Table of Contents 165 Articles in Issue "2018-02"
Title / Author(s) / Keywords
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Publication |
Sudden Problem in the Above Ground Storage Tank and the Overnight-Found PAUT Solution Sonotron NDT 64, Rehovot [Israel]
NEWS
| NDT.net Journal
| Olympus Webinar: Advancements in Offshore Corrosion Monitoring with the EPOCH® 6LT Ultrasonic Flaw Detector Olympus Scientific Solutions Americas (OSSA) 217, Waltham, MA [USA]
NEWS
| NDT.net Journal
| MANTIS: The Little but Powerful Brother of the GEKKO Karl Deutsch Pruef- und Messgeraetebau 116, Wuppertal [Germany]
NEWS
| NDT.net Journal
| MANTIS: Der kleine, starke Bruder des GEKKO Karl Deutsch Pruef- und Messgeraetebau 116, Wuppertal [Germany]
NEWS DE
| NDT.net Journal
| ECHOGRAPH-HRPR: Kalibre Boru Receives an Ultrasonic Tube Testing System Karl Deutsch Pruef- und Messgeraetebau 116, Wuppertal [Germany]
NEWS
| NDT.net Journal
| Corrosion Measurement at Refineries with the SONOWALL 70 SONOTEC GmbH 55, Halle [Germany]
NEWS
| NDT.net Journal
| Airbus praises the LineMAP/LineSIZING combo TESTIA France 27, Toulouse [France]
NEWS
| NDT.net Journal
| Testia GmbH qualified for CT TESTIA France 27, Toulouse [France]
NEWS
| NDT.net Journal
| The “OKO Association” Group at ASNT 2017 & APCNDT 2017 Promprylad LLC 23, Kiev [Ukraine]
NEWS
| NDT.net Journal
| CIVA Newsletter January 2018 EXTENDE 97, Massy [France] NEWS
| NDT.net Journal
| TESTIA WORLDWIDE NEWSLETTER January 2018 TESTIA France 27, Toulouse [France] NEWS
| NDT.net Journal
| Cofrend END info 21: Information letter for non destructive testing professionals COFREND 15, Paris [France]
NEWS
| NDT.net Journal
| Structural Health Monitoring Market worth 3.40 Billion USD by 2022 MarketsandMarkets 17, Pune, MH [India]
NEWS
| NDT.net Journal
| Infrastructure Monitoring Market worth 3.38 Billion USD by 2023 MarketsandMarkets 17, Pune, MH [India]
NEWS
| NDT.net Journal
| Transverse Cracking in the Manual and Automated Ultrasonic Testing of Welds L. Morgan 2 Morgan Consultant, Petersfield [United Kingdom] Ultrasonic Testing (UT), Tandem technique, Time of Flight Diffraction (TOFD), time of flight diffraction, tandem scanning, automated ultrasonic testing, Automated Ultrasonic Testing, AUT, Transverse cracking, manual ultrasonics, chevron cracking
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The possibility of cracks and other flaws occurring transverse to the direction of welding must not be
taken lightly. The detection of such flaws is always included in the training of UT operators but
operators rarely experience these flaws in practice, so their skills can atrophy. Experience has shown
that transverse cracks can and do occur for a variety of reasons and their detection may not be
straightforward. This paper discusses the use and limitations of conventional UT methods and how
new methods can contribute to a more effective inspection. Both Manual Ultrasonic Testing (MUT)
and Automated Ultrasonic Testing (AUT) are considered.
| NDT.net Journal
| iCT 2018, Algorithms, image processing and visualisation Fully Convolutional Deep Network Architectures for Automatic Short Glass Fiber Semantic Segmentation from CT scans T. Konopczyński1 2, D. Rathore2, J. Rathore3 5, T. Kröger1 3, L. Zheng2 2, C. Garbe2 4, S. Carmignato3 15, J. Hesser2 2 1Department of Mathematics and Informatics; Volume Graphics GmbH 35, Heidelberg [Germany] 2aDepartment of Radiation Oncology bInterdisciplinary Center for Scientific Computing (IWR); Universität Heidelberg 5, Heidelberg [Germany] 3aDepartment of Management and Engineering bDepartment of Management and Engineering (DTG); University of Padova (UNIPD) 29, Padova [Italy] segmentation, deep learning, x-ray CT, short glass fibers
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We present the first attempt to perform short glass fiber semantic segmentation from X-ray computed tomography (CT) volumetric datasets at medium (3.9 µm isotropic) and low (8.3 µm isotropic) resolution using deep learning architectures. We performed experiments on both synthetic and real CT scans and evaluated deep fully convolutional architectures with both 2D and 3D kernels. Our artificial neural networks show robustness at processing medium resolution scans and outperform existing methods in low resolution.
| iCT 2018 Session: Algorithms, image processing and visualisation | iCT 2018, Algorithms, image processing and visualisation A new calibration-free beam hardening reduction method for industrial CT T. Würfl1 2, N. Maass2 2, F. Dennerlein2 , A. Maier1 4 1Pattern Recognition Lab; University of Erlangen-Nürnberg (FAU) 40, Erlangen [Germany] 2Siemens AG 2, Erlangen [Germany]
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This work evaluates a new reference-free beam hardening reduction algorithm for industrial CT applications. The new method is fully automatic and robust to scatter and misalignment, while only consuming a third of the time required for reconstruction. Beam hardening reduction is performed by optimizing a raw data redundancy metric with respect to parameters of a polynomial model. The linearity of this model enables an efficient solution by convex optimization. We present an evaluation of experimental results on a extensive database of industrial CT data sets. The datasets cover a wide range of practically relevant multi-material objects with additional sources of artifacts like photon starvation and truncation. We conducted a user study comparing our method against a manual method, were an expert optimized image quality by selecting an appropriate beam hardening reduction function from a number of options. We find that our method can be applied to industrial CT problems to automatically yield beam hardening reduction on par with a timeconsuming manual optimization of image quality by an expert. Since the method is completely image-based it simplifies the adaptation of CT systems to different application fields.
| iCT 2018 Session: Algorithms, image processing and visualisation | iCT 2018, Algorithms, image processing and visualisation Detection of Narrow Gaps Using Hessian Eigenvalues for Shape Segmentation on CT Volume of Assembled Parts S. Watanabe , Y. Ohtake 14, Y. Nagai 12, H. Suzuki 15 School of Engineering; University of Tokyo 62, Tokyo [Japan] CT volume segmentation, Gap detection, Shape extraction of assembled parts
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Extracting each part of an assembled object from a CT volume is important for analyzing the assembled parts, e.g., evaluating part deformation, measuring the clearance between different parts, and checking the relative positions of the parts. However, separating parts sharing narrow gaps is difficult because the changes in the CT values across narrow gaps are too small to detect using conventional methods, e.g., peak detection of the gradient norms of the CT values. In this study, a method used in detecting a narrow gap whose size is comparable to the voxel-size is proposed. The proposed method is based on peak detection of the Hessian eigenvalues of the CT values. Combining the proposed method with a conventional gradient-based method, we developed a system to segment an assembly composed parts made of the same material.
| iCT 2018 Session: Algorithms, image processing and visualisation | Evaluation of internal defects in additive manufactured metallic network structures by Computed Tomography L. Pejryd 6 Scool of Science and Technology; Örebro University 6, Örebro [Sweden] Selective laser melting, aluminium, titanium, computed tomography
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The ability to manufacture complex internal features is one of the distinct differentiators of Additive Manufacturing (AM) as compared to other manufacturing methods for metal components. This manufacturing process provide designers with new opportunities in the design, such as e.g. networks and curved and non round cooling channels. To fully take advantage of metal AM in industrial use, robust methods for the detection of potential internal defects is however needed. A method that holds the promise of being one of the few tools for non-destructive evaluation (NDE) of internal features and defects is X-ray computed tomography (CT). The applicability and limitations of CT, especially for defect determination in products with complex internal structures is however not fully understood. In this work, parts with different sizes of controlled internal defects in the form of slots of varying width, 0,1 – 0,4 mm was manufactured by AM, using Selective Laser melting (SLM). The parts were produced in both titanium and aluminium alloys and both with internal networks and as solid pieces. For both of the designed types of samples, containing the pre designed defects, the ability to detect the defects by industrial computed tomography (CT) was evaluated. The evaluation of defects using CT data can be done by a trained operator. For solid components this can be done with some assistance of analysis modes that are available in comersial software. For components with complex internal structures, the result is more operator dependant and more work is needed to develop methods for CT inspection that can enable automation of the inspection process and/or to assist a trained operator.
| iCT 2018 Session: Materials Characterisation | Synchrotron based absorption edge tomography for 3D characterization of the microstructure of Mg-Y-Zn alloys C. Gollwitzer1 8, S. Cabeza1 7, G. Garces2 3 1BAM Federal Institute for Materials Research and Testing 1265, Berlin [Germany] 2Department of Physical Metallurgy; National Center for Metallurgical Research (CENIM-CSIC) 3, Madrid [Spain] Other Methods, Synchrotron CT, Absorption edge tomography, differential tomography, LPSO
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Absorption edge tomography is a method which exploits the sudden change of the attenuation coefficient, when the photon energy crosses the absorption edge of an element. The beamline BAMline at BESSY II, which is operated by the Federal Institute for Materials Research and Testing, can provide a monochromatized beam in a photon energy range from 5 keV up to 80 keV with a bandwidth of 2%. Together with the microtomography setup, this enables differential tomography sensitive to any element with N >= 24 (Cr) by using an appropriate K- or L-edge in this range. Here, absorption edge tomography at the Yttrium edge is employed to perform a non-destructive 3D characterization of the microstructure of a high strength Mg-Y-Zn alloy. The long period stacking ordered (LPSO) phase which forms fibres in this material was extracted based on the Yttrium content and the fibre length distribution was analysed.
| iCT 2018 Session: Materials Characterisation |
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