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The purpose of this paper was to use visual and arc sensors to simultaneously obtain the underwater wet welding information, and a weld seam-forming model was made to predict the weld seam's geometric parameters. It is difficult to obtain a fine welding quality in underwater welding because of the intense disturbances of the water environment. To automatically control the welding quality, the weld seam-forming model should first be established. Thus, the foundation was laid for automatically controlling the underwater welding seam-forming quality.

Visual and arc sensors were used simultaneously to obtain the weld seam image, current and voltage information; then signal algorithms were used to process the information, and the back propagation (BP) neural network was used to model the process.

Experiment results showed that the BP neural network model could precisely predict the weld seam-forming parameters of underwater wet welding.

A weld seam-forming model of underwater wet welding process was made; this laid the foundation for establishing a controller for controlling the underwater wet welding process automatically.

Welding is becoming increasingly unacceptable as a manual job and this is causing an acceleration in the trend towards automation. This paper briefly reviews some recent efforts at automating welding processes, including a program in the UK by the National Engineering Laboratory and the Welding Institute, and considers the future progress and effects of automation in this field.

The purpose of this paper is to establish a three-dimensional flow field model of the Invar alloy laser–metal inert gas (laser–MIG) hybrid welding process to investigate the influence of different heat sources between different layers and to analyze the flow field based on the two different heat source models for the multilayer welding.

The Invar steel plates with 19.5 mm thickness are welded into three layers’ seam using the hybrid laser–MIG welding technology. The flow field based on different heat source models is studied and then used to investigate the influence of different heat sources in different layers during the laser–MIG hybrid welding process. The simulation results of flow field using two different heat source models are compared with experiments.

The flow field simulations results show that using the Gaussian rotating body heat source model to simulate the temperature field is more consistent with the experiment of the hybrid laser–MIG welding where its flow field between different layers better reflects the characteristics of the hybrid laser–MIG welding.

The findings will be useful in the study of a variety of thick-plate laser–MIG hybrid welding process fluid flows.

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

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.

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.

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

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.

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

The purpose of this paper is to provide a modified welding image feature extraction algorithm for rotating arc narrow gap metal active-gas welding (MAG) welding, which is significant for improving the accuracy and reliability of the welding process.

An infrared charge-coupled device (CCD) camera was utilized to obtain the welding image by passive vision. The left/right arc position was used as a triggering signal to capture the image when the arc is approaching left/right sidewall. Comparing with the conventional method, the authors’ sidewall detection method reduces the interference from arc; the median filter removes the welding spatter; and the size of the arc area was verified to reduce the reflection from welding pool. In addition, the frame loss was also considered in the authors’ method.

The modified welding image feature extraction method improves the accuracy and reliability of sidewall edge and arc position detection.

The algorithm can be applied to welding seam tracking and penetration control in rotating or swing arc narrow gap welding.

The modified welding image feature extraction method is robust to typical interference and, thus, can improve the accuracy and reliability of the detection of sidewall edge and arc position.

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.

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.

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.

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.

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.

Bimetallic composite pipe consists of a corrosion resistance alloy (CRA) layer for corrosion resistance and carbon steel for mechanical properties, which shows a promising prospect of gathering pipeline with its effective-cost and reliable corrosion resistance. However, the corrosion resistance of composite pipe is determined by the quality of its welding gap. This paper aims to investigate the TIG welding gap corrosion resistance of X52/825 metallurgical clad pipe in H₂S/CO₂ environment.

Corrosion tests of X52/825 welding gap were performed in a stimulated gas field solution containing both 1 MPa CO₂ and 1.5 MPa H₂S at 70°C for 720 h in a self-designed high temperature and high pressure autoclave. The anti-stress corrosion cracking (SCC) performance of X52/825 clad pipe ring root welding gap was investigated in both NACE A solution and the stimulant gas field solution by four point bending testing and constant load test. Then the experiments were rerun in XX high sour gas well. In addition, the alloy diffusion and microstructure characteristics of TIG welding gap were analyzed through scanning electron microscopy and energy dispersive X-ray spectroscopy technologies.

The results reveal that the root welding gap is almost not corroded in the stimulant gas field solution, and no micro-cracks were observed by electron microscope. Anti-SCC test results show the root welding gap does not break, indicating a good resistance to environmental-cracking in H₂S/CO₂ environment. The transition layer can be obviously observed in the root welding zone, and the alloy content of transition layer is diluted. However, the transition layer does not penetrate into the inner of CRA layer, which illustrates its good anti-corrosion performance. Therefore, TIG welding technology can be well used in the welding process of composite pipe.

This paper may provide theoretical reference for manufacturing and application of clad pipe.

Development and demonstration of an autonomous, mobile welding robot capable of fabricating large‐scale customised structures.

An autonomous welding robot has been developed under the EC Framework V Growth program. The system comprises a global vision system for part location and orientation, and a robot transport vehicle (RTV) which carries a 6‐axis robot, robot controller, welding equipment, and local sensors at the welding torch. The RTV path, robot arm motion and weld process programming are performed automatically using sensors and specially customised simulation software.

The technology developed within the project was demonstrated, in November 2004, to be capable of identifying and welding large scale customised structures as found in the earth moving equipment and bridge fabrication industries.

The project demonstrated that current sensor technology is capable of being applied successfully to autonomous robots, but further developments in sensor technology are required to improve accuracy and joint access.

The NOMAD concept of autonomous mobile robots provides an alternative solution to welding mass customised structures.

This project demonstrated, for the first time, the capability of autonomous robots to weld large scale customised structures.

This paper outlines the range of robots available and in use in Britain for arc welding, and gives examples of typical current industrial applications. Work at the National Engeering Laboratories and the Welding Institute has the objective of increasing the range and ease of robot arc welding, and recent developments in this area are introduced.

Shielded metal arc welding (SMAW) is a typical manual process with many important but dangerous applications for the welder. The purpose of this paper is to present a methodology developed for execution time trajectory generation for robotic SMAW which offers greater safety and improved weld quality and repeatability.

The study presents a methodology developed for execution time trajectory generation for the robotic SMAW. In this methodology, while the electrode is melted the robot makes the diving movement, keeping the electric arc length constant. The trajectory is generated during execution time as a function of melting rate and independent of the welding speed, given by the welding parameters. The proposed methodology uses a variable tool center point (TCP) model where the covered electrode is considered a prismatic joint, whose displacement is determined by the melting rate.

The proposed methodology was implemented in a KUKA robot. The electrode melting rate was determined by measuring the arc voltage and the electrode holder trajectory was determined during the weld, keeping the arc length and the welding speed constant. All the obtained weld beads have the same aspect, showing the process repeatability.

Owing to its low productivity, robotic SMAW is only suitable to certain applications.

With this methodology, the TCP will always be located at the tip of the electrode (melting front), allowing one to program the welding speed independently of the electrode diving speed. The diving movement is automatically performed by the robot during the welding.

Robotic SMAW allows dangerous applications such as underwater welding and hot tapping of pipes without human intervention during the weld.