFM) provide new capabilities and multimodal imaging, but available commercial scanners have limitations in acquisition speed (30–300MB/s) and reconstruction speed. Our goal was to develop a solution for FMC acquisition that can be applied to high-speed robotized weld scanning (speed of 100 mm/s with a resolution of 1 mm). For FMC acquisition, we have applied a portable programmable ultrasound research system us4R-lite™ (us4us Ltd., Poland) in a 64:256 channel configuration and standard angled 32-element Phased-Array probes. The system can acquire and store raw RF or demodulated I/Q data at a speed of 2–6 GB/s, enabling real-time FMC at high speed. Data can be stored on a PC during scanning and processed by a high-performance GPU. We have successfully tested our experimental setup while scanning flat-section welds with a motorized scanner at a speed approaching 100 mm/s. The acquisition and processing software developed uses Nvidia CUDA on GPU and can manage real-time storage and scanning. Next, we are planning to integrate the solution into an industrialgrade high-speed FMC acquisition system with embedded GPU processing.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127544468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic defect detection in fiber-reinforced polymer matrix composites using thermographic vision data 基于热成像视觉数据的纤维增强聚合物基复合材料缺陷自动检测

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28128

Gonçalves Maria S., M. Machado, Telmo G. Santos, Nuno Mendes

{"title":"Automatic defect detection in fiber-reinforced polymer matrix composites using thermographic vision data","authors":"Gonçalves Maria S., M. Machado, Telmo G. Santos, Nuno Mendes","doi":"10.58286/28128","DOIUrl":"https://doi.org/10.58286/28128","url":null,"abstract":"\u0000The detection of internal defects, not visible to the naked eye from the outside of\u0000\u0000materials, using non-destructive testing (NDT) are increasingly requested by industrial\u0000\u0000processes. This study proposes a novel methodology for acquisition and processing of\u0000\u0000images from a thermographic camera using computer vision methods to test composite\u0000\u0000materials made of a polymer matrix reinforced with glass, carbon, and kevlar fibers. The\u0000\u0000image is acquired while cooling the sample, following a suggested procedure. The\u0000\u0000processing methodology is divided into three steps, image pre-processing, image\u0000\u0000processing, and data post-processing. In image preprocessing, filters are applied to\u0000\u0000improve image quality, and methods are proposed to segment and identify the region of\u0000\u0000interest. In image processing, a blob analysis method is suggested for defect\u0000\u0000identification, isolation and characterization. A data analysis method is proposed for the\u0000\u0000post-processing step to characterize the defects identified in the previous step. Samples\u0000\u0000with known defects in terms of size, geometry, and location were used to test the\u0000\u0000developed system. The system showed high performance, achieving 98% accuracy, and\u0000\u0000suitability for defect detection larger than 0.5 mm in thickness and 600 mm2 in area. The\u0000\u0000experimental results showed that the algorithm did not detect any false positives, and that\u0000\u0000the type of reinforcement used in the analyzed samples had no influence on the results.\u0000\u0000On the other hand, the depth of the delaminations had an influence on the pixel intensity\u0000\u0000contrast of the defect region, and its instant of maximum contrast. The lesser the depth of\u0000\u0000the defects detected, the higher the value of their intensity and the shorter the instant of\u0000\u0000maximum contrast.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126946370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0