scholarly journals A computer vision-based, in-situ springback monitoring technique for bending of large profiles

2021 ◽  
Author(s):  
Taekwang Ha ◽  
Jun Ma ◽  
Jørgen Blindheim ◽  
Torgeir Welo ◽  
Geir Ringen ◽  
...  
Keyword(s):  
Computer Vision ◽  
Product Quality ◽  
Large Size ◽  
Control Product ◽  
Monitoring Technique ◽  
Size Profile ◽  
Bending Process ◽  
Measurement Tools ◽  
Marked Points

Bending processes have various advantages, such as less processing time, lower number of tooling parts, and cost compared to other manufacturing processes. However, one of the disadvantages of a bending process is the inevitable springback problem, which entails geometrical inaccuracy. Many researchers have made attempts to effectively measure springback in-line to control product quality and compensate for variability. While measurement tools and machines are available to measure springback, they might not be able to accommodate large products due to the size limit of measurement devices. Nevertheless, sensor-based monitoring is becoming critical to control product quality and to move towards Industry 4.0. In this paper, an in-situ springback monitoring technique for bending of large-size profiles is proposed to overcome the measurement restrictions for such profiles. A computer vision technique with the circular Hough transform was used to evaluate springback. The marked points on a profile were used to track the deformation of the workpiece. However, a weakness with image processing is to recognize the points from the complex background. Instead of employing global search for the points in an image frame, the marked points were detected by locally setting regions based on forming parameters such as a bending angle and stretching level. Springback was calculated by the change of position of those points. The results of springback monitoring were validated with the physically measured data from experiments. Based on this measurement technique, the feasibility of a computer vision-based springback monitoring in large-size profile bending is discussed in detail.

scholarly journals 1 ML Wetting Layer upon Ga(As)Sb Quantum Dot (QD) Formation on GaAs Substrate Monitored with Reflectance Anisotropy Spectroscopy (RAS)

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Henning Fouckhardt ◽  
Johannes Strassner ◽  
Thomas H. Loeber ◽  
Christoph Doering
Keyword(s):  
Gaas Substrate ◽  
Semiconductor Quantum Dots ◽  
Ex Situ ◽  
Difference Spectroscopy ◽  
Wetting Layer ◽  
Reflectance Anisotropy ◽  
Atomic Force ◽  
Monitoring Technique ◽  
Scientific Dispute

III/V semiconductor quantum dots (QD) are in the focus of optoelectronics research for about 25 years now. Most of the work has been done on InAs QD on GaAs substrate. But, e.g., Ga(As)Sb (antimonide) QD on GaAs substrate/buffer have also gained attention for the last 12 years. There is a scientific dispute on whether there is a wetting layer before antimonide QD formation, as commonly expected for Stransky-Krastanov growth, or not. Usually ex situ photoluminescence (PL) and atomic force microscope (AFM) measurements are performed to resolve similar issues. In this contribution, we show that reflectance anisotropy/difference spectroscopy (RAS/RDS) can be used for the same purpose as an in situ, real-time monitoring technique. It can be employed not only to identify QD growth via a distinct RAS spectrum, but also to get information on the existence of a wetting layer and its thickness. The data suggest that for antimonide QD growth the wetting layer has a thickness of 1 ML (one monolayer) only.

scholarly journals Mapping of UV-C dose and SARS-CoV-2 viral inactivation across N95 respirators during decontamination

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alisha Geldert ◽  
Alison Su ◽  
Allison W. Roberts ◽  
Guillaume Golovkine ◽  
Samantha M. Grist ◽  
...  
Keyword(s):  
Optical Simulation ◽  
Pathogen Inactivation ◽  
Viral Inactivation ◽  
Flexible Form ◽  
Measurement Tools ◽  
Ultraviolet C ◽  
N95 Respirators ◽  
Uv C ◽  
Dose Difference

AbstractDuring public health crises like the COVID-19 pandemic, ultraviolet-C (UV-C) decontamination of N95 respirators for emergency reuse has been implemented to mitigate shortages. Pathogen photoinactivation efficacy depends critically on UV-C dose, which is distance- and angle-dependent and thus varies substantially across N95 surfaces within a decontamination system. Due to nonuniform and system-dependent UV-C dose distributions, characterizing UV-C dose and resulting pathogen inactivation with sufficient spatial resolution on-N95 is key to designing and validating UV-C decontamination protocols. However, robust quantification of UV-C dose across N95 facepieces presents challenges, as few UV-C measurement tools have sufficient (1) small, flexible form factor, and (2) angular response. To address this gap, we combine optical modeling and quantitative photochromic indicator (PCI) dosimetry with viral inactivation assays to generate high-resolution maps of “on-N95” UV-C dose and concomitant SARS-CoV-2 viral inactivation across N95 facepieces within a commercial decontamination chamber. Using modeling to rapidly identify on-N95 locations of interest, in-situ measurements report a 17.4 ± 5.0-fold dose difference across N95 facepieces in the chamber, yielding 2.9 ± 0.2-log variation in SARS-CoV-2 inactivation. UV-C dose at several on-N95 locations was lower than the lowest-dose locations on the chamber floor, highlighting the importance of on-N95 dose validation. Overall, we integrate optical simulation with in-situ PCI dosimetry to relate UV-C dose and viral inactivation at specific on-N95 locations, establishing a versatile approach to characterize UV-C photoinactivation of pathogens contaminating complex substrates such as N95s.

Electromigration of Electroplated Gold Interconnects

2005 ◽  
Vol 863 ◽  
Author(s):  
Steve Kilgore ◽  
Craig Gaw ◽  
Haldane Henry ◽  
Darrell Hill ◽  
Dieter Schroder
Keyword(s):  
Activation Energy ◽  
Diffusion Mechanism ◽  
Time To Failure ◽  
Ambient Temperatures ◽  
Temperature Coefficients ◽  
Current Stressing ◽  
Monitoring Technique ◽  
The Times ◽  
A Current

AbstractElectromigration tests were performed on passivated electroplated Au four terminal Kelvin line structures using the conventional in situ resistance monitoring technique. The stress conditions were a current density of 2.0 MA/cm2 with ambient temperatures ranging from 325°C to 375°C. The temperature coefficients of resistance (TCR) values were measured prior to current stressing to calculate the Joule heated film temperatures. The times to failure (lifetimes) for the Au line structures were considered as a 50% ΔR/R0 change. The median time to failure (t50%) was plotted against the inverse film temperature to determine the activation energy value as 0.59 ± 0.09 eV. Failure analysis of void location and suggested diffusion mechanism will be discussed.

Development of Computer Vision Technique for in Situ Soil Characterization

1996 ◽  
Vol 1526 (1) ◽  
pp. 86-97 ◽  
Author(s):  
Roman D. Hryciw ◽  
Scott A. Raschke
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Cohesionless Soil ◽  
Software Systems ◽  
Small Scale ◽  
Second Phase ◽  
Video Images ◽  
Subsurface Soil ◽  
Different Levels

Construction and rehabilitation of highways, tunnels, and bridges require detailed information about subsurface stratigraphy. This study presents development of a new method for characterizing subsurface soil in situ using computer vision. Hardware and software systems are integrated to obtain the grain-size distribution (GSD) of subsurface soils continuously with depth and to identify small-scale subsurface anomalies. Research is being conducted in three phases. The first phase consists of measuring the GSD of detached cohesionless soil specimens in the laboratory from digital images obtained with a computer vision system (CVS). The second phase uses the CVS to develop image processing and analysis techniques to classify soil assemblies in the laboratory and identify subsurface anomalies by simulating the manner in which images will be acquired in situ. A texture analysis approach has been developed that can detect changes in stratigraphy. The technique has been successful in identifying different types of dry, uniformly graded soils. Finally, a subsurface vision probe is being designed and constructed that will capture video images at three different levels of magnification continuously with depth.

scholarly journals Autonomous and In Situ Ocean Environmental Monitoring on Optofluidic Platform

Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 69 ◽  
Author(s):  
Fang Wang ◽  
Jiaomeng Zhu ◽  
Longfei Chen ◽  
Yunfeng Zuo ◽  
Xuejia Hu ◽  
...  
Keyword(s):  
Environmental Monitoring ◽  
Chemical Elements ◽  
Biogeochemical Cycles ◽  
Chemical Parameters ◽  
Advantages And Disadvantages ◽  
Large Size ◽  
High Power Consumption ◽  
Marine Disasters ◽  
Ocean Monitoring

Determining the distributions and variations of chemical elements in oceans has significant meanings for understanding the biogeochemical cycles, evaluating seawater pollution, and forecasting the occurrence of marine disasters. The primary chemical parameters of ocean monitoring include nutrients, pH, dissolved oxygen (DO), and heavy metals. At present, ocean monitoring mainly relies on laboratory analysis, which is hindered in applications due to its large size, high power consumption, and low representative and time-sensitive detection results. By integrating photonics and microfluidics into one chip, optofluidics brings new opportunities to develop portable microsystems for ocean monitoring. Optofluidic platforms have advantages in respect of size, cost, timeliness, and parallel processing of samples compared with traditional instruments. This review describes the applications of optofluidic platforms on autonomous and in situ ocean environmental monitoring, with an emphasis on their principles, sensing properties, advantages, and disadvantages. Predictably, autonomous and in situ systems based on optofluidic platforms will have important applications in ocean environmental monitoring.

scholarly journals Identification of Plastic Type and Surface Roughness of Film-Type Plastics in Water Using Kramers–Kronig Analysis

Chemosensors ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 88
Author(s):  
Boniphace Elphace Kanyathare ◽  
Benjamin Asamoah ◽  
Muhammad Umair Ishaq ◽  
James Amoani ◽  
Jukka Räty ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Light Scattering ◽  
Optical Detection ◽  
Nir Spectroscopy ◽  
Water Bodies ◽  
Complex Environment ◽  
Large Size ◽  
Film Type ◽  
Plastic Type

The knowledge of the plastic type, thickness, and the nature of the surface is important towards the monitoring of microplastic pollution in water bodies, especially when vis-NIR spectroscopy is utilized. Factors such as complex environment and surface roughness induced-light scattering of the probing light limit the optical detection of these parameters in in-situ measurements, however. In this paper, a novel application of Kramers–Kronig analysis was exploited to identify both smooth and rough film-type macroplastics with unknown thickness. This method is particularly useful in the in-situ identification of unknown film-like macroplastics; although the sample is large, the ratio function is detected from an area that corresponds to the size of a MP. Therefore, it can be applied for the case of large size MPs. The validity of the method was demonstrated using transmittance data for smooth and roughened plastics given in Kanyathare et al., 2020.

Twinning Behavior in AZ31-B Polycrystal Texture Subjected to In-Situ Bending Test

2010 ◽  
Vol 654-656 ◽  
pp. 715-718 ◽  
Author(s):  
Itsuya Sato ◽  
Seiji Miura ◽  
Tetsuo Mohri
Keyword(s):  
Bending Test ◽  
Confocal Scanning Laser Microscope ◽  
Compression Strain ◽  
Bending Process ◽  
Axis Compression ◽  
Confocal Scanning ◽  
Plane Plastic ◽  
Extension Strain ◽  
Confocal Scanning Laser

A commercial Mg alloy, AZ31B, has been used widely. In the texture of AZ31B sheet, each grain has its c-axis almost parallel to the sheet normal. Therefore, at the bending process of the sheet, basal slip system can not accommodate an in-plane plastic strain which is perpendicular to the c-axis of each grain. It is known that {10―,12} twin can be formed by applying an extension strain parallel to the c-axis, which is equivalent to the a-axis compression strain. So in the bending deformation of the AZ31B sheet with a texture microstructure, it is expected that {10―,12} twinning occurs. In this study, an in-situ bending test of AZ31B sheet with a texture was conducted under a confocal scanning laser microscope to observe twinning by applying compression stress along a direction almost perpendicular to the c-axis of grains. In addition, EBSD techniques were used for the analysis of crystal orientations. The process of twin development observed by the in-situ bending test can be summarized as follows; with the increase of the deformation strain, the total area of twins increases. However, it is noted that the growth of twins is apparent while the number of twins is almost constant during plastic bending deformmation. EBSD analysis suggested that twinning behavior obey Schmid’s law even in the polycrystal.

scholarly journals In-Situ Monitoring and Diagnosing for Fused Filament Fabrication Process Based on Vibration Sensors

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2589 ◽  
Author(s):  
Yongxiang Li ◽  
Wei Zhao ◽  
Qiushi Li ◽  
Tongcai Wang ◽  
Gong Wang
Keyword(s):  
Product Quality ◽  
Real Time ◽  
Case Studies ◽  
Complex Geometry ◽  
Identification Accuracy ◽  
In Situ Monitoring ◽  
Support Vector ◽  
Fused Filament Fabrication ◽  
Vibration Sensors

Fused filament fabrication (FFF) is one of the most widely used additive manufacturing (AM) technologies and it has great potential in fabricating prototypes with complex geometry. For high quality manufacturing, monitoring the products in real time is as important as maintaining the FFF machine in the normal state. This paper introduces an approach that is based on the vibration sensors and data-driven methods for in-situ monitoring and diagnosing the FFF process. The least squares support vector machine (LS-SVM) algorithm has been applied for identifying the normal and filament jam states of the FFF machine, besides fault diagnosis in real time. The identification accuracy for the case studies explored here using LS-SVM is greater than 90%. Furthermore, to ensure the product quality during the FFF process, the back-propagation neural network (BPNN) algorithm has been used to monitor and diagnose the quality defects, as well as the warpage and material stack caused by abnormal leakage for the products in-situ. The diagnosis accuracy for the case studies explored here using BPNN is greater than 95%. Results from the experiments show that the proposed approach can accurately recognize the machine failures and quality defects during the FFF process, thus effectively assuring the product quality.

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