scholarly journals Development of an Automated System for Adaptive Post-Weld Treatment and Quality Inspection of Linear Welds

2021 ◽  
Author(s):  
Anders Faarbæk Mikkelstrup ◽  
Morten Kristiansen ◽  
Ewa Kristiansen
Keyword(s):  
Automated System ◽  
Quality Inspection ◽  
Manual Treatment ◽  
Surface Gradient ◽  
3D Scan ◽  
Treatment Type ◽  
Acceptable Quality ◽  
Weld Profile ◽  
Skilled Operator ◽  
Weld Toe

Abstract High-frequency mechanical impact (HFMI) treatment is a well-documented post-weld treatment to improve the fatigue life of welds. Treatment of the weld toe must be performed by a skilled operator due to the curved and inconsistent nature of the weld toe to ensure an acceptable quality. However, the process is characterised by noise and vibrations; hence, manual treatment should be avoided for extended periods of time. This work proposes an automated system for applying robotised 3D scanning to perform post-weld treatment and quality inspection of linear welds. A 3D scan of the weld is applied to locally determine the gradient and curvature across the weld surface to locate the weld toe. Based on the weld toe position, an adaptive robotic treatment trajectory is generated that accurately follows the curvature of the weld toe and adapts tool orientation to the weld profile. The 3D scan is reiterated after the treatment, and the surface gradient and curvature are further applied to extract the quantitative measures of the treatment, such as groove radius, weld toe deviation, and indentation depth and width. The adaptive robotic treatment is compared experimentally to manual and linear robotic treatment. This is done by treating 600 mm weld toe of each treatment type and evaluating the quantitative measures using the developed system. The results showed that the developed system reduced the overall treatment variance by respectively 26.6 % and 31.9 %. Additionally, a mean weld toe deviation of 0.09 mm was achieved; thus, improving process stability yet minimising human involvement.

scholarly journals Development of an automated system for adaptive post-weld treatment and quality inspection of linear welds

2022 ◽  
Author(s):  
Anders F. Mikkelstrup ◽  
Morten Kristiansen ◽  
Ewa Kristiansen
Keyword(s):  
Automated System ◽  
Quality Inspection ◽  
Manual Treatment ◽  
Surface Gradient ◽  
3D Scan ◽  
Treatment Type ◽  
Acceptable Quality ◽  
Weld Profile ◽  
Skilled Operator ◽  
Weld Toe

AbstractHigh-frequency mechanical impact (HFMI) treatment is a well-documented post-weld treatment to improve the fatigue life of welds. Treatment of the weld toe must be performed by a skilled operator due to the curved and inconsistent nature of the weld toe to ensure an acceptable quality. However, the process is characterised by noise and vibrations; hence, manual treatment should be avoided for extended periods of time. This work proposes an automated system for applying robotised 3D scanning to perform post-weld treatment and quality inspection of linear welds. A 3D scan of the weld is applied to locally determine the gradient and curvature across the weld surface to locate the weld toe. Based on the weld toe position, an adaptive robotic treatment trajectory is generated that accurately follows the curvature of the weld toe and adapts tool orientation to the weld profile. The 3D scan is reiterated after the treatment, and the surface gradient and curvature are further applied to extract the quantitative measures of the treatment, such as weld toe radius, indentation depth, and groove deviation and width. The adaptive robotic treatment is compared experimentally to manual and linear robotic treatment. This is done by treating 600-mm weld toe of each treatment type and evaluating the quantitative measures using the developed system. The results showed that the developed system reduced the overall treatment variance by respectively 26.6% and 31.9%. Additionally, a mean weld toe deviation of 0.09 mm was achieved; thus, improving process stability yet minimising human involvement.

Effect of Weld Geometry on the Fatigue Behaviour of Umbilical Super Duplex Stainless Steel Tubes

2017 ◽  
Author(s):  
Hauwa Raji ◽  
Jamie Fletcher Woods
Keyword(s):  
Stainless Steel ◽  
Fatigue Strength ◽  
Fatigue Behavior ◽  
Fatigue Tests ◽  
Super Duplex Stainless Steel ◽  
Steel Tubes ◽  
Weld Geometry ◽  
Weld Profile ◽  
Weld Toe ◽  
Toe Angle

The fatigue behavior of welded components is complicated by many factors intrinsic to the nature of welded joints. The mechanical properties of the material, the welding process and position, the type and geometry of the weld and the residual stress distribution across the weld are a few factors affecting fatigue behavior. Published studies [1, 2] have shown that weld geometry is significantly important in determining the fatigue strength of the weld. For a given weld geometry, the fatigue strength is determined by the severity of the stress concentration at the weld toe or at weld defects and by the soundness of the weld metal. The effect of external weld geometry profile on the fatigue behavior of welded small bore super duplex umbilical steel tubes is investigated. Root cause analysis consisting of fractography, metallography and weld profile measurement is carried out on pairs of fatigue failure samples which were tested at the same stress range but failed at significantly different number of cycles. The samples are selected from Technip Umbilicals Ltd (TU) fatigue database. Following the failure analysis, weld geometric profile measurements are performed on fatigue test samples that were prepared for testing. The weld profile was measured in terms of the external weld cap height, weld width and external linear misalignment. Axial fatigue tests are carried out on these samples which are pre-strained before test to simulate the plastic bending cycles typically experienced during the manufacturing and installation processes prior to operational service. The fatigue tests results are interrogated together with the measured geometric data to identify trends and anomalies. Key weld geometric fatigue performance criteria are subsequently identified. For the welded super duplex stainless steel (SDSS) tubes studied, the height of the weld and the weld toe angle provided the best correlation with fatigue life — shorter lives were obtained from specimens with the highest weld aspect ratio (weld height to width) and lowest weld toe angle.

Evaluation of a completely automated tissue-sectioning machine for paraffin blocks

2011 ◽  
Vol 66 (2) ◽  
pp. 151-154 ◽  
Author(s):  
Maristela L Onozato ◽  
Stephen Hammond ◽  
Mark Merren ◽  
Yukako Yagi
Keyword(s):  
Turnaround Time ◽  
Automated System ◽  
Short Report ◽  
Sectioned Material ◽  
Acceptable Quality ◽  
Near Future ◽  
Anatomical Pathology

Tissue-sectioning automation can be a resourceful tool in processing anatomical pathology specimens. The advantages of an automated system compared with traditional manual sectioning are the invariable thickness, uniform orientation and fewer tissue-sectioning artefacts. This short report presents the design of an automated tissue-sectioning device and compares the sectioned specimens with normal manual tissue sectioning performed by an experienced histology technician. The automated system was easy to use, safe and the sectioned material showed acceptable quality with well-preserved morphology and tissue antigenicity. It is expected that the turnaround time will be improved in the near future.

scholarly journals Automation analysis X-ray of the spine to objectify the assessment of the severity of scoliotic deformity in idiopathic scoliosis: a preliminary report

2020 ◽  
Vol 8 (3) ◽  
pp. 317-326
Author(s):  
Grigory A. Lein ◽  
Natalia S. Nechaeva ◽  
Gulnar М. Mammadova ◽  
Andrey A. Smirnov ◽  
Maxim M. Statsenko
Keyword(s):  
Neural Network ◽  
Idiopathic Scoliosis ◽  
Cobb Angle ◽  
Machine Learning Algorithms ◽  
Automated System ◽  
X Rays ◽  
X Ray ◽  
Scoliotic Deformity ◽  
Window Method ◽  
Treatment Type

Background. A large number of studies have focused on automating the process of measuring the Cobb angle. Although there is no practical tool to assist doctors with estimating the severity of the curvature of the spine and determine the best suitable treatment type. Aim. We aimed to examine the algorithms used for distinguishing vertebral column, vertebrae, and for building a tangent on the X-ray photographs. The superior algorithms should be implemented into the clinical practice as an instrument of automatic analysis of the spine X-rays in scoliosis patients. Materials and methods. A total of 300 digital X-rays of the spine of children with idiopathic scoliosis were gathered. The X-rays were manually ruled by a radiologist to determine the Cobb angle. This data was included into the main dataset used for training and validating the neural network. In addition, the Sliding Window Method algorithm was implemented and compared with the machine learning algorithms, proving it to be vastly superior in the context of this research. Results. This research can serve as the foundation for the future development of an automated system for analyzing spine X-rays. This system allows processing of a large amount of data for achieving 85% in training neural network to determine the Cobb angle. Conclusions. This research is the first step toward the development of a modern innovative product that uses artificial intelligence for distinguishing the different portions of the spine on 2D X-ray images for building the lines required to determine the Cobb angle.

Validation of manual blood culture bottles  v2

2021 ◽  
Author(s):  
Sien Ombelet ◽  
Liselotte Hardy ◽  
Jan Jacobs
Keyword(s):  
Blood Culture ◽  
Blood Cultures ◽  
Automated System ◽  
Low Resource Settings ◽  
Low Resource ◽  
System P ◽  
Acceptable Quality ◽  
Personal Experiences ◽  
Laboratory Protocol

Use of equipment-free, “manual” blood cultures is still widespread in low-resource settings, as requirements for implementation of automated systems are often not met. Quality of manual blood culture bottles currently on the market, however, is usually unknown. An acceptable quality in terms of yield and speed of growth can be ensured by evaluating the bottles using simulated blood cultures. In these experiments, bottles from different systems are inoculated in parallel with blood and a known quantity of bacteria. Based on literature review and personal experiences, we propose a short and practical protocol for an efficient evaluation of manual blood culture bottles, aimed at research or reference laboratories in low-resource settings. This laboratory protocol was used in a study for Médecins Sans Frontières' Mini-Lab project, which aims to bring clinical bacteriology to low-resource settings. Three bottle types were evaluated in this study; two "manual" blood culture bottles and one automated system.

Fatigue Life Improvement Using Mechanical Post Treatment for Weldment

2008 ◽  
Vol 580-582 ◽  
pp. 97-100
Author(s):  
Seung Ho Han ◽  
Jeong Woo Han ◽  
Yong Yun Nam
Keyword(s):  
Fatigue Life ◽  
Fatigue Strength ◽  
Residual Stresses ◽  
Quantitative Measure ◽  
Fatigue Strength Improvement ◽  
Weld Profile ◽  
Weld Toe ◽  
Life Improvement ◽  
Hammer Peening ◽  
Compressive Residual Stresses

Mechanical post treatments for welded structures have been applied in various industrial fields and, in most cases, have been found to cause substantial increase in their fatigue strength. These methods, generally, consist of the modification of weld toe geometry and the introduction of compressive residual stresses. In hammer peening, the weld profile is modified due to removal or reduction of minute crack-like flaws; compressive residual stresses are also induced by repeated hammering of the weld toe region with blunt-nosed chisel. In this study, a hammer peening procedure, using commercial pneumatic chipping hammer, was developed; a quantitative measure of fatigue strength improvement was performed. The fatigue life of hammer-peened specimen was prolonged by approximately 10 times in S=240MPa, and was doubled for the as-welded specimen.

scholarly journals Improving the Performance of Lung Cancer Detection at Earlier Stage and Prediction of Reoccurrence using the Neural Networks and Ant Lion Optimizer

2019 ◽  
Vol 8 (2) ◽  
pp. 6378-6391
Keyword(s):  
Lung Cancer ◽  
Optimization Algorithm ◽  
Back Propagation ◽  
Medical Application ◽  
Automated System ◽  
Ant Lion Optimization ◽  
Treatment Type ◽  
Ant Lion ◽  
Propagation Network ◽  
Lion Optimization Algorithm

Lung cancer is considered to be the one among the most dreaded disease which will be the main reason for the death of individuals and having greater deterioration of death if it is not identified at primitive stage. Because of the fact that Lung cancer could be identified only after spreading to the parts of lungs to a greater extent and it is very tough to predict the presence of lung cancer at the earlier stage. Moreover, it involves greater error in the diagnosing the presence of Lung cancer by Radiologists and Expert Doctors. Therefor it is compulsory to design an intelligent and automated system for accurately predicting the cancer and stage at which the stage of cancer or enhancing the accuracy of prediction for detecting the cancer at earlier which will be much helpful in deciding the treatment type and depth of the treatment based on the extent of disease. Currently application of ANN strategies are the influential ways in supporting expert doctor for examining, complicated medical increase across a wider category of medical application. Back Propagation Network are ideal in recognizing lung cancer and there is no requirement involvement by expert doctors. Maximum number of applications of BPN in medical diagnosis will be utilized in the applications related to decision making of the presence or absence of disease; by which the performance will be reliant over the considered features and allocating the patient with minimum number of classes. Here this research paper establishes the idea of using BPN in the classification of the lung cancer and its stages and the predicting the possibility of recurrence. Along with the BPN, a nature inspired Meta Heuristics that is termed as Ant Lion Optimization Algorithm is used in optimizing the parameters and weights of Back Propagation Network. By using the Ant Lion Optimization Algorithm, the convergence mechanism is improved along with improving the accuracy of the proposed technique and it avoids the chance of getting caught within the clutches of local minima. By using this proposed method BPN network optimized with the help of antlion optimizer more accurate prediction of lung cancer is possible even at primitive stage and the predicting of chance of reoccurrence even after undergoing the appropriate treatment.

Computer-Controlled Hrem Alignment Using Automated Diffractogram Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 532-533
Author(s):  
G.Y. Fan ◽  
O.L. Krivanek
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
The Other ◽  
Full Information ◽  
Resolution Electron ◽  
Skilled Operator ◽  
Automatic Alignment ◽  
High Resolution Electron Microscope ◽  
Computer Controlled ◽  
Recorded Image

Full alignment of a high resolution electron microscope (HREM) requires five parameters to be optimized: the illumination angle (beam tilt) x and y, defocus, and astigmatism magnitude and orientation. Because neither voltage nor current centering lead to the correct illumination angle, all the adjustments must be done on the basis of observing contrast changes in a recorded image. The full alignment can be carried out by a computer which is connected to a suitable image pick-up device and is able to control the microscope, sometimes with greater precision and speed than even a skilled operator can achieve. Two approaches to computer-controlled (automatic) alignment have been investigated. The first is based on measuring the dependence of the overall contrast in the image of a thin amorphous specimen on the relevant parameters, the other on measuring the image shift. Here we report on our progress in developing a new method, which makes use of the full information contained in a computed diffractogram.

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