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.

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.

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 Survey of Underwater Wet Weld Seam Tracking Based on Ultrasonic Sensor

2013 ◽  
Vol 433-435 ◽  
pp. 2227-2230
Author(s):  
Bo Chen ◽  
Ji Cai Feng
Keyword(s):  
Weld Seam ◽  
Welding Process ◽  
Development Trend ◽  
Ultrasonic Sensor ◽  
Seam Tracking ◽  
Signal Process ◽  
Underwater Welding ◽  
Weld Seam Tracking ◽  
Automation Control ◽  
Tracking Technology

With the exploration of marine sources becoming more and more important, underwater welding is widely needed. Because of the special working condition, underwater weld seam tracking technology is urgently needed, for the automation control of the underwater welding process is the inevitable development trend because of the rigorous environment. This paper used ultrasonic sensor to monitor the weld seam position in underwater wet welding process, and signal process algorithm was developed to obtain the weld seam information, experiment results showed that this method could detect the weld seam shape correctly, this load the foundation for further automatically controlling the 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.

A tactual weld seam tracking method in super narrow gap of thick plates

2020 ◽  
Vol 62 ◽  
pp. 101864 ◽  
Author(s):  
Ting Lei ◽  
Yu Huang ◽  
Wenjun Shao ◽  
Weinan Liu ◽  
Youmin Rong
Keyword(s):  
Weld Seam ◽  
Seam Tracking ◽  
Narrow Gap ◽  
Thick Plates ◽  
Tracking Method ◽  
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.

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