Development and evaluation of an image processing algorithm for monitoring fiber laser fusion cutting by a high-speed camera

2021 ◽  
Vol 33 (3) ◽  
pp. 032004
Author(s):  
Max Schleier ◽  
Benedikt Adelmann ◽  
Cemal Esen ◽  
Uwe Glatzel ◽  
Ralf Hellmann
Keyword(s):  
Image Processing ◽  
Fiber Laser ◽  
High Speed ◽  
Processing Algorithm ◽  
Laser Fusion ◽  
High Speed Camera ◽  
Image Processing Algorithm ◽  
Laser Fusion Cutting

scholarly journals An Image-Processing Method for Extracting Kinematic Characteristics of Droplets during Pulsed GMAW

2019 ◽  
Vol 9 (24) ◽  
pp. 5481 ◽  
Author(s):  
Peizhuo Zhai ◽  
Songbai Xue ◽  
Tao Chen ◽  
Jianhao Wang ◽  
Yu Tao
Keyword(s):  
Image Processing ◽  
Monitoring System ◽  
High Speed ◽  
Gas Metal Arc Welding ◽  
Processing Algorithm ◽  
Automatic Welding ◽  
Threshold Method ◽  
Image Processing Algorithm ◽  
Kinematic Characteristics ◽  
Metal Arc Welding

Pulsed gas metal arc welding (GMAW) is widely applied in industrial manufacturing. The use of pulsed GMAW was found superior to the traditional direct-current (DC) welding method with respect to spatter, welding performance, and adaptability of all-position welding. These features are closely related to the special pulsed projected metal transfer process. In this paper, a monitoring system based on a high-speed camera and laser backlight is proposed. High-quality images with clear droplets and a translucent arc can be obtained at the same time. Furthermore, a novel image-processing algorithm is proposed in this paper, which was successfully applied to remove the interference of the arc. As a result, the edge and region of droplets were precisely extracted, which is not possible using only the threshold method. Based on the algorithm, centroid coordinates of undetached and detached droplets can be calculated, and more parameters of the kinematic characteristics of droplets can be derived, such as velocity, acceleration, external force, and momentum. The proposed monitoring system and image-processing algorithm give a simple and feasible way to investigate kinematic characteristics, which can provide a new method for possible applications in studying mathematic descriptions of droplet flight trajectory and developing a precise automatic welding system.

scholarly journals On Image Processing Algorithm for Registration of Three-Dimensional Gas Bubble Movement Using a High Speed Camera

2019 ◽  
Vol 8 (02) ◽  
pp. 24473-24483
Author(s):  
Jakub Augustyniak ◽  
Dariusz Mariusz Perkowski
Keyword(s):  
Image Processing ◽  
Measurement Error ◽  
Computer Tomography ◽  
High Speed ◽  
Flow Analysis ◽  
Gas Bubble ◽  
High Speed Camera ◽  
Image Processing Algorithm ◽  
Two Phase ◽  
Tomography Method

The paper deals with an imaging computer tomography method based on simple image processing techniques for two phase flow analysis. Moreover, it has been presented the algorithm of 3D bubble trajectory reconstruction using a single high speed camera and the system of mirrors. In the experiment a glass tank filled with distilled water was used. The nozzle through which the bubbles were generated was placed in the center of the tank bottom. Through the use of basic image processing and analysis techniques such as noise reduction, smoothing, edge detection and few algorithms like close contour filling, tracking single bubble etc. proposed in paper it became possible to draw out 3D trajectories for gas bubble paths in liquid. In the paper the measurement error of imaging computer tomography method has been estimated. The maximum measurement error recorded for this method was within the limits ±0,65 [mm] for a certain set of parameters like: resolution, mirror angle and deviation error of z axis from the 90o vertical line. Trajectories of subsequently departing bubbles were visualized in the form of figures.

scholarly journals On Image Processing Algorithm for Registration of Three-Dimensional Gas Bubble Movement Using a High Speed Camera

2019 ◽  
Vol 8 (02) ◽  
pp. 24473-24483
Author(s):  
Jakub Augustyniak ◽  
Dariusz Mariusz Perkowski
Keyword(s):  
Image Processing ◽  
Measurement Error ◽  
Computer Tomography ◽  
High Speed ◽  
Flow Analysis ◽  
Gas Bubble ◽  
High Speed Camera ◽  
Image Processing Algorithm ◽  
Two Phase ◽  
Tomography Method

The paper deals with an imaging computer tomography method based on simple image processing techniques for two phase flow analysis. Moreover, it has been presented the algorithm of 3D bubble trajectory reconstruction using a single high speed camera and the system of mirrors. In the experiment a glass tank filled with distilled water was used. The nozzle through which the bubbles were generated was placed in the center of the tank bottom. Through the use of basic image processing and analysis techniques such as noise reduction, smoothing, edge detection and few algorithms like close contour filling, tracking single bubble etc. proposed in paper it became possible to draw out 3D trajectories for gas bubble paths in liquid. In the paper the measurement error of imaging computer tomography method has been estimated. The maximum measurement error recorded for this method was within the limits ±0,65 [mm] for a certain set of parameters like: resolution, mirror angle and deviation error of z axis from the 90o vertical line. Trajectories of subsequently departing bubbles were visualized in the form of figures.

Internal quality evaluation of chestnut using nuclear magnetic resonance

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Soo Hyun Park ◽  
Sang Ha Noh ◽  
Michael J. McCarthy ◽  
Seong Min Kim
Keyword(s):  
Image Processing ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Processing Algorithm ◽  
Internal Quality ◽  
Soluble Solid Content ◽  
Mr Images ◽  
Image Processing Algorithm ◽  
Internal Defects ◽  
Nuclear Magnetic

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

An Image Processing Algorithm to Find New and Old Bruises

1995 ◽  
Vol 11 (5) ◽  
pp. 751-757 ◽  
Author(s):  
J. A. Throop ◽  
D. J. Aneshansley ◽  
B. L. Upchurch
Keyword(s):  
Image Processing ◽  
Processing Algorithm ◽  
Image Processing Algorithm

scholarly journals Image Processing Algorithm for Weight Estimation of Dairy Cattle

2011 ◽  
Vol 36 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Kwang-Wook Seo ◽  
Hyeon-Tae Kim ◽  
Dae-Weon Lee ◽  
Yong-Cheol Yoon ◽  
Dong-Yoon Choi
Keyword(s):  
Image Processing ◽  
Dairy Cattle ◽  
Processing Algorithm ◽  
Weight Estimation ◽  
Image Processing Algorithm
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