The Review of the Welding Robot’s Precision

Welding is an significant link in industrial production,and it is known as the"industrial tailor".However,welding fume,arc light,and metal spatter cause a harsh welding working environment,and the quality of welding has a decisive influence on product quality.Low production capacity,difficult recruitment,and low profits have become drawbacks for the development of the welding field.Combining traditional welding with robots can solve these drawbacks and increase the precision of welding.Welding robots are industrial robots engaged in welding and are mostly used in large-scale manufacturing fields such as automobile manufacturing.Welding robots are divided into spot welding robots,arc welding robots and laser welding robots.In addition,body accuracy and control accuracy are the two main factors that affect the robot welding accuracy.In this case,the sensing technology of welding robot is also essential.

Digital Twin Implementation of Autonomous Planning Arc Welding Robot System

Industrial robots are currently applied for ship sub-assembly welding to replace welding workers because of the intelligent production and cost savings.In order to improve the efficiency of the robot system,a digital twin system of welding path planning for the arc welding robot in ship sub-assembly welding is proposed in this manuscript to achieve autonomous planning and generation of the welding path.First,a five-dimensional digital twin model of the dual arc welding robot system is constructed.Then,the system kinematics analysis and calibration are studied for communication realization between the virtual and the actual system.Besides,a topology consisting of three bounding volume hierarchies(BVH)trees is proposed to construct digital twin virtual entities in this system.Based on this topology,algorithms for welding seam extraction and collision detection are presented.Finally,the genetic algorithm and the RRT-Connect algorithm combined with region partitioning(RRT-Connect-RP)are applied for the welding sequence global planning and local jump path planning,respectively.The digital twin system and its path planning application are tested in the actual application scenario.The results show that the system can not only simulate the actual welding operation of the arc welding robot but also realize path planning and real-time control of the robot.

Optimal Posture Searching Algorithm on Mobile Welding Robot

An independently developed mobile welding robot system is introduced. Kinematics model is the base of robot planning. With the Denavit-Hartenberg method, robot kinematics equation can be gotten. The robot welding torch inclination angle consists of the working and moving angles. According to the kinematics model,both the two angles and torch position can be calculated. Under special moving angle, a two-step algorithm is used to obtain the optimal manipulator posture. The calculation result shows that the algorithm has high precision.

On-Line Detection of Porosity in Gas Tungsten Arc Welding of Aluminum Alloy Based on Spectrum Features

The real-time detection of porosity in welding process is an important problem to be solved in intelligent welding manufacturing.A new on-line detection method for porosity of aluminum alloy in robotic arc welding based on arc spectrum is proposed in this paper.First,k-shape and the improved k-means were used for the initial feature selection of the preprocessed arc spectrum to reduce the data dimension.Second,the secondary feature selection was carried out based on the importance of features to further reduce feature redundancy.Then,the optimal sample label library was established by combining the final characteristic parameters and the X-ray pictures of welds.Finally,an on-line detection method of porosity in gas tungsten arc welding of aluminum alloy based on light gradient boosting machine(LightGBM)was proposed.Compared with extreme gradient boosting(XGBoost)and categorical boosting(CatBoost),this method can achieve better detection performance.The new method proposed in this paper can be used to detect other welding defects,which is helpful to the development of intelligent welding technology.