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A welding robot is a complicated system with uncertainty, time-varying, strong coupling and non-linear system. It is more complicated if it is used in an underwater environment. It is difficult to establish an accurate dynamic model for an underwater welding robot. Aiming at the tracking control of an underwater welding robot, it is difficult to achieve the control performance requirements by the classical proportional integral derivative control method to realize automatic tracking of the seam. The purpose of this paper is to suggest a novel method to deal with these issues.

To combine the advantages of active disturbance rejection control (ADRC) and sliding mode control (SMC) to improve the shortcomings of a single control method, a hybrid control method for an underwater welding robot trajectory tracking based on SMC_ADRC is proposed in this research work.

The simulation experiment of the proposed approach is carried out by Matlab/Simulink, and the welding experiment is recorded. The seam gets plumper and smoother, with better continuity and no undercut phenomenon.

The proposed approach is effective and reliable, and the system’s tracking performance is stable, which can effectively reduce chattering and improve system robustness.

An active disturbance rejection controller (ADRC) based on model compensation is proposed in this paper. The method should first be taken a nominal model of the robot to compensate. Subsequently, the uncertain external disturbance is estimated and compensated is used an expansion state observer (ESO) in real time, which can reduce the estimating range of observation for ESO. The purpose of this paper is to suggest a novel method to improve the system tracking performance, as well as the dynamic and static performance index.

A welding robot is a complicated system with uncertainty, time-varying, strong coupling and a nonlinear system; it is more complex as if it is used in an underwater environment, and it is difficult to establish an accurate dynamic model for an underwater welding robot. Aiming at the tracking control of an underwater welding robot, it is difficult to achieve the control performance requirements by the conventional proportional integral derivative method to realize automatic tracking of the seam.

The simulation experiment is carried out by MATLAB/Simulink, and the application experiment is recorded. The experimental results show that the control method is correct and effective, and the system’s tracking performance is stable, and the robustness and tracking accuracy of the system are also improved.

The seam gets plumper and smoother, with better continuity and no undercut phenomenon.

The purpose of this study is to develop a new positioning method for remotely operated vehicle (ROV) in the nuclear power plant. The ROV of the nuclear power plant is developed to inspect the reactor cavity pools, the component pools and spent-fuel storage pools. To enhance the operational safety, the ability of localizing the ROV is indispensable.

Therefore, the positioning method is proposed based on the MEMS inertial measurement unit and mechanical scanning sonar in this paper. Firstly, the ROV model and on board sensors are introduced in detail. Then the sensor-based Kalman filter is deduced for attitude estimation. After that, the positioning method is proposed that divided into static positioning and dynamic positioning. The improved iterative closest point-Kalman filter is deduced to estimate the global position by the whole circle scanning sonar data in static, and the relative positioning method is proposed by the small scale scanning sonar data in dynamic.

The performance of the proposed method is verified by comparing with the visual positioning system. Finally, the effectiveness of the proposed method is proved by the experiment in the reactor simulation pool of the Daya Bay Nuclear Power Plant.

The research content of this manuscript is aimed at the specific application needs of nuclear power plants and has high theoretical significance and application value.

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.

This paper aims to propose a diverless weld bead maintenance welding technology to prevent the leakage of subsea oil and gas pipeline and solve the key problems in the maintenance of subsea pipeline.

Based on the analysis of the cross-section of the fillet weld, the multi-layer and multi-pass welding path planning of the submarine pipeline sleeve fillet weld is studied, and thus a multi-layer and multi-pass welding path planning strategy is proposed. A welding seam filling method is designed, and the end position of the welding gun is planned, which provides a theoretical basis for the motion control of the maintenance system.

The trajectory planning and adjustment of multi-layer and multi-pass fillet welding and the motion stability control of the rotating mechanism are realized.

It provides the basis for the prototype design of the submarine pipeline maintenance and welding robot system, and also lays the foundation for the in-depth research on the intelligent maintenance system of submarine pipeline.

The maintenance of diverless subsea pipeline is a new type of maintenance method, which can solve the problem of large amount of subsea maintenance work with high efficiency.

Examines research work to investigate the potential of using robot manipulators for underwater ultrasonic testing of welds in joints of complex geometry. Describes experiments carried out into non‐contact ultrasonic immersion testing using a six‐axis robot and an ultrasonic inspection system and gives results from scanning of a small T‐node specimen. Concludes that since the work described was carried out a prototype five axis scanning device has been developed which is capable of full underwater operation.

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.

This study aims to improve the welding quality and efficiency, and an algorithm should be designed to realize tracking space-curved fillet weld joints.

Fillet weld joints tracking based on the two wheels and the horizontal slider coordinated movement has been studied. The method of pattern recognition is used to identify the height deviation, and the analysis of the accuracy corresponding to recognizing height deviations has been researched. The proportional control algorithm is used to control the vertical and horizontal sliders movement, so fillet weld joints tracking in the height direction has been achieved. Based on wheels and vertical and horizontal sliders coordinated movement, the algorithm of space-curved fillet weld joints tracking has been researched.

Some experiments have been done, and experimental results show that the welding robot can track space-curved fillet weld joints with high accuracy and good reliability.

The welding robot can improve the welding quality and efficiency.

The welding robot can track fillet weld joints in ship panels, and it was shown that the welding robot could track space-curved fillet weld joints with high accuracy and good reliability.

The welding robot has many industrial and social applications.

There are various forms of fillet weld joints in the industry, and the fillet weld is curved in the space. Experimental results show that the welding robot can track space-curved fillet weld joints with good stability and high precision.

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.

The purpose of this paper is to develop a novel autonomous in‐pipe robot to perform the preventive point reparation for long‐distance offshore oil pipelines.

The autonomous in‐pipe robot performs online ultrasonic inspection for pipe wall thickness, and the original inspection data are stored in large capacity hard disk. Through the offline data analysis by the data analysts and the software tool, the pipeline health status is known. If server defects lie there, the in‐pipe robot is introduced into the pipeline once more to indicate the defect's location to the maintenance ship.

The laboratory tests and the field tests prove the feasibility and validity of the developed autonomous in‐pipe robot. Furthermore, the application of intelligent control techniques ensures the mission completion by the autonomous in‐pipe robot, which worked in the awful pipeline environment.

The developed autonomous in‐pipe robot helps eliminate lost production costs and pipeline downtime caused by leakages and guarantees the safe run of offshore oil pipelines.

For the application of the autonomous in‐pipe robot, there are no special requirements for maintained pipelines themselves, so it is applicable to the point reparation for most long‐distance welded offshore pipelines.