Study on Dynamic Development of Three-dimensional Weld Pool Surface in Stationary GTAW

2018 ◽  
Vol 37 (5) ◽  
pp. 455-462 ◽  
Author(s):  
Jiankang Huang ◽  
Jing He ◽  
Xiaoying He ◽  
Yu Shi ◽  
Ding Fan
Keyword(s):  
Weld Pool ◽  
Specular Reflection ◽  
Three Dimensional ◽  
Welding Process ◽  
Surface Shape ◽  
Weld Penetration ◽  
Dynamic Development ◽  
Pool Surface ◽  
Gtaw Process ◽  
Weld Pool Surface

AbstractThe weld pool contains abundant information about the welding process. In particular, the type of the weld pool surface shape, i. e., convex or concave, is determined by the weld penetration. To detect it, an innovative laser-vision-based sensing method is employed to observe the weld pool surface of the gas tungsten arc welding (GTAW). A low-power laser dots pattern is projected onto the entire weld pool surface. Its reflection is intercepted by a screen and captured by a camera. Then the dynamic development process of the weld pool surface can be detected. By observing and analyzing, the change of the reflected laser dots reflection pattern, for shape of the weld pool surface shape, was found to closely correlate to the penetration of weld pool in the welding process. A mathematical model was proposed to correlate the incident ray, reflected ray, screen and surface of weld pool based on structured laser specular reflection. The dynamic variation of the weld pool surface and its corresponding dots laser pattern were simulated and analyzed. By combining the experimental data and the mathematical analysis, the results show that the pattern of the reflected laser dots pattern is closely correlated to the development of weld pool, such as the weld penetration. The concavity of the pool surface was found to increase rapidly after the surface shape was changed from convex to concave during the stationary GTAW process.

Sensing Free Surface of Arc Weld Pool Using Specular Reflection: Principle and Analysis

1996 ◽  
Vol 210 (6) ◽  
pp. 553-564 ◽  
Author(s):  
R Kovacevic ◽  
Y M Zhang
Keyword(s):  
Weld Pool ◽  
Specular Reflection ◽  
Three Dimensional ◽  
Surface Shape ◽  
Pool Surface ◽  
Imaging Model ◽  
Dimensional Shape ◽  
Weld Pool Surface ◽  
Welding Processes ◽  
Three Dimensional Shape

The weld pool surface provides important information for understanding arc welding processes. In this study, a novel vision sensor is proposed to measure the three-dimensional shape of the free weld pool surface. A pulsed laser is projected on to the weld pool through a specific grid. Specular reflection from the pool surface is sensed using a high shutter speed camera. The three-dimensional weld pool surface shape is clearly shown by the specular reflection. To determine the shape of the pool surface, an image processing technology has been developed to extract the skeleton of the specular reflection from the acquired image. The imaging principle is analysed to determine the correlation between the reflection and the weld pool surface. If the weld pool surface is known, the corresponding specular reflection can be directly calculated using the imaging model which is derived based on the reflection law. However, no explicit models can be obtained to determine the weld pool surface using the reflection and sensor parameters. To solve this difficulty, an iterative algorithm is proposed. The weld pool surface can now be calculated in 1 second from the specular reflection of the weld pool surface. A higher calculation speed is currently being pursued.

Real-Time Image Processing for Monitoring of Free Weld Pool Surface

1997 ◽  
Vol 119 (2) ◽  
pp. 161-169 ◽  
Author(s):  
R. Kovacevic ◽  
Y. M. Zhang
Keyword(s):  
Weld Pool ◽  
Specular Reflection ◽  
Welding Process ◽  
Ccd Camera ◽  
Weld Penetration ◽  
Reflection Pattern ◽  
Pool Surface ◽  
Edge Points ◽  
On Line ◽  
Weld Pool Surface

The arc weld pool is always deformed by plasma jet. In a previous study, a novel sensing mechanism was proposed to sense the free weld pool surface. The specular reflection of pulsed laser stripes from the mirror-like pool surface was captured by a CCD camera. The distorted laser stripes clearly depicted the 3D shape of the free pool surface. To monitor and control the welding process, the on-line acquisition of the reflection pattern is required. In this work, the captured image is analyzed to identify the torch and electrode. The weld pool edges are then detected. Because of the interference of the torch and electrode, the acquired pool boundary may be incomplete. To acquire the complete pool boundary, models have been fitted using the edge points. Finally, the stripes reflected from the weld pool are detected. Currently, the reflection pattern and pool boundary are being related to the weld penetration and used to control the weld penetration.

scholarly journals The Reconsitution of the Weld Pool Surface in Stationary TIG Welding Process With Filler Wire

2020 ◽  
Author(s):  
Jiankang Huang ◽  
LIU Guangyin ◽  
HE Jing ◽  
YU Shurong ◽  
LIU Shien ◽  
...  
Keyword(s):  
Weld Pool ◽  
Three Dimensional ◽  
Welding Process ◽  
Tig Welding ◽  
Filler Wire ◽  
Surface Evolution ◽  
Recovery Algorithm ◽  
Pool Surface ◽  
Weld Pool Surface ◽  
Dimensional Surface

Abstract In order to study the dynamic characteristics of the weld pool surface during the TIG welding process of the filler wire, an observation test platform for the study of the three-dimensional surface behavior evolution of the TIG weld pool based on the grid structure laser was used to observe the weld pool surface and obtain the reflection grid laser image. The three-dimensional surface evolution of the fixed-point TIG welding pool is accurately restored by the three-dimensional recovery algorithm of the weld pool surface, so as to obtain the three-dimensional surface morphology of the weld pool. The difference between the obtained weld pool height and the experimental results is very small, and the results are basically the same.

scholarly journals Deep Learning-Based Detection of Penetration from Weld Pool Reflection Images

2020 ◽  
Vol 99 (9) ◽  
pp. 239s-245s
Author(s):  
CHAO LI ◽  
◽  
QIYUE WANG ◽  
WENHUA JIAO ◽  
MICHAEL JOHNSON ◽  
...  
Keyword(s):  
Weld Pool ◽  
Data Augmentation ◽  
Welding Process ◽  
Descent Method ◽  
Machine Learning Techniques ◽  
Gradient Descent Method ◽  
Neural Net ◽  
Weld Penetration ◽  
Process Data ◽  
Pool Surface

An innovative method was proposed to determine weld joint penetration using machine learning techniques. In our approach, the dot-structured laser images reflected from an oscillating weld pool surface were captured. Experienced welders typically evaluate the weld penetration status based on this reflected laser pattern. To overcome the challenges in identifying features and accurately processing the images using conventional machine vision algorithms, we proposed the use the raw images without any processing as the input to a convolutional neural network (CNN). The labels needed to train the CNN were the measured weld penetration states, obtained from the images on the backside of the workpiece as a set of discrete weld penetration categories. The raw data, images, and penetration state were generated from extensive experiments using an automated robotic gas tungsten arc welding process. Data augmentation was performed to enhance the robustness of the trained network, which led to 270,000 training examples, 45,000 validation examples, and 45,000 test examples. A six-layer convolutional neural net-work trained with a modified mini-batch gradient descent method led to a final testing accuracy of 90.7%. A voting mechanism based on three continuous images increased the classification accuracy to 97.6%.

Prediction of Surface Depression of a Tungsten Inert Gas Weld Pool in the Full-Penetration Condition

1995 ◽  
Vol 209 (3) ◽  
pp. 221-226 ◽  
Author(s):  
C S Wu ◽  
L Dorn
Keyword(s):  
Weld Pool ◽  
Dynamic Balance ◽  
Three Dimensional ◽  
Tig Welding ◽  
Inert Gas ◽  
Three Dimensional Model ◽  
Pool Surface ◽  
Full Penetration ◽  
Weld Pool Surface ◽  
Surface Depression

A three-dimensional model is set up to predict the surface depression of a tungsten inert gas (TIG) weld pool in a full-penetration condition in order to find out the relation between pool depression and weld penetration. It solves pool surface depression, fluid flow and heat transfer simultaneously and determines the configuration of a weld pool surface based on the dynamic balance among arc pressure, pool gravity and surface tension at the deformed weld pool surface. In the numerical simulation, difficulties associated with the irregular shape of the deformed weld pool surface and the liquid/solid interface have been overcome by adopting a boundary-fitted non-orthogonal curvilinear coordinate system. A series of data about pool surface depression under different TIG welding conditions are obtained. The validity of the model is verified through TIG welding experiments.

scholarly journals Numerical Simulation and Industrial Application of High Speed Tandem TIG Welding

2021 ◽  
Author(s):  
Dongsheng Wu ◽  
Jiuling Huang ◽  
Kong Liang ◽  
Xueming Hua ◽  
Min Wang ◽  
...  
Keyword(s):  
Molten Metal ◽  
Weld Pool ◽  
High Speed ◽  
Metal Flow ◽  
Welding Process ◽  
Tig Welding ◽  
Pool Surface ◽  
Weld Pool Surface ◽  
Welding Processes ◽  
Molten Metal Flow

Abstract Self-developed high speed tandem TIG welding equipment were adopted to manufacture titanium welded tubes with high efficiency and high quality. The joint made by this high efficient welding process met Chinese standard requirements. A coupled electrode, arc and weld pool numerical model was also developed to investigate temperature and velocity distributions, and energy propagation of this welding process. The numerical results showed that the Marangoni stress was much higher than the arc shear stress, and was mainly positive after leading and trailing arcs in the x and y directions, so the molten metal flowed backward on the top weld pool surface. Previous studies proposed that a “pull-push” flow pattern defined as a backward molten metal flow after the leading arc and a forward molten metal flow before the trailing arc existed on the top weld pool surface in tandem arc welding processes, while it was not observed in this case. The calculated arc efficiency of the high speed tandem TIG welding was about 79.8%.

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