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This paper aims to overcome the limitations of low efficiency, low power density and strong electromagnetic interference (EMI) of the existing pulsed melt inert gas (MIG) welding power supply. So a novel and simplified implementation of digital high-power pulsed MIG welding power supply with LLC resonant converter is proposed in this work.

A simple parallel full-bridge LLC resonant converter structure is used to design the digital power supply with high welding current, low arc voltage, high open-circuit voltage and a wide range of arc loads, by effectively exploiting the variable load and high-power applications of LLC resonant converter.

The efficiency of each converter can reach up to 92.3%, under the rated operating condition. Notably, with proposed scheme, a short-circuit current mutation of 300 A can stabilize at 60 A within 8 ms. Furthermore, the pulsed MIG welding test shows that a stable welding process with 280 A peak current can be realized and a well-formed weld bead can be obtained, thereby verifying the feasibility of LLC resonant converter for pulsed MIG welding power supply.

The high efficiency, high power density and weak EMI of LLC resonant converter are conducive to the further optimization of pulsed MIG welding power supply. Consequently, a high performance welding power supply is implemented by taking adequate advantages of LLC resonant converter, which can provide equipment support for exploring better pulsed MIG welding processes.

The criteria importance through intercriteria correlation (CRITIC) and range of value (ROV) combined methods were used to determine a single index for all multiple responses.

This paper used cold metal transfer (CMT) and pulse metal-inert gas (MIG) welding processes to study the weld-on-bead geometry of AA2099-T86 alloy. This study used Taguchi's approach to find the optimal setting of the input welding parameters. The welding current, welding speed and contact-tip-to workpiece distance were the input welding parameters for finding the output responses, i.e. weld penetration, dilution and heat input. The L9 orthogonal array of Taguchi's approach was used to find out the optimal setting of the input parameters.

The optimal input welding parameters were determined with combined output responses. The predicted optimum welding input parameters were validated through confirmation tests. Analysis of variance showed that welding speed is the most influential factor in determining the weld bead geometry of the CMT and pulse MIG welding techniques.

The heat input and weld bead geometry are compared in both welding processes. The CMT welding samples show superior defect-free weld beads than pulse MIG welding due to lesser heat input and lesser dilution.

The paper aims to report on a new welding technology, TIP TIG.

The principle of operation and benefits of the technology are described together with a typical application.

The study finds that the technology provides the quality of TIG welding at the speeds of MIG welding, providing significant cost savings to the user.

TIP TIG provides a good opportunity for all users of robotic MIG welding to improve the quality of their product and reduce their costs.

The paper introduces a new and useful technology to the robot industry.

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.

This paper aims to characterise the hardness, tensile properties, corrosion behaviour and fatigue properties (in air and in a 3.5 per cent NaCl solution) of aluminium 6061-T651 in the as-received and as-welded conditions.

Aluminium 6061-T651 plate material, prepared with double-V or square butt joint preparations was welded using semi-mechanised or mechanised pulsed gas metal arc welding. Magnesium-alloyed ER5356 or ER5183 filler material or silicon-alloyed ER4043 filler wire was used. The material was characterised in the as-supplied and as-welded conditions, and fatigue tests were performed in air and in a 3.5 per cent NaCl solution. The fatigue results were compared to the reference fatigue design curves for aluminium published in Eurocode 9 – Part 1-3.

Significant softening, attributed to the partial dissolution and coarsening of precipitates, grain growth and recrystallisation during welding, was observed in the heat-affected zone (HAZ) of the 6061-T651 welds. During tensile testing, failure occurred in the HAZ of all 6061 welds tested. Welding reduced the room temperature fatigue life of all specimens evaluated. In 6061 welds, failure occurred preferentially in the softened HAZ of the welds. The presence of a corrosive environment (a 3.5 per cent NaCl solution in this investigation) during fatigue testing reduced the fatigue properties of all the samples tested. Corrosion pits formed preferentially at second phase particles and reduced the overall fatigue life by accelerating fatigue crack initiation.

The fatigue properties of welded aluminium structures under dynamic loading conditions have been studied extensively. Welding is known to create tensile residual stresses, to promote grain growth, recrystallisation and softening in the HAZ, and to introduce weld defects that act as stress concentrations and preferential fatigue crack initiation sites. Several fatigue studies of aluminium welds emphasised the role of precipitates, second phase particles and inclusions in initiating fatigue cracks. When simultaneously subjected to a corrosive environment and dynamic loading, the fatigue properties are often adversely affected and even alloys with good corrosion resistance may fail prematurely under conditions promoting fatigue failure. The corrosion-fatigue performance of aluminium welds has not been systematically examined to date.

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.

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.

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.

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.

General Principles of 3‐D Vision Cameras: Vision systems aimed at upgrading on‐line operations of robotic‐based processes are major advances for intelligent automation. On‐line 3D visualization of the working scenes, with appropriate features extraction and analysis, are prerequisites for innovative and modern factory fabrication. There exist several techniques for 3D imaging a work scene. Besl has classified some of them according to the following list:

Jaguar Cars has invested millions of dollars in two new facilities – a press shop and a body‐in‐white shop – to produce aluminium bodies for the next generation XJ luxury passenger car.

Fillet welding is one of the most widespread types of welding in the industry, which is still carried out manually or automated by contact. This paper aims to describe an online programming system for noncontact fillet welding robots with “U”- and “L”-shaped structures, which responds to the needs of the Fourth Industrial Revolution.

In this paper, the authors propose an online robot programming methodology that eliminates unnecessary steps traditionally performed in robotic welding, so that the operator only performs three steps to complete the welding task. First, choose the piece to weld. Then, enter the welding parameters. Finally, it sends the automatically generated program to the robot.

The system finally managed to perform the fillet welding task with the proposed method in a more efficient preparation time than the compared methods. For this, a reduced number of components was used compared to other systems: a structured light 3 D camera, two computers and a concentrator, in addition to the six-axis industrial robotic arm. The operating complexity of the system has been reduced as much as possible.

To the best of the authors’ knowledge, there is no scientific or commercial evidence of an online robot programming system capable of performing a fillet welding process, simplifying the process so that it is completely transparent for the operator and framed in the Industry 4.0 paradigm. Its commercial potential lies mainly in its simple and low-cost implementation in a flexible system capable of adapting to any industrial fillet welding job and to any support that can accommodate it.

In this study, a robotic robust system is achieved, aligned to Industry 4.0, with a friendly, intuitive and simple interface for an operator who does not need to have knowledge of industrial robotics, allowing him to perform a fillet welding saving time and increasing productivity.