A Vision-Based Gap Detection Method during the Placement of Large-Scale Composite Structures

2011 ◽  
Vol 186 ◽  
pp. 11-15
Author(s):  
Li Cao ◽  
Wen Chen ◽  
Jun Xiao
Keyword(s):  
Image Processing ◽  
Video Processing ◽  
Composite Structures ◽  
Large Scale ◽  
Low Cost ◽  
High Quality ◽  
Detection Technology ◽  
Gap Measurement ◽  
Automatic Placement ◽  
On Line

Video processing technology is regarded as a low-cost detection technology in complex environment. Because the placement layer is thin and the surface is complex that causes high detection error and high cost in laser measurement. Two problems must be solved before using it in large-scale composite structures automatic placement. One is to obtain the high-quality and stable image, and the other is to improve efficiency of image processing. In this paper, a method obtaining the high quality placement gap images was studied. It made use of the optical characteristics of composite material’s surface texture. And some parameters were determined by experiments. To reduce the calculation cost of image processing, a placement gap measurement method based on line scanning was also proposed here. The method was effective in our detection experiments on an actual workpiece.

scholarly journals Extensive Screening of Green Solvents for Safe and Sustainable UiO-66 Synthesis

2020 ◽  
Author(s):  
Diletta Morelli Venturi ◽  
Filippo Campana ◽  
Fabio Marmottini ◽  
Ferdinando Costantino ◽  
Luigi Vaccaro
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Metal Organic Framework ◽  
Dimethyl Formamide ◽  
Scale Production ◽  
Green Solvents ◽  
High Quality ◽  
Color Code ◽  
Large Scale Production ◽  
Metal Organic

<p>Zirconium based Metal-Organic Framework UiO-66 is to date considered one of the benchmark compound among stable MOFs and it has attracted a huge attention for its employment in many strategic applications. Large scale production of UiO-66 for industrial purposes requires the use of safe and green solvents, fulfilling the green chemistry principles and able to replace the use of <i>N,N</i>-Dimethyl-Formamide (DMF), which, despite its toxicity, is still considered the most efficient solvent for obtaining UiO-66 of high quality. Herein we report on a survey of about 40 different solvents with different polarity, boiling point and acidity, used for the laboratory scale synthesis of high quality UiO-66 crystals. The solvents were chosen according the European REACH Regulation 1907/2006 among those having low cost, low toxicity and fully biodegradable. Concerning MOF synthesis, the relevant parameters chosen for establishing the quality of the results obtained are the degree are the crystallinity, microporosity and specific surface area, yield and solvent recyclability. Taking into account also the chemical physical properties of all the solvents, a color code was assigned in order to give a final green assessment for the UiO-66 synthesis. Defectivity of the obtained products, the use of acidic modulators and the use of alternative Zr-salts have been also taken into consideration. Preliminary results lead to conclude that GVL (γ-valerolactone) is among the most promising solvents for replacing DMF in UiO-66 MOF synthesis. </p>

scholarly journals Extensive Screening of Green Solvents for Safe and Sustainable UiO-66 Synthesis

2020 ◽  
Author(s):  
Diletta Morelli Venturi ◽  
Filippo Campana ◽  
Fabio Marmottini ◽  
Ferdinando Costantino ◽  
Luigi Vaccaro
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Metal Organic Framework ◽  
Dimethyl Formamide ◽  
Scale Production ◽  
Green Solvents ◽  
High Quality ◽  
Color Code ◽  
Large Scale Production ◽  
Metal Organic

<p>Zirconium based Metal-Organic Framework UiO-66 is to date considered one of the benchmark compound among stable MOFs and it has attracted a huge attention for its employment in many strategic applications. Large scale production of UiO-66 for industrial purposes requires the use of safe and green solvents, fulfilling the green chemistry principles and able to replace the use of <i>N,N</i>-Dimethyl-Formamide (DMF), which, despite its toxicity, is still considered the most efficient solvent for obtaining UiO-66 of high quality. Herein we report on a survey of about 40 different solvents with different polarity, boiling point and acidity, used for the laboratory scale synthesis of high quality UiO-66 crystals. The solvents were chosen according the European REACH Regulation 1907/2006 among those having low cost, low toxicity and fully biodegradable. Concerning MOF synthesis, the relevant parameters chosen for establishing the quality of the results obtained are the degree are the crystallinity, microporosity and specific surface area, yield and solvent recyclability. Taking into account also the chemical physical properties of all the solvents, a color code was assigned in order to give a final green assessment for the UiO-66 synthesis. Defectivity of the obtained products, the use of acidic modulators and the use of alternative Zr-salts have been also taken into consideration. Preliminary results lead to conclude that GVL (γ-valerolactone) is among the most promising solvents for replacing DMF in UiO-66 MOF synthesis. </p>

scholarly journals A Survey of Crowdsourcing in Medical Image Analysis

2020 ◽  
Vol 7 ◽  
pp. 1-26 ◽  
Author(s):  
Silas Nyboe Ørting ◽  
Andrew Doyle ◽  
Arno Van Hilten ◽  
Matthias Hirth ◽  
Oana Inel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Image Analysis ◽  
Medical Image ◽  
Large Scale ◽  
Medical Image Analysis ◽  
Machine Learning Algorithms ◽  
Imaging Analysis ◽  
High Quality ◽  
Comprehensive Literature Review

Rapid advances in image processing capabilities have been seen across many domains, fostered by the  application of machine learning algorithms to "big-data". However, within the realm of medical image analysis, advances have been curtailed, in part, due to the limited availability of large-scale, well-annotated datasets. One of the main reasons for this is the high cost often associated with producing large amounts of high-quality meta-data. Recently, there has been growing interest in the application of crowdsourcing for this purpose; a technique that has proven effective for creating large-scale datasets across a range of disciplines, from computer vision to astrophysics. Despite the growing popularity of this approach, there has not yet been a comprehensive literature review to provide guidance to researchers considering using crowdsourcing methodologies in their own medical imaging analysis. In this survey, we review studies applying crowdsourcing to the analysis of medical images, published prior to July 2018. We identify common approaches, challenges and considerations, providing guidance of utility to researchers adopting this approach. Finally, we discuss future opportunities for development within this emerging domain.

Data Science and Knowledge Analytic Contexts on IoE Data for E-BI Application Case

2019 ◽  
pp. 100-126
Author(s):  
Nilamadhab Mishra
Keyword(s):  
Large Scale ◽  
Data Science ◽  
Low Cost ◽  
Edge Computing ◽  
The Other ◽  
High Quality ◽  
Main Research ◽  
Cognitive Values ◽  
Research Challenge

The progressive data science and knowledge analytic tasks are gaining popularity across various intellectual applications. The main research challenge is to obtain insight from large-scale IoE data that can be used to produce cognitive actuations for the applications. The time to insight is very slow, quality of insight is poor, and cost of insight is high; on the other hand, the intellectual applications require low cost, high quality, and real-time frameworks and algorithms to massively transform their data into cognitive values. In this chapter, the author would like to discuss the overall data science and knowledge analytic contexts on IoE data that are generated from smart edge computing devices. In an IoE-driven e-BI application, the e-consumers are using the smart edge computing devices from which a huge volume of IoE data are generated, and this creates research challenges to traditional data science and knowledge analytic mechanisms. The consumer-end IoE data are considered the potential sources to massively turn into the e-business goldmines.

scholarly journals Low-Cost, Disposable, Flexible and Highly Reproducible Screen Printed SERS Substrates for the Detection of Various Chemicals

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Wei Wu ◽  
Li Liu ◽  
Zhigao Dai ◽  
Juhua Liu ◽  
Shuanglei Yang ◽  
...  
Keyword(s):  
Screen Printing ◽  
Large Scale ◽  
Low Cost ◽  
Large Area ◽  
Sers Substrates ◽  
Sensing Applications ◽  
Relative Standard ◽  
Sers Detection ◽  
On Line ◽  
Liquid Milk

Abstract Ideal SERS substrates for sensing applications should exhibit strong signal enhancement, generate a reproducible and uniform response and should be able to fabricate in large-scale and low-cost. Herein, we demonstrate low-cost, highly sensitive, disposable and reproducible SERS substrates by means of screen printing Ag nanoparticles (NPs) on a plastic PET (Polyethylene terephthalate) substrates. While there are many complex methods for the fabrication of SERS substrates, screen printing is suitable for large-area fabrication and overcomes the uneven radial distribution. Using as-printed Ag substrates as the SERS platform, detection of various commonly known chemicals have been done. The SERS detection limit of Rhodamine 6G (R6G) is higher than the concentration of 1 × 10−10 M. The relative standard deviation (RSD) value for 784 points on the detection of R6G and Malachite green (MG) is less than 20% revealing a homogeneous SERS distribution and high reproducibility. Moreover, melamine (MA) is detected in fresh liquid-milk without additional pretreatment, which may accelerate the application of rapid on-line detection of MA in liquid milk. Our screen printing method highlights the use of large-scale printing strategies for the fabrication of well-defined functional nanostructures with applications well beyond the field of SERS sensing.

scholarly journals Upscaling UAS Paradigm to UltraLight Aircrafts: A Low-Cost Multi-Sensors System for Large Scale Aerial Photogrammetry

2020 ◽  
Vol 12 (8) ◽  
pp. 1265 ◽  
Author(s):  
Nicolas Latte ◽  
Peter Gaucher ◽  
Corentin Bolyn ◽  
Philippe Lejeune ◽  
Adrien Michez
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Complete Information ◽  
Integration Time ◽  
Unmanned Aerial Systems ◽  
Price Ratio ◽  
High Quality ◽  
Technical Limitation ◽  
Aerial Photogrammetry ◽  
Operational Range

The use of unmanned aerial systems (UASs) has rapidly grown in many civil applications since the early 2010s. Nowadays, a large variety of reliable low-cost UAS sensors and controllers are available. However, contrary to ultralight aircrafts (ULAs), UASs have a too small operational range to efficiently cover large areas. Flight regulations prevailing in many countries further reduced this operational range; in particular, the “within visual line of sight” rule. This study presents a new system for image acquisition and high-quality photogrammetry of large scale areas (>10 km²). It was developed by upscaling the UAS paradigm, i.e., low-cost sensors and controllers, little (or no) on-board active stabilization, and adequate structure from motion photogrammetry, to an ULA platform. Because the system is low-cost (good quality-price ratio of UAS technologies), multi-sensors (large variety of available UAS sensors) and versatile (high ULA operational flexibility and more lenient regulation than for other platforms), the possible applications are numerous in miscellaneous research domains. The system was described in detail and illustrated from the flight and images acquisition to the photogrammetric routine. The system was successfully used to acquire high resolution and high quality RGB and multispectral images, and produced precisely georeferenced digital elevation model (DEM) and orthophotomosaics for a forested area of 1200 ha. The system can potentially carry any type of sensors. The system compatibility with any sensor can be tested, in terms of image quality and flight plan, with the proposed method. This study also highlighted a major technical limitation of the low-cost thermal infrared cameras: the too high integration time with respect to the flight speed of most UASs and ULAs. By providing the complete information required for reproducing the system, the authors seek to encourage its implementation in different geographical locations and scientific contexts, as well as, its combination with other sensors, in particular, laser imaging detection and ranging (LiDAR) and hyperspectral.

An Online Visual Inspection System for Oil-Seal Dimension

2011 ◽  
Vol 130-134 ◽  
pp. 3548-3552
Author(s):  
Zhang Liang Wu ◽  
Chang Ku Sun ◽  
Jie Liu
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Low Cost ◽  
Measuring System ◽  
Inspection System ◽  
Image Processing Algorithm ◽  
Vision Inspection ◽  
Computer Image Processing ◽  
On Line ◽  
Machine Vision Inspection

Adoption of machine vision inspection and computer image processing technology, an oil-seal dimension measuring system was developed to meet the requirement of online production and real time inspection. The makeup and principle of the system were introduced, as well as its working process and design requirements were described on detailed. The technique of quadratic filtering for image preprocessing combined with the principle of three points determining a circle, point Hough transform and the least squares was employed for image processing algorithm, and high precision sub-pixel edge detection was achieved. The measuring results of experiments demonstrated that the inspection goal on 100 percents of products could be realized successfully, and with many advantages such as non-contact, on-line, real time, appropriate precision and low cost, the system can be applied widely in other production fields.

Preparation of high-quality graphene using triggered microwave reduction under an air atmosphere

2018 ◽  
Vol 6 (7) ◽  
pp. 1829-1835 ◽  
Author(s):  
Wen-Shuai Jiang ◽  
Chao Yang ◽  
Guo-Xing Chen ◽  
Xiao-Qing Yan ◽  
Shao-Nan Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Reduction Method ◽  
Low Cost ◽  
Scale Production ◽  
High Quality ◽  
Air Atmosphere ◽  
Large Scale Production

High-quality intrinsic graphene can be prepared by a simple triggered microwave reduction method under air conditions, which provides a simple and low-cost route for large-scale production of high-quality graphene.

scholarly journals A Survey of Crowdsourcing in Medical Image Analysis

2020 ◽  
Vol 7 ◽  
pp. 1-26
Author(s):  
Silas Nyboe Ørting ◽  
Andrew Doyle ◽  
Arno Van Hilten ◽  
Matthias Hirth ◽  
Oana Inel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Image Analysis ◽  
Medical Image ◽  
Large Scale ◽  
Medical Image Analysis ◽  
Machine Learning Algorithms ◽  
Imaging Analysis ◽  
High Quality ◽  
Comprehensive Literature Review

Rapid advances in image processing capabilities have been seen across many domains, fostered by the  application of machine learning algorithms to "big-data". However, within the realm of medical image analysis, advances have been curtailed, in part, due to the limited availability of large-scale, well-annotated datasets. One of the main reasons for this is the high cost often associated with producing large amounts of high-quality meta-data. Recently, there has been growing interest in the application of crowdsourcing for this purpose; a technique that has proven effective for creating large-scale datasets across a range of disciplines, from computer vision to astrophysics. Despite the growing popularity of this approach, there has not yet been a comprehensive literature review to provide guidance to researchers considering using crowdsourcing methodologies in their own medical imaging analysis. In this survey, we review studies applying crowdsourcing to the analysis of medical images, published prior to July 2018. We identify common approaches, challenges and considerations, providing guidance of utility to researchers adopting this approach. Finally, we discuss future opportunities for development within this emerging domain.

scholarly journals Super-linear speedup for real-time condition monitoring using image processing and drones

2022 ◽  
Vol 12 (2) ◽  
pp. 1548
Author(s):  
Moath Alsafasfeh ◽  
Bradely Bazuin ◽  
Ikhlas Abdel-Qader
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Condition Monitoring ◽  
Video Processing ◽  
Execution Time ◽  
Large Scale ◽  
Solar Panels ◽  
Position Information ◽  
Time Condition ◽  
Linear Speedup

Real-time inspections for the large-scale solar system may take a long time to get the hazard situations for any failures that may take place in the solar panels normal operations, where prior hazards detection is important. Reducing the execution time and improving the system’s performance are the ultimate goals of multiprocessing or multicore systems. Real-time video processing and analysis from two camcorders, thermal and charge-coupling devices (CCD), mounted on a drone compose the embedded system being proposed for solar panels inspection. The inspection method needs more time for capturing and processing the frames and detecting the faulty panels. The system can determine the longitude and latitude of the defect position information in real-time. In this work, we investigate parallel processing for the image processing operations which reduces the processing time for the inspection systems. The results show a super-linear speedup for real-time condition monitoring in large-scale solar systems. Using the multiprocessing module in Python, we execute fault detection algorithms using streamed frames from both video cameras. The experimental results show a super-linear speedup for thermal and CCD video processing, the execution time is efficiently reduced with an average of 3.1 times and 6.3 times using 2 processes and 4 processes respectively.

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