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Article
Publication date: 23 January 2009

Meng Kong and Shanben Chen

The purpose of this paper is to describe work aimed to control the Al alloy welding penetration through the passive vision for welding robot.

Abstract

Purpose

The purpose of this paper is to describe work aimed to control the Al alloy welding penetration through the passive vision for welding robot.

Design/methodology/approach

First a passive vision system was established. The system can capture the Al alloy welding image. Based on the analysis of the characteristic of the welding image, the composite edge detectors were developed to recognize the shape of the weld seam and the weld pool. To realize the automatic control of the Al alloy‐weld process, the relation between the welding parameter and the quality of the weld appearance was established through the random welding experiment. The wire feed was chosen with PID controller adjusting the wire feed rate according to the weld gap variation.

Findings

This paper finds that the passive vision system can be captured the clear weld seam and weld pool image simultaneously. the method of composite edge detectors can be effectively and accurately recognize the weld seam edges. The wire feed rate controller ensured the welding robot to adjust the wire feed rate according to the gap variation.

Research limitations/implications

This system has been applied to the industrial welding robot production.

Originality/value

The weld seam and weld pool image can be simultaneously captured by the passive vision system. The composite edge detectors have been developed for the passive vision method. The controller has been set up for Al alloy welding process based on the neural network.

Details

Sensor Review, vol. 29 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 1 May 2009

Fanhuai Shi, Tao Lin and Shanben Chen

The weld seam detection is required for a welding robot to preplan the weld seam track before the actual welding. The purpose of this paper is to investigate this subject…

Abstract

Purpose

The weld seam detection is required for a welding robot to preplan the weld seam track before the actual welding. The purpose of this paper is to investigate this subject in natural lighting conditions.

Design/methodology/approach

This paper presents an efficient algorithm of weld seam detection for butt joint welding from a single image. The basic idea of the approach is to find a pair of weld seam edges in local area first. Then, starting from the two endpoints of each edge, search for the remnant edge by iterative edge detection and edge linking.

Findings

The proposed method is insensitive to the variance of the background image and can apply to most shapes of weld seams in butt joint welding.

Research limitations/implications

The proposed method is designed only for butt joint welding, and it is performed before actual welding.

Practical implications

The system is applicable to preplan the weld trajectory for most shapes of weld seams in butt joint welding. In addition, the proposed technique may have some potential applications in the field of tailor‐welded blanks.

Originality/value

The proposed algorithm is based on local image processing and detects the whole weld seam from a single image without giving any initial seam, which is insensitive to the variance of the background image and has low‐computation cost.

Details

Industrial Robot: An International Journal, vol. 36 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 22 March 2013

Zhen Ye, Gu Fang, Shanben Chen and Mitchell Dinham

This paper aims to develop a method to extract the weld seam from the welding image.

Abstract

Purpose

This paper aims to develop a method to extract the weld seam from the welding image.

Design/methodology/approach

The initial step is to set the window for the region of the weld seam. Filter and edge‐operator are then applied to acquire edges of images. Based on the prior knowledge about characteristics of the weld seam, a series of routines is proposed to recognize the seam edges and calculate the seam representation.

Findings

The proposed method can be used to extract seams of different deviations from noise‐polluted images efficiently. Besides, the method is low time‐consuming and quick enough for real time processing.

Practical implications

Weld seam extraction is the key problem in passive vision based seam tracking technology. The proposed method can extract the weld seam even when the image is noisy, and it is quick enough to be applied in seam tracking technology. The method is expected to improve seam tracking results.

Originality/value

A useful method is developed for weld seam extraction from the noise‐polluted image based on prior knowledge of weld seam. The method is robust and quick enough for real time processing.

Details

Sensor Review, vol. 33 no. 2
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 17 August 2012

Yanling Xu, Huanwei Yu, Jiyong Zhong, Tao Lin and Shanben Chen

The purpose of this paper is to analyze the technology of capturing and processing weld images in real‐time, which is very important to the seam tracking and the weld

1020

Abstract

Purpose

The purpose of this paper is to analyze the technology of capturing and processing weld images in real‐time, which is very important to the seam tracking and the weld quality control during the robotic gas tungsten arc welding (GTAW) process.

Design/methodology/approach

By analyzing some main parameters on the effect of image capturing, a passive vision sensor for welding robot was designed in order to capture clear and steady welding images. Based on the analysis of the characteristic of the welding images, a new improved Canny algorithm was proposed to detect the edges of seam and pool, and extract the seam and pool characteristic parameters. Finally, the image processing precision was verified by the random welding experiments.

Findings

It was found that the seam and pool images can be clearly acquired by using the passive vision system, and the welding image characteristic parameters were accurately extracted through processing. The experiment results show that the precision range of the image processing can be controlled about within ±0.169 mm, which can completely meet the requirement of real‐time seam tracking for welding robot.

Research limitations/implications

This system will be applied to the industrial welding robot production during the GTAW process.

Originality/value

It is very important for the type of teaching‐playback robots with the passive vision that the real‐time images of seam and pool are acquired clearly and processed accurately during the robotic welding process, which helps determine follow‐up seam track and the control of welding quality.

Details

Industrial Robot: An International Journal, vol. 39 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 23 August 2011

Shanchun Wei, Meng Kong, Tao Lin and Shanben Chen

This paper aims to develop a method to achieve automatic robotic welding and seam tracking so that three‐dimensional weld seam could be tracked without teaching and good…

Abstract

Purpose

This paper aims to develop a method to achieve automatic robotic welding and seam tracking so that three‐dimensional weld seam could be tracked without teaching and good welding formation could be accomplished.

Design/methodology/approach

Adaptive image processing method was used for various types of weld seam. Also the relationship between welding height and arc signal was calibrated. Through the decomposition and synthesis, three‐dimensional space type weld seam could be extracted and tracked well. The workpiece without teaching was finally tracked precisely and in a timely way with use of the fuzzy controller.

Findings

Composite sensing technology including arc and visual sensing had obvious advantages. Image processing method could be used for tracking plane weld seam efficiently while arc sensing could characterize welding height. Through the coupled controlling algorithm, arc sensing and visual sensing could be fused effectively.

Research limitations/implications

How to couple information more accurately and quickly was still one of the most important problems in composite sensing technology.

Practical implications

Composite sensing technology could reduce costs to achieve weld seam instead such expensive device as laser sensor. The simulating parts of scalloped segment of bottom board for rockets were tracked in the project. Once more adaptive algorithms were developed, more complicated practical workpieces could be dealt with in robotic welding which promotes the application of industry robots.

Originality/value

A useful method for three‐dimensional space type weld seam tracking without teaching was developed. The whole procedure of adaptive image processing method was simple but efficient and robust. The coupled controlling strategy addressed could accomplish seam tracking by composite sensing technology.

Details

Industrial Robot: An International Journal, vol. 38 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 23 October 2007

H.Y. Shen, H.B. Ma, T. Lin and S.B. Chen

The control of weld penetration in gas tungsten arc welding (GTAW) is required for a “teach and playback” robot to overcome the gap variation in the welding process. This…

1042

Abstract

Purpose

The control of weld penetration in gas tungsten arc welding (GTAW) is required for a “teach and playback” robot to overcome the gap variation in the welding process. This paper aims to investigate this subject.

Design/methodology/approach

This paper presents a robotic system based on the real‐time vision measurement. The primary objective has been to demonstrate the feasibility of using vision‐based image processing to measure the seam gap in real‐time and adjust welding current and wire‐feed rate to realize the penetration control during the robot‐welding process.

Findings

The paper finds that vision‐based measurement of the seam gap can be used in the welding robot, in real‐time, to control weld penetration. It helps the “teach and playback” robot to adjust the welding procedures according to the gap variation.

Research limitations/implications

The system requires that the seam edges can be accurately identified using a correlation method.

Practical implications

The system is applicable to storage tank welding of a rocket.

Originality/value

The control algorithm based on the knowledge base has been set up for continuous GTAW. A novel visual image analysis method has been developed in the study for a welding robot.

Details

Industrial Robot: An International Journal, vol. 34 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 19 November 2021

Yanbiao Zou and Hengchang Zhou

This paper aims to propose a weld seam tracking method based on proximal policy optimization (PPO).

Abstract

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.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 21 August 2017

Yanbiao Zou, Jinchao Li and Xiangzhi Chen

This paper aims to propose a set of six-axis robot arm welding seam tracking experiment platform based on Halcon machine vision library to resolve the curve seam tracking issue.

Abstract

Purpose

This paper aims to propose a set of six-axis robot arm welding seam tracking experiment platform based on Halcon machine vision library to resolve the curve seam tracking issue.

Design/methodology/approach

Robot-based and image coordinate systems are converted based on the mathematical model of the three-dimensional measurement of structured light vision and conversion relations between robot-based and camera coordinate systems. An object tracking algorithm via weighted local cosine similarity is adopted to detect the seam feature points to prevent effectively the interference from arc and spatter. This algorithm models the target state variable and corresponding observation vector within the Bayes framework and finds the optimal region with highest similarity to the image-selected modules using cosine similarity.

Findings

The paper tests the approach and the experimental results show that using metal inert-gas (MIG) welding with maximum welding current of 200A can achieve real-time accurate curve seam tracking under strong arc light and splash. Minimal distance between laser stripe and welding molten pool can reach 15 mm, and sensor sampling frequency can reach 50 Hz.

Originality/value

Designing a set of six-axis robot arm welding seam tracking experiment platform with a system of structured light sensor based on Halcon machine vision library; and adding an object tracking algorithm to seam tracking system to detect image feature points. By this technology, this system can track the curve seam while welding.

Details

Industrial Robot: An International Journal, vol. 44 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 1 May 2009

Hong Yue, Kai Li, Haiwen Zhao and Yi Zhang

The purpose of this paper is to introduce structured light image processing technology into pipeline welding automation projects, and develop a vision‐based pipeline girth…

Abstract

Purpose

The purpose of this paper is to introduce structured light image processing technology into pipeline welding automation projects, and develop a vision‐based pipeline girth‐welding robot. The welding torch can accurately track the weld and complete the omni‐orientation welding automatically.

Design/methodology/approach

Weld image processing adopts the base theory including Laplacian of Gaussian filter, neighbourhood mean filter, largest variance threshold segmentation and morphologic, etc. obtains good effect of weld recognition.

Findings

The paper uses a vision sensor to achieve the weld character's recognition and extraction, directly control the robot tracking weld to complete automation welding. Compared with the existing pipeline welding devices, it does not need the lay orbit or plot tracking mark, which can shorten the assistant time to improve the productivity.

Practical implications

The research findings can satisfy the need of whole‐directional automation welding for large diameter transportation pipe's circular abutting weld. It fits for the automation welding for the long‐distance transportation pipe of petroleum, natural gas, and water.

Originality/value

Aiming at the character recognition and extract of V‐type weld, the method combining the neighbourhood mean filter algorithm with the largest variance threshold segmentation is proposed to obtain the quick weld image processing speed.

Details

Industrial Robot: An International Journal, vol. 36 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 28 August 2007

Hai Chao Li, Hong Ming Gao and Lin Wu

This paper aims to develop a performing approach for telerobotic arc welding in an unstructured environment.

Abstract

Purpose

This paper aims to develop a performing approach for telerobotic arc welding in an unstructured environment.

Design/methodology/approach

A teleteaching approach is presented for an arc welding telerobotic system in an unstructured environment. Improved laser vision sensor enhances the precision of teleteaching welding seam. Stereoscopic vision display system is developed to provide the perception information of remote environment that increased the dexterity of the teleteaching process. Operator interacts with the system by welding multi‐modal human‐machine interface, which integrated the teleteaching operation window, status display window and space mouse.

Findings

The sensor‐based teleteaching approach, which integrated laser vision sensing and stereoscopic vision display, can perform arc welding of most welding seam trajectory in an unstructured environment. The approach releases the payload of human operator and improves adaptability of the arc welding system.

Research limitations/implications

The paper provides the remote welding telerobotic approach that is gentle to most unstructured environments.

Practical implications

The sensor‐based teleteaching approach provides the capability of a telerobotic system used in remote welding field, which can shorten the incident response time and maintenance period of nuclear plants, space and underwater.

Originality/value

This paper introduces the sensor‐based teleteaching concept and performing procedure to be used for remote telerobotic arc welding.

Details

Industrial Robot: An International Journal, vol. 34 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

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