Vision-Based Seam Tracking in Robotic Welding: A Review of Recent Research

2020 ◽  
pp. 61-86
Author(s):  
Ziheng Wang ◽  
Yanling Xu
Keyword(s):  
Seam Tracking ◽  
Robotic Welding

scholarly journals Research on the Deviation Sensing of V-groove Weld Seam based on a Novel Two Channel Acoustic Sensor

2021 ◽  
Author(s):  
Yanfeng Gao ◽  
Jianhua Xiao ◽  
Genliang Xiong ◽  
Hua Zhang
Keyword(s):  
Weld Seam ◽  
Welding Process ◽  
Simulation Method ◽  
Seam Tracking ◽  
Acoustic Sensor ◽  
Robotic Welding ◽  
Weld Seam Tracking ◽  
Novel Method ◽  
Linear Property ◽  
Sensing Performance

Abstract It is essential to sense the deviation of weld seam real-timely in robotic welding process. However, welding process always accompanied with high temperature, strong arc light and background noises, which significantly affects the application of sensors. In this study, a novel acoustic sensor was developed. This sensor consists of two microphones. Based on the sound signals collected by these two microphones, the deviation of weld seam was detected. The frequency response of the developed acoustic sensor was studied through simulation method firstly, and then the sensing performance of it was analyzed with experiments. The experimental results show that the developed acoustic sensor has a linear property for the deviation detection of V-groove weld seam. This research provides a novel method for weld seam tracking.

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.

Applications of Robotics in Welding

2018 ◽  
Vol 7 (3) ◽  
pp. 30
Author(s):  
Tanveer Majeed ◽  
Mohd Atif Wahid ◽  
Faizan Ali
Keyword(s):  
Control System ◽  
Industrial Robot ◽  
Seam Tracking ◽  
Effective Control ◽  
Welding Parameters ◽  
Profile Measurement ◽  
Robotic Welding ◽  
Intelligent Control System ◽  
Joint Location ◽  
Welding Processes

An Industrial robot is reprogrammable, automatically controlled, multifunctional manipulator programmable in three or more axes, which may be either fixed in place or mobile for use in industrial automation applications. Technical innovations in robotic welding has facilitated manual welding processes in sever working conditions with enormous heat and fumes to be replaced with robotic welding. The robotic welding has greater capability to control robot motion, welding parameters and enhanced wrong detection and wrong correction. Major difficulties in robotic welding are joint edge inspection, weld penetration control, seam tracking of joints, and width or profile measurement of a joint. These problems can be more easily solved by use of sensory feedback signals from weld joint.  Robotic welding system has intelligent and effective control system that can track the joint, monitor the joint in process and accounts for variation in joint location. Sensors play an important role in robotic welding systems with adaptive and intelligent control system features that can track the joint, account for variation in joint location and geometry monitor in-process quality of the weld. In this paper various aspects of robotic welding, robot programming, and problems associated with robot welding are undertaken.

An Optimal Image Processing Method for Simultaneous Detection of Weld Seam Position and Weld Gap in Robotic Arc Welding

2020 ◽  
pp. 1341-1357
Author(s):  
Amruta Rout ◽  
Deepak BBVL ◽  
Bibhuti Bhusan Biswal ◽  
Golak Bihari Mahanta ◽  
Bala Murali Gunji
Keyword(s):  
Image Processing ◽  
Path Planning ◽  
Edge Detection ◽  
Weld Seam ◽  
Industrial Robot ◽  
Simultaneous Detection ◽  
Seam Tracking ◽  
Robotic Welding ◽  
Labview Software ◽  
Edge Detection Method

For robot path planning the weld seam positions need to be known in advance as the industrial robot generally work in teach and playback mode. In this paper, a vision sensor has been utilized for automation of robotic welding path planning. A seam tracking algorithm has been proposed for a butt type of weld joint with varying weld gap for effective measurement of weld path positions and weld gap simultaneously. For this first an image acquisition algorithm technique has been proposed for capturing of image of weld seam in gray scale mode. Then in image processing at first one pattern matching algorithm for tracking of weld seam path is performed. Then different edge detection techniques have been applied to find the most efficient edge detection method for obtaining the characteristics of weld seam edge. Then best edge fitting method has been applied to fit the edges along the weld seam edge and the pixel values on the edges were measured. The weld gap and the midpoint between edges points are measured simultaneously by vision assistant toolbox in LabVIEW software background.

Modern tracking methods of the weld seams for robotic welding based on laser vision

2021 ◽  
Author(s):  
Keyword(s):  
Control System ◽  
Seam Tracking ◽  
Automatic Welding ◽  
Robotic Welding ◽  
Welding Seam ◽  
Advantages And Disadvantages ◽  
Laser Sensors ◽  
Vision Sensors ◽  
Laser Vision ◽  
Weld Seams

Laser sensors with various technologies used to track weld seams during welding operations are discussed in detail Laser vision sensors provide full automation of welding robotic systems and real-time process monitoring. Reasonable selection of the control system for a robotic welding system with laser vision is represented. Based on the analysis of the advantages and disadvantages, the practical application of laser vision sensors in the process of automatic welding is predicted. Keywords weld seam tracking; laser vision sensor; robotic welding; seam recognition; pre-processing of images; structure of the control system

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.

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