4,823 research outputs found

    Visual Sensing and Defect Detection of Gas Tungsten Arc Welding

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    Weld imperfections or defects such as incomplete penetration and lack of fusion are critical issues that affect the integration of welding components. The molten weld pool geometry is the major source of information related to the formation of these defects. In this dissertation, a new visual sensing system has been designed and set up to obtain weld pool images during GTAW. The weld pool dynamical behavior can be monitored using both active and passive vision method with the interference of arc light in the image significantly reduced through the narrow band pass filter and laser based auxiliary light source.Computer vision algorithms based on passive vision images were developed to measure the 3D weld pool surface geometry in real time. Specifically, a new method based on the reversed electrode image (REI) was developed to calculate weld pool surface height in real time. Meanwhile, the 2D weld pool boundary was extracted with landmarks detection algorithms. The method was verified with bead-on-plate and butt-joint welding experiments.Supervised machine learning was used to develop the capability to predict, in real-time, the incomplete penetration on thin SS304 plate with the key features extracted from weld pool images. An integrated self-adaptive close loop control system consisting the non-contact visual sensor, machine learning based defect predictor, and welding power source was developed for real-time welding penetration control for bead on plate welding. Moreover, the data driven methods were first applied to detect incomplete penetration and LOF in multi-pass U groove welding. New features extracted from reversed electrode image played the most important role to predict these defects. Finally, real time welding experiments were conducted to verify the feasibility of the developed models

    Strain Prediction Using Deep Learning during Solidification Crack Initiation and Growth in Laser Beam Welding of Thin Metal Sheets

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    The strain field can reflect the initiation time of solidification cracks during the welding process. The traditional strain measurement is to first obtain the displacement field through digital image correlation (DIC) or optical flow and then calculate the strain field. The main disadvantage is that the calculation takes a long time, limiting its suitability to real-time applications. Recently, convolutional neural networks (CNNs) have made impressive achievements in computer vision. To build a good prediction model, the network structure and dataset are two key factors. In this paper, we first create the training and test sets containing welding cracks using the controlled tensile weldability (CTW) test and obtain the real strain fields through the Lucas–Kanade algorithm. Then, two new networks using ResNet and DenseNet as encoders are developed for strain prediction, called StrainNetR and StrainNetD. The results show that the average endpoint error (AEE) of the two networks on our test set is about 0.04, close to the real strain value. The computation time could be reduced to the millisecond level, which would greatly improve efficiency

    Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

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    Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

    In situ monitoring of additive manufacturing using digital image correlation: A review

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    UIDB/00667/2020 POCI-01-0145-FEDER-016414This paper is a critical review of in situ full-field measurements provided by digital image correlation (DIC) for inspecting and enhancing additive manufacturing (AM) processes. The principle of DIC is firstly recalled and its applicability during different AM processes systematically addressed. Relevant customisations of DIC in AM processes are highlighted regarding optical system, lighting and speckled pattern procedures. A perspective is given in view of the impact of in situ monitoring regarding AM processes based on target subjects concerning defect characterisation, evaluation of residual stresses, geometric distortions, strain measurements, numerical modelling validation and material characterisation. Finally, a case study on in situ measurements with DIC for wire and arc additive manufacturing (WAAM) is presented emphasizing opportunities, challenges and solutions.publishersversionpublishe

    Digital Image Correlation for Measuring Full-Field Residual Stresses in Wire and Arc Additive Manufactured Components

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    This study aims to demonstrate the capability of the digital image correlation (DIC) technique for evaluating full-field residual stresses in wire and arc-additive-manufactured (WAAM) components. Investigations were carried out on WAAM steel parts (wall deposited on a substrate) with two different wall heights: 24 mm and 48 mm. Mild steel solid wire AWS ER70S-6 was used to print WAAM walls on substrates that were rigidly clamped to H-profiles. DIC was used to monitor the bending deformation of WAAM parts during unclamping from the H-profiles, and residual stresses were calculated from the strain field captured during unclamping. Residual stresses determined from the proposed DIC-based method were verified with an analytical model and validated by the results from established residual stress measurement techniques, i.e., the contour method and X-ray diffraction.</jats:p

    The development of an experimental technique to measure the influence of temperature on the mechanical properties of weldments

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    In large industries, such as in power stations, welds are widely employed to join different components together to meet various property requirements. The thermal gradient that develops during welding causes an inhomogeneous distribution of material properties, in areas adjacent to the weld, known as the Heat Affected Zones (HAZ). Welded joints subjected to elevated temperatures and loads during operations often experience a degradation of mechanical properties and performance of the joint. Studies have found that mechanical phenomena’s such as, fatigue and creep have compromised the structural integrity of weld zones. In essence a welded component acts as a composite material, for which it’s overall performance is dependent on its weakest material component. This study focuses on developing an experimental technique that is capable of measuring the influence of temperature on the mechanical and material properties across a weldment. The development of the experimental technique includes the design and optimisation of the hot zone of a welded tensile specimen, identification and characterisation of the different weld zones as well as, refining a strain recording strategy to detect the localised strains in each of the different weld zones. The application of the experimental technique is applied to welded components from turbine steam penetrations, which were extracted from a coal fired power station. The steam penetrations are a low Cr structural steel; (Cr 0.66, C 0.24 by wt. %) and have been in service for approximately 24 year (± 212 000 hrs). Two primary systems namely the Gleeble 3800 thermo-mechanical simulator and digital image correlation are used in this study. In order to accurately map the in-service evolution of material properties, each of the welds were mechanically loaded in tension and exposed to elevated operating temperatures. To induce mechanical loading at constant elevated temperatures, a Gleeble 3800 thermo-mechanical simulator with a tensile module was used to deform specimens at a strain rate of 50 µε.s1 . Experiments were conducted at various temperatures, ranging from room temperature (RT) to 535 o C. The evolution of material properties across the weldment was evaluated using Digital Image Correlation (DIC). DIC is a non-contact digital technique, capable of measuring localized strain during mechanical loading at elevated temperatures. In order to investigate the localized strain across the different weld zones, virtual strain gauges of one millimetre in length were simulated at intervals of one millimetre. It was found that there was a continuous accumulation of strain from the Fusion Line (FL) into the Parent Material (PM). This finding suggested that the HAZ nearest to the PM; which was the Fine Grained Heat Affected Zone (FGHAZ) was the weakest zone as it strained the most. The FL was found to be the least ductile region of the weld as most of the absorbed thermal energy provided during the welding process was used for strain hardening. At elevated temperatures, localised strain occurred at lower strain values than those at RT. This finding suggested that at elevated temperatures there was more thermal energy available for dislocation activation and mobilization. The influence of temperature on the local weld zones were evaluated by extending a specimen, containing just the parent material. A simulation of a virtual strain gauge across the monolithic specimen’s gauge length, revealed that necking occurred at the centre of the specimen which corresponded to the hot zone. In contrast, a simulation of virtual strain gauges across both welds revealed that necking occurred in the region between the HAZ and weld material. This finding inferred that the presence of a weld reduced the strength of the component, as the weld material was the weakest material. Furthermore, the in-service operating conditions was found to have significantly influenced the material behaviour of the welds. A weld that was exposed to a more elevated temperatures and loads, was found to have undergone a higher degree of material degradation, and strained to a larger extent when compared to a weld that was exposed to a more moderate operating environment
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