Research and Review Journal of Nondestructive Testing最新文献_第6页

Non-destructive testing of fiber-reinforced composites by terahertz method 纤维增强复合材料的太赫兹法无损检测

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28215

P. Hłosta, M. Strąg, W. Świderski

{"title":"Non-destructive testing of fiber-reinforced composites by terahertz method","authors":"P. Hłosta, M. Strąg, W. Świderski","doi":"10.58286/28215","DOIUrl":"https://doi.org/10.58286/28215","url":null,"abstract":"\u0000Fiber-reinforced composites are materials that are increasingly replacing metals in many construction solutions. Damage to the composite structure may occur both as a result of technological errors in the production phase and during operation as material fatigue or as a result of an impact by a foreign body. The specificity of defects that occur in fiberreinforced composites results in the development of non-destructive testing methods that enable the detection of these defects. One of these methods is the use of terahertz radiation. Terahertz radiation penetrates well through non-metallic materials. It can therefore be used for non-destructive testing, especially of composites reinforced with glass and aramid fibers. The terahertz band has been known for many years, but interest in the use of terahertz radiation in non-destructive testing has only recently emerged. This is due, among others, to the availability of sources of terahertz radiation of appropriate power enabling these tests. The radiation source is an important element of nondestructive testing with active methods that are most often used in this type of testing. In non-destructive testing, the terahertz radiation range from 100 GHz to 300 GHz is most often used. In this paper we present the results obtained using the transmission terahertz method.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"24 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":"114322118","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

Detection of defects initiation in weld joints 焊缝缺陷产生的检测

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28098

Pavel Mareš, J. Veselá

{"title":"Detection of defects initiation in weld joints","authors":"Pavel Mareš, J. Veselá","doi":"10.58286/28098","DOIUrl":"https://doi.org/10.58286/28098","url":null,"abstract":"\u0000Welded joints on various pipelines, especially steam pipelines of fossil power plants, are exposed to high pressure and temperature of steam during operation. The applied stress and temperature together with the chemical composition and microstructure of the material have a major influence on the damage growth in these joints. Growth of defects as a time-dependent event, the sensitivity of the material to damage due to stress temperature and others plays a major role. In the case of steam pipes of fossil power plants, this is mainly creep damage. Early detection of these defects, especially at their initial stage, can help in managing the service life and thereby reducing the costs for operation, both by minimizing unplanned shutdowns as well as by planning any repairs in time. The work is focused on the detection of defect indications, especially creep damage occurring in weld joints and heat-affected areas. The aim is to distinguish manufacturing defects of welded joints from indications of early crack growth by ultrasonic testing. Indications from manufacturing defects may also be detected during testing and, if detected, will be evaluated in the same way as defects that are primarily targeted by the testing techniques. Several different techniques were tested on samples cut from the operated steam pipeline systems and compared with the results of metallographic analyses on selected parts.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"20 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":"116509564","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

How the EU project “Online Microstructure Analytics” advances inline sensing of microstructure during steel manufacturing 欧盟“在线微观结构分析”项目如何推进钢铁制造过程中微观结构的在线感知

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28201

F. van den Berg, M. Aarnts, Haibing Yang, F. Fintelman, B. Ennis, L. Gillgren, D. Jorge-Badiola, A. Martínez-de-Guerenu, C. Davis, G. West, Lei Zhou, M. Jolfaei, A. Peyton, John W. Wilson, A. Volker, Q. Marina, A. Duijster, M. Malmström, A. Jansson, B. Hutchinson, C. Mocci, M. Vannucci, V. Colla, C. Reboud, A. Skarlatos, R. Miorelli, P. Lombard, O. Hubert, J. Taurines, I. Lobanova, S. Despréaux, S. Labbé, C. Celada-Casero

{"title":"How the EU project “Online Microstructure Analytics” advances inline sensing of microstructure during steel manufacturing","authors":"F. van den Berg, M. Aarnts, Haibing Yang, F. Fintelman, B. Ennis, L. Gillgren, D. Jorge-Badiola, A. Martínez-de-Guerenu, C. Davis, G. West, Lei Zhou, M. Jolfaei, A. Peyton, John W. Wilson, A. Volker, Q. Marina, A. Duijster, M. Malmström, A. Jansson, B. Hutchinson, C. Mocci, M. Vannucci, V. Colla, C. Reboud, A. Skarlatos, R. Miorelli, P. Lombard, O. Hubert, J. Taurines, I. Lobanova, S. Despréaux, S. Labbé, C. Celada-Casero","doi":"10.58286/28201","DOIUrl":"https://doi.org/10.58286/28201","url":null,"abstract":"\u0000Weight savings in mobility and transport are mandatory in order to reduce CO 2 emissions and energy consumption. The steel industry offers weight saving solutions by a growing portfolio of Advanced High Strength Steel (AHSS) products. AHSS owe their strength to their largely refined and complex microstructures, containing multiple metallurgical phases. Optimal control of the thermo-mechanical processing of AHSS requires inline sensors for real-time monitoring of evolution and consistency of microstructure and material properties. To coordinate and accelerate European development activities in this domain, the project ”Online Microstructure Analytics (OMA)” was established in 2019, constituting of a consortium of 14 specialised research organisations. The EU-funded OMA project, with a total budget exceeding 6 MEU, focuses on inline sensing techniques to monitor the consistency and homogeneity of microstructure, texture and mechanical properties for automotive steels and in particular for AHSS.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"22 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":"131794846","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

Advances in the implementation of a UT contactless inspection system in the manufacturing process of thermoplastic components for aeronautical use, within the framework of the H2020-DOMMINIO project. 在H2020-DOMMINIO项目框架内，在航空热塑性部件制造过程中实施UT非接触检测系统的进展。

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28106

R.C. Giacchetta, Ricardo González, David Sánchez, A. Morales, F. Ansedes, Eduardo Moreno

{"title":"Advances in the implementation of a UT contactless inspection system in the manufacturing process of thermoplastic components for aeronautical use, within the framework of the H2020-DOMMINIO project.","authors":"R.C. Giacchetta, Ricardo González, David Sánchez, A. Morales, F. Ansedes, Eduardo Moreno","doi":"10.58286/28106","DOIUrl":"https://doi.org/10.58286/28106","url":null,"abstract":"\u0000In recent decades, the aeronautical industry has undergone a drastic transformation in the manufacturing philosophy in response to the growth of aircraft production (by 60% in the last 10 years), due to the increase in passenger transport demand. Although the pandemic has contracted the sector 66% during the last years 2020-2021, it is expected to normalize by 2024. The transition to the use of more advanced composite materials, together with the increase in aircraft performance and the rate of productivity is a challenge. Also, the necessity to produce effective structures and components using ecological materials and technologies have been increased, with the consequence of reducing cost, weight and fuel consumption. The DOMMINIO project from the European H2020 program, aims to develop new integrated design methodologies and knowledge based on manufacturing and optimization for the production of new multifunctional fuselage parts. A new technology is applied manufacturing by Laser ATL (Automatic Tape Layout) technique, using the automated deposit of thermoplastic tapes on a mold. Additionally, the DOMMINIO project deals with ensuring the quality of the components during the manufacturing process by a novel non-destructive control based on Ultrasound contactless technologies. To this end, DASEL has developed non-contact transducers that are coupled to the technological process of layer deposition, performing a non-contact quality control. This paper presents the results of the first year of the project, emphasizing the detection of delamination or lack of consolidation in real time.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"28 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":"131881916","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

Wheel and axle defect detection based on deep learning 基于深度学习的轮轴缺陷检测

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28166

Jian ping Peng, Qian Zhang, Bo Zhao

{"title":"Wheel and axle defect detection based on deep learning","authors":"Jian ping Peng, Qian Zhang, Bo Zhao","doi":"10.58286/28166","DOIUrl":"https://doi.org/10.58286/28166","url":null,"abstract":"\u0000With technological innovations in the world of high-speed railways, railways have become an indispensable and important part of life. As a key part of the train, the safety of the wheels and axles cannot be ignored. Industry often uses non-destructive testing (NDT) methods, and because of the special structure of wheels and axles, we commonly use phased-array ultrasonic testing. However, the disadvantage is that ultrasonic inspection methods rely too much on the intuition of skilled workers and as the workload increases, a large amount of data is not used effectively, which can easily lead to safety hazards. To deal with these issues, an efficient detection method emerges as the times require. we collected ultrasound-based B-scan defect data for wheels and axles, by expert manual annotation to establish a database of various types of defects in wheels and axles of existing trains. By using the improved YOLO-v5-based algorithm for training validation and testing, improving the feature extraction layer and adding a small target detection layer for difficult defects. Finally, by adding an attention mechanism to improve the training accuracy and using active learning strategies for data enhancement to make it more applicable to ultrasound images, the experiments significantly improved detection efficiency and stability, with a high defect detection rate and a significantly decreased false alarm rate. The algorithm has good performance with laboratory data. The algorithm has good performance in laboratory data and can meet the application requirements in the actual wheel and axle inspection data, we tested more than 3000 different pictures which are all from the real data collected by ultrasonic testing, with the defect detection alarms reaching 100%, detection speed reaching real-time detection, and false alarms being controlled to within 2%. More importantly, with the self-upgraded of algorithm and new data collection, the detection efficiency will improve gradually.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"471 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":"132127375","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

Combining radar and ultrasound imaging for surface echo compensation and augmented visibility of interior structures in NDT applications 在无损检测应用中，结合雷达和超声成像进行表面回波补偿和增强内部结构可见性

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28094

I. Ullmann, J. Schür, M. Vossiek

{"title":"Combining radar and ultrasound imaging for surface echo compensation and augmented visibility of interior structures in NDT applications","authors":"I. Ullmann, J. Schür, M. Vossiek","doi":"10.58286/28094","DOIUrl":"https://doi.org/10.58286/28094","url":null,"abstract":"\u0000Millimeter-wave radar imaging is a promising technique in non-destructive testing. When a small material defect is located closely to the test object’s surface, the strong reflection caused by the air-material interface can overlap with the defect’s weak reflection and mask it. If the image resolution is not sufficient, the defect cannot be resolved and will not be recognizable in the reconstruction image. To solve this problem, surface echo compensation techniques have been invented. However, these techniques are usually restricted to planar surfaces, which for most applications is not the case. This article presents a technique for surface echo compensation of arbitrarily shaped objects. We propose to combine radar and air-coupled ultrasound. Since aircoupled ultrasound is not able to penetrate solids, an air-coupled ultrasound imaging system is only able to detect the surface of a solid object. The idea of our proposed concept is to employ the ultrasound signal to compensate for the surface echo in the radar signal. The proposed method is based on the idea of using signals of equal wavelengths for both wave types and an amplitude calibration. Then, the resulting signals for radar and ultrasound are formally equal, which makes it possible to directly combine them numerically. That way, a modified radar image can be obtained which only contains the reflections from the inside and highlights interior defects.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"55 49","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134225859","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

Monitoring crack tip position in Cracked Lap Shear specimens subjected to fatigue loading 疲劳荷载作用下裂纹搭接剪切试样裂纹尖端位置的监测

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28219

M. Carboni, A. Panerai, L. M. Martulli, A. Bernasconi

引用次数: 0

Inspection benchmarking of Fiber Reinforced Polymers produced by Additive Manufacturing 增材制造技术生产的纤维增强聚合物的检测基准

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28175

M. Machado, Henrique V. Silva, João Pazadinhas, M. Carvalho, Telmo G. Santos

{"title":"Inspection benchmarking of Fiber Reinforced Polymers produced by Additive Manufacturing","authors":"M. Machado, Henrique V. Silva, João Pazadinhas, M. Carvalho, Telmo G. Santos","doi":"10.58286/28175","DOIUrl":"https://doi.org/10.58286/28175","url":null,"abstract":"\u0000The production of Polymer Matrix Composites (PMCs) through Additive Manufacturing (AM) presents new defects, and the detection of these is crucial for proper functioning. Non-destructive testing (NDT) techniques such as terahertz (THz), air-coupled ultrasounds, and active thermography are fast, automatable, non-invasive, and noncontact inspection methods. The aim of this study is to investigate the use of NDT techniques for detecting defects in PMCs produced by AM. Six samples were produced using polylactic acid (PLA) as the base material and reinforced with continuous fibers of Kevlar, glass, and carbon. Two types of samples were created: one with a full-thickness reinforcement defect in a specific area and the other with a partial reinforcement defect, with a layer of fibers missing in the same area. The samples were then tested using three NDT techniques: THz, non-contact ultrasonic, and active thermography. The results showed that THz was only able to detect the defect in the carbon fiber sample with full-thickness reinforcement, ultrasonic testing was able to detect the defects in Kevlar and carbon fiber samples with missing three layers of fibers, and active thermography was the most reliable technique, detecting all samples with missing three layers of fibers as well as partial reinforcement defects.\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":"125771730","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

State of Aging Classification of Modified-HP Steel Tubes by Eddy Current Test Applying Machine Learning 应用机器学习的涡流试验对改性高压钢管的老化状态进行分类

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28080

Ana Carolina Pereira Soares Brandão, Ana Beatriz Dantas Fonseca, Iane de Araújo Soares, Luiz Henrique de Almeida, Clara Johanna Pacheco, G. Pereira

{"title":"State of Aging Classification of Modified-HP Steel Tubes by Eddy Current Test Applying Machine Learning","authors":"Ana Carolina Pereira Soares Brandão, Ana Beatriz Dantas Fonseca, Iane de Araújo Soares, Luiz Henrique de Almeida, Clara Johanna Pacheco, G. Pereira","doi":"10.58286/28080","DOIUrl":"https://doi.org/10.58286/28080","url":null,"abstract":"\u0000In the petrochemical industry, steam reforming furnaces play a crucial role in large-scale hydrogen production. These furnaces are equipped with centrifugal cast HP-modified austenitic stainless-steel tubes, which are exposed to temperatures ranging from 600 to 1000ºC for extended periods. As a result, the wall temperature profile of these tubes exhibits a vertical gradient of distinct aging states, labelled as state I to VI in the literature, each characterized by specific microstructures. Given that the reformer tubes are expensive components of the furnace assembly, it is imperative to monitor their service life. Non-destructive testing is a vital tool for evaluating the structural integrity of industrial components. Hence, the objective of this study is to establish a real-time classification system for determining the aging states of HP-modified stainless-steel tubes using a non-destructive magnetic system and the machine learning technique Support Vector Machine (SVM). Two tubes, each measuring 12.6 meters in length, were removed from the same steam reforming furnace after 160,000 hours of service. The inspection was conducted using an eddy current hybrid probe adapted to an inspection vehicle, allowing for real-time data acquisition. The results demonstrated that the developed classification system was capable of accurately identifying the different aging states present along the studied tubes.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"31 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":"124808702","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

Deep learning algorithms for design of periodic structures and dispersion curves calculation 周期结构设计与色散曲线计算的深度学习算法

Research and Review Journal of Nondestructive Testing Pub Date : 2023-08-01 DOI: 10.58286/28162

Kseniia Barashok, Boris I, Jaesun Lee

{"title":"Deep learning algorithms for design of periodic structures and dispersion curves calculation","authors":"Kseniia Barashok, Boris I, Jaesun Lee","doi":"10.58286/28162","DOIUrl":"https://doi.org/10.58286/28162","url":null,"abstract":"\u0000Periodic structure is useful and powerful tool for the wave manipulation. The\u0000\u0000development of design and analysis of periodic structures using traditional methods\u0000\u0000(analysis of eigenfrequencies by the finite element method) takes quite a lot of time.\u0000\u0000Machine learning and deep learning algorithms can speed up the development and\u0000\u0000subsequent analysis of periodic structures. In this work, we consider a particular case of\u0000\u0000the propagation of torsional waves in cylindrical objects, the calculation of their\u0000\u0000dispersion curves, and methods for generating the design of a unit cell of periodic\u0000\u0000structure by a given bandgap configuration. To achieve this goal, autoencoders and\u0000\u0000diffusion models were used. A dataset of unit cell shapes and their dispersion curves\u0000\u0000were used as training data. First, the dispersion curves were analysed to form a bandgap\u0000\u0000configuration, which was then fed to the input of the neural network. The neural\u0000\u0000network generates unit cell shape as the output data. Information about dispersion\u0000\u0000curves is also very important for the analysis of periodic structures. To calculate the\u0000\u0000dispersion curves, the possibility of using deep learning methods is considered - the\u0000\u0000problem is the opposite of the previous one. According to the given form, the neural\u0000\u0000network should calculate dispersion curves. The paper presents the results of applying\u0000\u0000this method for calculating dispersion curves.\u0000","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"143 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":"127296351","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