A study on an automatic seam tracking system by using an electromagnetic sensor for sheet metal arc welding of butt joints

2002 ◽  
Vol 216 (6) ◽  
pp. 911-920 ◽  
Author(s):  
B-H You ◽  
J-W Kim
Keyword(s):  
Sheet Metal ◽  
Arc Welding ◽  
Tracking System ◽  
Weld Line ◽  
Welding Process ◽  
Seam Tracking ◽  
Displacement Sensor ◽  
Tracking Accuracy ◽  
Metal Arc Welding ◽  
Electromagnetic Sensor

Many sensors, such as the vision sensor and the laser displacement sensor, have been developed to automate the arc welding process. However, these sensors have some problems due to the effects of arc light, fumes and spatter. An electromagnetic sensor, which utilizes the generation of an eddy current, was developed for detecting the weld line of a butt joint in which the root gap size was zero. An automatic seam tracking system designed for sheet metal arc welding was constructed with a sensor. Through experiments, it was revealed that the system had an excellent seam tracking accuracy of the order of ±0.2mm.

A study of a dual-electromagnetic sensor system for weld seam tracking of I-butt joints

2003 ◽  
Vol 217 (9) ◽  
pp. 1305-1313 ◽  
Author(s):  
J-W Kim ◽  
J-H Shin
Keyword(s):  
Sheet Metal ◽  
Arc Welding ◽  
Weld Seam ◽  
Welding Process ◽  
Seam Tracking ◽  
Sensor System ◽  
Displacement Sensor ◽  
Butt Joints ◽  
Current Variation ◽  
Electromagnetic Sensor

Seam tracking systems for the arc welding process use various kinds of sensor including the arc sensor, vision sensor and laser displacement sensor. Among the various sensors available, the electromagnetic sensor is one of the most useful methods, especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fumes generated during the welding process, or by the surface conditions of the weldment such as paint marks and scratches. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation in the metal near the sensor, was developed for the arc welding of sheet metal I-butt joints. The dual-electromagnetic sensor thus detects the offset displacement of the weld line from the centre of the sensor head, even when there is no gap in the joint. A set of design variables for the sensor was examined to determine the maximum sensing capability through repeated experiments. Seam tracking was performed by correcting the position of the sensor to the amount of offset displacement determined during each sampling period. From the experimental results, the developed sensor system showed an excellent capability for weld seam detection and tracking when the sensor-to-workpiece distance was less than 5mm.

Noncontact Ultrasonic Sensing for Seam Tracking in Arc Welding Processes

1998 ◽  
Vol 120 (3) ◽  
pp. 600-608 ◽  
Author(s):  
S. B. Zhang ◽  
Y. M. Zhang ◽  
R. Kovacevic
Keyword(s):  
Arc Welding ◽  
Focal Length ◽  
Tracking System ◽  
Gas Metal Arc Welding ◽  
Transmission Efficiency ◽  
Seam Tracking ◽  
High Frequency Ultrasound ◽  
Tracking Accuracy ◽  
Metal Arc Welding ◽  
Welding Processes

A novel seam tracking technology based on high frequency ultrasound is developed in order to achieve high accuracy in weld seam identification. The transmission efficiency of the ultrasound is critical for obtaining a sufficient echo amplitude. Since the transmission efficiency is determined by the difference in impedance between the piezoelectric ceramic and air, match layers are designed to optimize the transmission efficiency by matching impedance. Since the air impedance depends on the density and velocity of the ultrasound, which both depend on the temperature, the optimization has been done for a wide bandwidth. Also, the receiving circuit is designed so that its resonance frequency matches the frequency of the ultrasound. As a result, the sensitivity of the noncontact ultrasonic sensor is improved 80-fold. By properly designing the focal length of the transducer, a high resolution ultrasound beam, 0.5 mm in diameter, is achieved. Based on the proposed sensing technology, a noncontact seam tracking system has been developed. Applications of the developed system in gas tungsten arc welding (GTAW) and CO2 gas metal arc welding (GMAW) processes show that a tracking accuracy of 0.5 mm is guaranteed despite the arc light, spatter, high temperature, joint configuration, small gap, etc.

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.

A Study on Modified Hough Algorithm for Image Processing in Weld Seam Tracking System

2015 ◽  
Vol 1088 ◽  
pp. 824-828 ◽  
Author(s):  
Jong Pyo Lee ◽  
Qian Qian Wu ◽  
Min Ho Park ◽  
Cheol Kyun Park ◽  
Ill Soo Kim
Keyword(s):  
Image Processing ◽  
Weld Seam ◽  
Gma Welding ◽  
Vision System ◽  
Tracking System ◽  
Computing Time ◽  
Weld Line ◽  
Welding Process ◽  
Seam Tracking ◽  
Weld Seam Tracking

In modern market, achieving mechanical and automatic arc welding process is the key issue to be solved in welding industries. Because of the high complexity of the welding environment, manual detection of the weld line information is hard to be successful and time consuming. Therefore, this study aim at developing a new image processing algorithm for seam tracking system in Gas Metal Arc (GMA) welding by modified Hough algorithm based on the laser vision system. Firstly, noises in the captured weld seam images by CCD camera were effectively removed by noise filtering algorithm and then weld joint position were detected by the modified Hough algorithm to realize the automatic weld seam tracking. To verify the efficiency of the developed image processing model, a common image processing method was employed and the processed results were compared with the proposed algorithm. Statistical results proved that the modified Hough algorithm was able to acquire the weld information precisely with less computing time and memory cost, which also capable for industrial application.

Visual Technique for Detecting Weld Position Based on Hough Transformation

2010 ◽  
Vol 139-141 ◽  
pp. 2059-2062
Author(s):  
Zhao Yu Li ◽  
Xiang Dong Gao ◽  
Xing Huan Zhu ◽  
Jian Wen Lin
Keyword(s):  
Arc Welding ◽  
Tracking System ◽  
Welding Process ◽  
Seam Tracking ◽  
Edge Image ◽  
Hough Transformation ◽  
Visual Sensing ◽  
Visual Technique ◽  
Arc Welding Process ◽  
Weld Edge

Detecting the weld position is the precondition of seam tracking during an arc welding process, and is crucial to achieve high-quality welds. Visual sensing is one of the most attractive approaches to detect the weld position, which provides valuable information to control the arc following the expected path. The weld edge is main characteristics of the weld position image, here the visual technique for detecting the weld position based on Hough transformation is proposed. The weld position can be detected and recognized through Hough transformation, while the weld edge image is detected using the Canny operators. And Hough transformation is modified based on the actual weld situation. Therefore, the precision of the weld detection can be improved. From the analysis of experiments, it has been proved that the proposed method can detect the width and the center of the weld, and is suitable for the seam tracking system based on the computer vision.

Optimization of Welding Process Parameters for Rotating Arc Welding Sensor Based on Genetic Algorithm

2008 ◽  
Vol 575-578 ◽  
pp. 769-773
Author(s):  
Jian Ping Jia ◽  
Hua Zhang ◽  
Hui Huang
Keyword(s):  
Genetic Algorithm ◽  
Process Parameters ◽  
Arc Welding ◽  
High Speed ◽  
Tracking System ◽  
Welding Process ◽  
Welding Current ◽  
Seam Tracking ◽  
Rotating Arc ◽  
Input Variables

The high speed rotating arc welding sensor (RAWS) driven by motor with air axis is widely used in seam tracking system. Using the characters of the RAWS, the purpose of this study based on Genetic Algorithm (GA) is to optimize welding process parameters of the RAWS for obtaining satisfied seam geometry. The output variables are penetration, width and height of the seam geometry. These output variables are determined by input variables, which are the welding current, welding voltage, welding speed, rotating arc radius, rotating arc frequency and rotating arc direction. Experimentations are made according to the optimal welding process parameters, and the result shows that the GA is an effective method to optimize the welding process parameters of the RAWS. The described computational methodology enables obtaining a seam with desired geometry.

scholarly journals Two gas metal arc welding process dataset of arc parameters and input parameters

Data in Brief ◽  
2021 ◽  
Vol 35 ◽  
pp. 106790
Author(s):  
Rogfel Thompson Martinez ◽  
Guillermo Alvarez Bestard ◽  
Sadek C. Absi Alfaro
Keyword(s):  
Arc Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Metal Arc Welding ◽  
Input Parameters ◽  
Arc Welding Process
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