Application of Vision Sensor to Seam Tracking of Butt Joint in Container Manufacture

2012 ◽  
pp. 56-82
Keyword(s):  
Butt Joint ◽  
Seam Tracking ◽  
Vision Sensor

Weld Seam Recognition Based on Wavelet Analysis Algorithm

2011 ◽  
Vol 480-481 ◽  
pp. 1593-1597
Author(s):  
You Rui Huang ◽  
Na Na Zhao
Keyword(s):  
Genetic Algorithm ◽  
Wavelet Analysis ◽  
Image Recognition ◽  
Weld Seam ◽  
Wavelet Coefficient ◽  
Recognition Algorithm ◽  
Seam Tracking ◽  
Vision Sensor ◽  
Immune Genetic Algorithm ◽  
Analysis Algorithm

Vision sensor for weld seam location and seam tracking is developed. It is difficult for realizing picture precise identification based on machine welding at present, the image recognition algorithm based on wavelet analysis is designed in this paper. It uses immune genetic algorithm to optimize wavelet coefficient, and extracts the edge of picture preferably. In the process of detecting edges, compared with the others, the algorithm can inhibit the interference of noises effectively and remove artifacts of edges, which make the detected edge clearly and carefully. The result shows that the wavelet analysis algorithm has better effect for weld seam recognition.

A study on the welding seam tracking by using Laser Vision Sensor

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Taewook Kim ◽  
Seungbeom Lee ◽  
Seunghwan Baek ◽  
Kwangsuck Boo
Keyword(s):  
Seam Tracking ◽  
Vision Sensor ◽  
Welding Seam ◽  
Laser Vision Sensor ◽  
Laser Vision

Welding seam recognition and tracking for a novel mobile welding robot based on multi-layer sensing strategy

2021 ◽  
Author(s):  
Chao Liu ◽  
Hui Wang ◽  
Yu Huang ◽  
Youmin Rong ◽  
Jie Meng ◽  
...  
Keyword(s):  
Seam Tracking ◽  
Sensor System ◽  
Vision Sensor ◽  
Welding Robot ◽  
Welding Seam ◽  
Localization And Mapping ◽  
Laser Vision Sensor ◽  
Tracking Ability ◽  
Mobile Welding Robot ◽  
Laser Vision

Abstract Mobile welding robot with adaptive seam tracking ability can greatly improve the welding efficiency and quality, which has been extensively studied. To further improve the automation in multiple station welding, a novel intelligent mobile welding robot consists of a four-wheeled mobile platform and a collaborative manipulator is developed. Under the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operation. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, the multi-layer sensing strategy is performed to ensure the welding seam can be detected and tracked with high precision. By applying hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Then a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively in different station. Also, the multiple station welding efficiency can be improved and quality can also be guaranteed.

Robotic Curve-Shaped Seam Tracking System Using Vision Sensor

2013 ◽  
Vol 397-400 ◽  
pp. 1486-1489
Author(s):  
Feng Xin Gao
Keyword(s):  
Image Processing ◽  
Fuzzy Controller ◽  
Tracking System ◽  
Processing Method ◽  
Seam Tracking ◽  
Feature Points ◽  
Vision Sensor ◽  
End Effector ◽  
Tuning Mechanism ◽  
Self Tuning

This paper presents a vision-based curve-shaped seam tracking system. The measurement of the curve trajectory is based on a camera that is installed ahead of the end effector of the robot. Effective image processing method is designed to extract the feature points of the curve. Then a fuzzy controller is proposed to control the position of the robot to track the curve. To improve the performance of the controller, a self-tuning mechanism is added to the controller. Finally, experiments are fully conducted to verify the effectiveness of the proposed method.

The Method and Experimental Research on Seam Tracking and Dual-Beam Laser Welding for T-Type Welding Seam

2014 ◽  
Vol 687-691 ◽  
pp. 309-315
Author(s):  
Ping Jiang Wang ◽  
Xin Wang ◽  
Ling Lin ◽  
Yang Wu
Keyword(s):  
Laser Welding ◽  
Machine Tool ◽  
Seam Tracking ◽  
Motion Trajectory ◽  
Vision Sensor ◽  
Cnc System ◽  
Welding Seam ◽  
Beam Laser ◽  
Dual Beam ◽  
Welding Torch

Aimed at the goal of improving the quality and the efficiency of welding for T-type welding seam, This paper put forward a method to track the seam by using the vision sensor. Machine tool main motion trajectory is generated from the numerical model of the parts. The position of two welding torches are adjusted independently based on the machine tool main motion trajectory to ensure the welding precision. Two sets of adjusting mechanism are needed for T-type welding seam. The vision sensor measure the seam and pass the deviation signal to the CNC system. The CNC system adjust the position of the welding torch installed on the cross slide table to reach the goal of seam tracking and dual-beam laser welding for T-type welding seam. Practice shows that this system for T-type welding seam dual-beam laser welding is easy to operate and can improve the quality and the efficiency.

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