Weld-pool image centroid algorithm for seam-tracking vision model in arc-welding process

2011 ◽  
Vol 5 (5) ◽  
pp. 410 ◽  
Author(s):  
X. Gao ◽  
D. Ding ◽  
T. Bai ◽  
S. Katayama
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Welding Process ◽  
Seam Tracking ◽  
Centroid Algorithm ◽  
Arc Welding Process ◽  
Pool Image

scholarly journals Numerical simulation of weld pool formation in submerged arc welding process

2020 ◽  
Vol 38 (4) ◽  
pp. 355-362
Author(s):  
Yosuke OGINO ◽  
Masahiro IIDA ◽  
Satoru ASAI ◽  
Shohei KOZUKI ◽  
Naoya HAYAKAWA ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Weld Pool ◽  
Arc Welding ◽  
Welding Process ◽  
Submerged Arc Welding ◽  
Arc Welding Process ◽  
Pool Formation ◽  
Submerged Arc

A novel electrode-arc-weld pool model for studying the keyhole formation in the keyhole plasma arc welding process

2019 ◽  
Vol 52 (16) ◽  
pp. 165203 ◽  
Author(s):  
Dongsheng Wu ◽  
Shinichi Tashiro ◽  
Xueming Hua ◽  
Manabu Tanaka
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Welding Process ◽  
Plasma Arc Welding ◽  
Plasma Arc ◽  
Pool Model ◽  
Arc Welding Process

scholarly journals An adaptive approach to compensate seam tracking error in robotic welding process by a moving fixture

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881620
Author(s):  
Reza Ebrahimpour ◽  
Rasul Fesharakifard ◽  
Seyed Mehdi Rezaei
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Sliding Mode ◽  
Gas Metal Arc Welding ◽  
Tracking Error ◽  
Welding Process ◽  
Seam Tracking ◽  
Ball Screw ◽  
Robotic Welding ◽  
Metal Arc Welding

Welding is one of the most common method of connecting parts. Welding methods and processes are very diverse. Welding can be of fusion or solid state types. Arc welding, which is classified as fusion method, is the most widespread method of welding, and it involves many processes. In gas metal arc welding or metal inert gas–metal active gas, the protection of the molten weld pool is carried out by a shielding gas and the filler metal is in the form of wire which is automatically fed to the molten weld pool. As a semi-metallic arc process, the gas metal arc welding is a very good process for robotic welding. In this article, to conduct the metal active gas welding torch, an auxiliary ball screw servomechanism is proposed to move under a welder robot to track the welded seam. This servomechanism acts as a moving fixture and operates separately from the robot. At last, a decentralized control method based on adaptive sliding mode is designed and implemented on the fixture to provide the desired motion. Experimental results demonstrate an appropriate accuracy of seam tracking and error compensation by the proposed method.

scholarly journals A Convenient Unified Model to Display the Mobile Keyhole-Mode Arc Welding Process

2020 ◽  
Vol 10 (22) ◽  
pp. 7955
Author(s):  
Yan Li ◽  
Chen Su ◽  
Ling Wang ◽  
Chuansong Wu
Keyword(s):  
Weld Pool ◽  
Electric Potential ◽  
Arc Welding ◽  
Manufacturing Industry ◽  
Welding Process ◽  
Unified Model ◽  
Computational Time ◽  
Good Prospect ◽  
Plasma Arc ◽  
Arc Welding Process

Keyhole-mode plasma arc welding (PAW) has a good prospect in the manufacturing industry. Unified models of plasma arc and workpiece help to reveal the physical mechanism in PAW for a better application. Previous unified models either deal with a constant keyhole situation or take too much computational time to display the dynamic keyhole process with a two-phase flow method. In view of the convenience for industrial application as well as good accuracy, a convenient unified model was developed to describe the mobile keyhole-mode PAW. With a simplified technique, the multiphase heat and force effect between plasma arc and workpiece was turned into a single-phase problem at each individual domain. Thus, it takes less computational time than previous unified models. The temperature field and weld pool during the mobile keyhole-mode PAW process were revealed, the arc flow and pool flow were displayed and the electric potential was predicted. The experiment was conducted on a stainless-steel plate, and the weld pool image and the measured arc pressure agree well with the calculated result. The calculated electric potential drop also coincides with the experiment. The model provides a convenient and accurate method to display the mobile keyhole-mode arc welding process.

Detection of Weld Pool Width during Strong Arc Disturbance Environment

2012 ◽  
Vol 201-202 ◽  
pp. 379-382
Author(s):  
Liang Zheng Jiang ◽  
Xiang Dong Gao
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Specular Reflection ◽  
Welding Process ◽  
Internal Edge ◽  
External Edge ◽  
Filtering Algorithm ◽  
Light Effects ◽  
Arc Welding Process ◽  
Weld Pool Width

Detecting the weld pool width is prerequisite to control the welding quality. However, in an arc welding process, it is difficult to obtain a clear image of weld pool due to strong arc disturbance. A method is proposed to lessen the arc disturbance and obtain the width of a weld pool. A camera was used to capture the weld pool images during the arc welding process. The frequency domain filter combined with spatial processing algorithms were used to depress the noises in the pool image. During arc welding, the weld pool was in a liquid state and showed specular reflection due to the arc light effects. Because of the specular reflection, edges of the weld pool exhibited different brightness from that of the internal weld pool where a camera hangs. According to this phenomenon, it was easy to recognize the outlines of the internal and external weld pool. After the image noise of the weld pool was eliminated by an image filtering algorithm, then the line scanning on the image was carried out. It was crystal-clear that the external edge and internal edge demonstrate different grey levels. Therefore the method could be utilized to identify and extract the internal weld pool width and external weld pool width.

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