Ripple Line Fillet Seam Tracking with Visual Sensors in Welding Process

2013 ◽  
Vol 579-580 ◽  
pp. 46-51 ◽  
Author(s):  
Qi Lin Bi ◽  
Yan Ming Quan
Keyword(s):  
Tracking System ◽  
Welding Process ◽  
Base Plate ◽  
Seam Tracking ◽  
Welding Parameter ◽  
Motion Controller ◽  
Side Plate ◽  
Image Information ◽  
Time Motion ◽  
Welding Torch

To overcome the problems resulting from weldment trimming and assemble errors, thermal deformation, arc blow, etc., a set of new tracking system of fillet seam for automatic corrugated plate welding was put forward based on machine vision technology. The tracking system included two cameras: the precursor was set in front of the welding torch (a corrugation cycle far away), for capturing the linear laser projected on the side plate and the base plate; the another one was installed over the melting pool for capturing the image of welding torch tip and the seam. The processed image information from the precursor camera was used to track the fillet seam three-dimensional trajectory and the seam width, according to the information the welding motion controller and the welding power made preplanning; the processed torch tip and seam image information was sent to the motion controller and the welding power so that they could make real-time motion and welding parameter adjustment. Computer simulation proved that this new tracking system could work efficiently.

Intelligent seam tracking using ultrasonic sensors for robotic welding

Robotica ◽  
1997 ◽  
Vol 15 (3) ◽  
pp. 275-281 ◽  
Author(s):  
Ajay Mahajan ◽  
Fernando Figueroa
Keyword(s):  
Tracking System ◽  
Welding Process ◽  
Seam Tracking ◽  
Robotic Welding ◽  
Ultrasonic Sensors ◽  
Intelligent Sensor ◽  
Novel Approach ◽  
Transmitted Waves ◽  
Welding Torch ◽  
Arc Welding Process

This paper presents a novel approach for seam tracking using ultrasonics. An ultrasonic seam tracking system has been developed for robotic welding which tracks a seam that curves freely on a two-dimensional surface. The seam is detected by scanning the area ahead of the torch and monitoring the amplitude of the waves received after reflection from the workpiece surface. Scanning is accomplished by using two ultrasonic sensors (a transmitter and a receiver) mounted on a stepper motor such that the transmitter angle is the same as the receiver angle. The motor is mounted on the end-effector just ahead of the welding torch and covers a ninety degree arc in front of the torch. If there is no seam then the receiver receives most of the transmitted waves after reflection, but if there is a seam then most of the transmitted waves are dispersed in directions other than that of the receiver. The system has been tested and is very robust in the harsh environments generated by the arc welding process. The robustness of the system stems from using various schemes such as time windowing, a waveguide, air and metal shields, and an intelligent sensor manager. This ultrasonic system offers some distinct advantages over traditional systems using vision and other sensing techniques. It can be used to weld very shiny surfaces, and is a very economical method in terms of cost as well as computational intensity. The system can be used to detect seams less than 0.5 mm wide and 0.5 mm deep.

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.

Design of Automatic Spot Welding Control System about the Vehicle Compartment Side Plate Based on PLC

2013 ◽  
Vol 441 ◽  
pp. 801-804
Author(s):  
Yi Lun Han ◽  
Jing Wang ◽  
Zong Bing Zhang ◽  
Ming Zhang
Keyword(s):  
Intelligent Control ◽  
Spot Welding ◽  
Welding Process ◽  
Response Speed ◽  
Welding Parameter ◽  
Side Plate ◽  
Compound Control ◽  
The Stability ◽  
And Control ◽  
Control Accuracy

In order to improve the welding efficiency of vehicle compartment side plate, the stability of welding parameter and control accuracy, the thesis applies advanced intelligent control theory (fuzzy and PID compound control) and multi-sensor fusion technology and combines with the automatic spot welding process, using the Mitsubishi FX2N-80MT-001 programmable controller and GT1155-QSBD-C touch screen, achieved the automatic spot welding control of the vehicle compartment side plate. Experimental results show that the system’s response speed, control accuracy and stability can meet the requirements of production.

Automated seam tracking system based on passive monocular vision for automated linear robotic welding process

2017 ◽  
Author(s):  
Átila Astor Weis ◽  
Adriano Velasque Werhli ◽  
Nelson L. Duarte Filho ◽  
Luciane Baldassari Soares ◽  
Cristiano Rafael Steffens ◽  
...  
Keyword(s):  
Tracking System ◽  
Welding Process ◽  
Monocular Vision ◽  
Seam Tracking ◽  
Robotic Welding

Laser vision seam tracking system based on proximal policy optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yanbiao Zou ◽  
Hengchang Zhou
Keyword(s):  
Weld Seam ◽  
Tracking System ◽  
Tracking Error ◽  
Welding Process ◽  
Seam Tracking ◽  
Reference Image ◽  
Image Block ◽  
Content Type ◽  
Weld Seam Tracking ◽  
Policy Optimization

Purpose This paper aims to propose a weld seam tracking method based on proximal policy optimization (PPO). Design/methodology/approach By constructing a neural network based on PPO and using the reference image block and the image block to be detected as the dual-channel input of the network, the method predicts the translation relation between the two images and corrects the location of feature points in the weld image. The localization accuracy estimation network (LAE-Net) is built to update the reference image block during the welding process, which is helpful to reduce the tracking error. Findings Off-line simulation results show that the proposed algorithm has strong robustness and performs well on the test set of curved seam images with strong noise. In the welding experiment, the movement of welding torch is stable, the molten material is uniform and smooth and the welding error is small, which can meet the requirements of industrial production. Originality/value The idea of image registration is applied to weld seam tracking, and the weld seam tracking network is built on the basis of PPO. In order to further improve the tracking accuracy, the LAE-Net is constructed and the reference images can be updated.

Design of Plane Curvilinear Welding Manipulator Control System Based on Motion Controller

2012 ◽  
Vol 580 ◽  
pp. 122-125
Author(s):  
Ru Xiong Li ◽  
Song Hua Jiao ◽  
Yan Wu
Keyword(s):  
Motion Control ◽  
Motor System ◽  
Welding Process ◽  
Curved Beam ◽  
Stepping Motor ◽  
Motion Controller ◽  
Beam Design ◽  
Welding Torch ◽  
Motion Control Card ◽  
Manipulator Control

The 3-D welding manipulator use the hardware of motion controller、IPC 、 stepping motor system and so on, motion control card was used to control three stepping motor, the curved beam design a append structural with“ ”shape to avoid splash in the welding process. In software development, use windows multithread technology to make sure the gesture demand of welding gun perpendicular to welder all the time. Practice has proved, the manipulator can interpolate welding curve and realize accuracy controlling of welding-torch position and gesture in the whole welding process.

Underwater Wet Weld Seam Tracking Based on Passive Visual Sensor

2013 ◽  
Vol 683 ◽  
pp. 725-728
Author(s):  
Bo Chen ◽  
Chuan Bao Jia ◽  
Ji Cai Feng
Keyword(s):  
Weld Seam ◽  
Tracking System ◽  
Water Environment ◽  
Welding Process ◽  
Seam Tracking ◽  
Visual Sensor ◽  
Weld Seam Tracking ◽  
Influence Of Water ◽  
Image Processing Algorithms ◽  
Weld Automation

Weld seam tracking system is urgently needed in weld automation process, but it has not been well studied in underwater weld applications. This paper used visual sensor to automatically monitor the weld seam in underwater wet weld process, and image processing algorithms were developed to remove the influence of water environment on the captured image and automatically obtain the weld torch deviation, and the weld torch was adjusted automatically according to the deviation obtained by the image, experiment results showed that the system could meet the requirements of underwater wet welding process.

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.

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