2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation最新文献_第7页

Elastic Properties of IN718 Fabricated via Laser Directed Energy Deposition (DED) 激光定向能沉积法制备IN718的弹性性能

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-74848

M. M. Rahman, G. Huanes-Alvan, H. Sahasrabudhe, S. Chakrapani

{"title":"Elastic Properties of IN718 Fabricated via Laser Directed Energy Deposition (DED)","authors":"M. M. Rahman, G. Huanes-Alvan, H. Sahasrabudhe, S. Chakrapani","doi":"10.1115/qnde2021-74848","DOIUrl":"https://doi.org/10.1115/qnde2021-74848","url":null,"abstract":"\u0000 Additive manufacturing of nickel based super alloys such as IN718 is highly desirable since they have a wide range of applications in high performance structures. Compared to conventional methods, laser processing allows for near net shaping of complex geometries. However, laser processing can result in very complex microstructures including meta-stable phases, grain boundary segregation of precipitates, dendritic grains and cellular microstructure. Describing elastic properties of such structures can be quite challenging due to these features. This article explores the use of resonant ultrasound spectroscopy (RUS) to characterize the elastic properties of IN718 samples fabricated using Laser Directed Energy Deposition (DED). For initial estimates of the elastic constants, ultrasonic wave (longitudinal and shear) velocities measured at 5MHz and 2.25 MHz respectively. The initial assumption was that the eventual structure will be orthotropic and the 9 elastic constants were determined using a combination of RUS and propagating wave experiments. A finite element approach was adopted to model this system and to minimize the values of elastic constants. The results seem to suggest that the secondary phases such as Laves will influence the eventual anisotropy of the bulk structure.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"439 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114353890","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

Shear Horizontal Guided Wave Corrosion Detection and Quantification in Pipes via Linear Scanning Magnetostrictive Transducers (MST) 基于线性扫描磁致伸缩传感器(MST)的管道剪切水平导波腐蚀检测与定量

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-75249

Xin Chen, S. Vinogradov, A. Cobb

{"title":"Shear Horizontal Guided Wave Corrosion Detection and Quantification in Pipes via Linear Scanning Magnetostrictive Transducers (MST)","authors":"Xin Chen, S. Vinogradov, A. Cobb","doi":"10.1115/qnde2021-75249","DOIUrl":"https://doi.org/10.1115/qnde2021-75249","url":null,"abstract":"\u0000 Shear horizontal (SH) guided waves are being widely considered as a promising tool for locating wall thinning corrosion in pipelike structures. One established approach to excite such waves in pipes is through the magnetostrictive transducers (MsT), which is an electromagnetic-based guided wave transducer that offers unique advantages over other transducer types. A common practice for fast screening of defects is using an automated probe positioning system. In this paper, we report the usage of a newly designed linear scanning MsT, where an iron cobalt (FeCo) strip of a predefined length wound with radio frequency (RF) coils is attached to the testing structure using shear wave couplants and a moving permanent magnet driven by a stepper motor is used to excite SH guided waves at predefined positions. In this fashion, manual manipulation of probe is minimized which significantly increases testing speed. The performance of the linear scanning MsT at corrosion inspection is evaluated experimentally by introducing “V” shaped gradual wall thinning patches of different depths and locations on a 406 mm outer diameter (OD) steel pipe with 10 mm wall thickness. The reflection and transmission amplitudes of SH modes, as well as indications from B-scan and synthetic aperture focusing technique (SAFT) images, are extracted for corrosion detection and quantification. Numerical modeling is also conducted to facilitate the understanding of SH waves interaction with defects.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116168715","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: 1

Stress Monitoring in a Real-Size Reinforced Concrete Column Using Torsional Resonance 基于扭转共振的实尺寸钢筋混凝土柱应力监测

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-73958

Agustin Spalvier, Santiago Laco, Gonzalo Cabrera, G. Cetrangolo

{"title":"Stress Monitoring in a Real-Size Reinforced Concrete Column Using Torsional Resonance","authors":"Agustin Spalvier, Santiago Laco, Gonzalo Cabrera, G. Cetrangolo","doi":"10.1115/qnde2021-73958","DOIUrl":"https://doi.org/10.1115/qnde2021-73958","url":null,"abstract":"\u0000 Nondestructive detection and monitoring of stress in concrete structural members is highly coveted. Yet, there are still no efficient techniques capable of achieving that goal. The leading approach towards this goal has been based on acoustoelasticity, the relationship between mechanical properties, such as mechanical wave speed, and the stress state of the solid medium. In concrete materials, acoustoelasticity has been increasingly studied, mainly using wave propagation phenomena, and usually in small samples of plain concrete — without steel reinforcement — axially loaded. A less studied approach involves the use of resonance phenomena, which offers other benefits. In this study, we tested a real-size reinforced concrete column of cross section 20 cm × 20 cm and 2 m long, by applying three cycles of controlled compressive axial load, varying from 0 to 4 MPa, and measuring axial strains and torsional frequencies of vibration. Repeatable results show that the frequencies of vibration and applied compression are positively correlated. indicating a dominant elastic behavior. This study is an important step forward on the path to understanding and implementing a nondestructive technique for stress monitoring of real concrete structures.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121191199","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

Enhancing Vibration-Based Structural Health Monitoring via Edge Computing: A Tiny Machine Learning Perspective 通过边缘计算增强基于振动的结构健康监测:一个微小的机器学习视角

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-75153

F. Zonzini, Francesca Romano, Antonio Carbone, Matteo Zauli, L. De Marchi

{"title":"Enhancing Vibration-Based Structural Health Monitoring via Edge Computing: A Tiny Machine Learning Perspective","authors":"F. Zonzini, Francesca Romano, Antonio Carbone, Matteo Zauli, L. De Marchi","doi":"10.1115/qnde2021-75153","DOIUrl":"https://doi.org/10.1115/qnde2021-75153","url":null,"abstract":"\u0000 Despite the outstanding improvements achieved by artificial intelligence in the Structural Health Monitoring (SHM) field, some challenges need to be coped with. Among them, the necessity to reduce the complexity of the models and the data-to-user latency time which are still affecting state-of-the-art solutions. This is due to the continuous forwarding of a huge amount of data to centralized servers, where the inference process is usually executed in a bulky manner. Conversely, the emerging field of Tiny Machine Learning (TinyML), promoted by the recent advancements by the electronic and information engineering community, made sensor-near data inference a tangible, low-cost and computationally efficient alternative. In line with this observation, this work explored the embodiment of the One Class Classifier Neural Network, i.e., a neural network architecture solving binary classification problems for vibration-based SHM scenarios, into a resource-constrained device. To this end, OCCNN has been ported on the Arduino Nano 33 BLE Sense platform and validated with experimental data from the Z24 bridge use case, reaching an average accuracy and precision of 95% and 94%, respectively.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122328065","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: 4

Application of Artificial Intelligence for Automated Detection of Defects in Nuclear Energy Domain 人工智能在核能领域缺陷自动检测中的应用

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-74889

Eleftherios Anagnostopoulos, Yann Kernin

{"title":"Application of Artificial Intelligence for Automated Detection of Defects in Nuclear Energy Domain","authors":"Eleftherios Anagnostopoulos, Yann Kernin","doi":"10.1115/qnde2021-74889","DOIUrl":"https://doi.org/10.1115/qnde2021-74889","url":null,"abstract":"\u0000 Ensuring the integrity of the primary circuit in nuclear power plants is crucial considering the extreme pressures and temperatures while operating Pressurized Water Reactors (PWR). Non-Destructive Testing (NDT) on such harsh environments is a challenging and complex scenario. Automated assistance on acquisition and analysis systems can importantly contribute as supplementary safety barrier by providing real-time alarms for potential existence of defects.\u0000 In this paper we present the application of Artificial Intelligence in Visual Testing (VT) of Bottom Mounted Nozzles (BMN) of the Reactor Pressure Vessel (RPV). The method that we apply is based on Object Detection using Convolutional Neural Networks (CNN) combined with the Transfer Learning technique in order to limit the necessary training time of the model and the use of Data Augmentation methods for reducing the size of the learning data set. The proposed CNN demonstrates great performances for automatic surface defect detection (cracks) in highly noisy environments with variating illumination conditions. These performances combined with accurate localization and characterization of the defects confirms the interest of advanced CNNs against traditional imaging processing methods for NDT applications. In this study, the results of a comparative blind-test between Human VT analysts are also presented.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129988704","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: 1

Transition to Online Cable Insulation Condition Monitoring 向在线电缆绝缘状态监测过渡

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-75014

S. Glass, L. Fifield, Mychal P. Spencer

{"title":"Transition to Online Cable Insulation Condition Monitoring","authors":"S. Glass, L. Fifield, Mychal P. Spencer","doi":"10.1115/qnde2021-75014","DOIUrl":"https://doi.org/10.1115/qnde2021-75014","url":null,"abstract":"\u0000 Nuclear power plant cables were originally qualified for 40 year life and generally have not required specific test verification to assure service availability through the initial plant qualification period. However, license renewals to 60 and 80 years of operation require a cable aging management program that depends on some form of test and verification to assure fitness for service. Environmental stress (temperature, radiation, chemicals, water, and mechanical) varies dramatically within a nuclear power plant and, in some cases, cables have degraded and required repair or replacement before their qualified end-of-life period. In other cases, cable conditions have been mild and dependable cable performance confirmed to extend well beyond the initial qualified life. Most offline performance-based testing requires cables to be decoupled and de-energized for specially trained technicians to perform testing. These offline tests constitute an expensive operational burden that limits the economic viability of nuclear power plants. Although initial investment may be higher, new online test practices are emerging as options or complements to offline testing that avoid or minimize the regularly scheduled offline test burden. These online methods include electrical and fiber-optic partial discharge measurement, spread spectrum time or frequency domain reflectometry, distributed temperature profile measurements, and local interdigital capacitance measurement of insulation characteristics. Introduction of these methods must be supported by research to confirm efficacy plus either publicly financed or market driven investment to support the start-up expense of cost-effective instrumentation to monitor cable condition and assure reliable operation. This work summarizes various online cable assessment technologies plus introduces a new cable motor test bed to assess some of these technologies in a controlled test environment.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129206216","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: 1

Estimation of Internal Surface Roughness of Additively Manufactured Components Under Complex Conditions Using Artificial Intelligence and Measurements of Ultrasonic Backscatter 基于人工智能和超声后向散射测量的复杂条件下增材制造部件内表面粗糙度估计

2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation Pub Date : 2021-07-28 DOI: 10.1115/qnde2021-75106

Mohamed Subair Syed Akbar Ali, M. Pavlovic, P. Rajagopal

{"title":"Estimation of Internal Surface Roughness of Additively Manufactured Components Under Complex Conditions Using Artificial Intelligence and Measurements of Ultrasonic Backscatter","authors":"Mohamed Subair Syed Akbar Ali, M. Pavlovic, P. Rajagopal","doi":"10.1115/qnde2021-75106","DOIUrl":"https://doi.org/10.1115/qnde2021-75106","url":null,"abstract":"\u0000 Additive Manufacturing (AM) is increasingly being considered for fabrication of components with complex geometries in various industries such as aerospace and healthcare. Control of surface roughness of components is thus a crucial aspect for more widespread adoption of AM techniques. However, estimating the internal (or ‘far-side’) surface roughness of components is a challenge, and often requires sophisticated techniques such as X-ray computed tomography, which are difficult to implement online. Although ultrasound could potentially offer a solution, grain noise and inspection surface conditions complicate the process.\u0000 This paper studies the feasibility of using Artificial Intelligence (AI) in conjunction with ultrasonic measurements for rapid estimation of internal surface roughness in AM components, using numerical simulations. In the first models reported here, a pulse-echo configuration is assumed, whereby a specimen sample with rough surfaces is insonified with bulk ultrasonic waves and the backscatter is used to generate A-scans. Simulations are carried out for various combinations of the model parameters, yielding a large number of such A-scans. A neural network algorithm is then created and trained on a subset of the datasets so generated using simulations, and later used to predict the roughness from the rest. The results demonstrate the immense potential of this approach in inspection automation for rapid roughness assessments in AM components, based on ultrasonic measurements.","PeriodicalId":189764,"journal":{"name":"2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121691085","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