Welding is a method of realizing material connections, and the development of modern sensing technology is pushing this traditional process towards automation and intelligence. Among many sensing methods, visual sensing stands out with its advantages of non-contact, fast response and economic benefits, etc. This paper provides a comprehensive review of visualization methods in the context of specific welding processes in the following five aspects. The problem of IWP location is summarized from two directions of active and passive vision. Weld seam identification and tracking methods are discussed in detail based on the morphological characteristics of the weld seam. The feasibility of different weld path planning methods is analyzed based on the point cloud information and the composite vision information. Two types of monitoring means based on infrared sensing and visible light sensing are summarized taking into account the thermal and morphological characteristics of the weld pool, and welding defect detection technology is summarized by comparing the intelligent detection algorithms and the traditional detection algorithms. Finally, by combining the existing developments in computer technology, composite sensing technology, machine learning technology, and multi-robot control technology, the article concludes with a summary and trends in the development of automated welding technologies. 

Progress, challenges and trends on vision sensing technologies in automatic/intelligent robotic welding: State-of-the-art review

Plane welds are a common type of weld in industrial sites. When the welding robot welds multiple types of plane welds at the same time, the traditional teaching and programming modes become relatively complicated. Therefore, in order to solve the problem of automatic robot welding of various types of plane welds, taking plane V-type butt, plane I-type butt, and plane lap welds as examples, this paper proposes a plane weld extraction method based on 3D vision. Firstly, in order to realize the line and plane segmentation of the workpiece point cloud, we establish the concept of plane point cloud density. Secondly, to segment workpiece edge lines, an iterative segmentation algorithm based on RANSAC is proposed. Then, based on the geometric features of the workpiece, a method for extracting weld feature points based on centroid positioning is proposed. Finally, the least squares method is used to fit the feature points of the welding seam to complete the welding trajectory planning. The experimental results show that the method can well solve the problem of automatic planning welding trajectory of plane V-type butt, plane I-type butt, and plane lap welds, to realize that the welding robot can simultaneously weld various plane welds without teaching and programming. 

/pdf/a-point-cloud-based-welding-trajectory-planning-method-for-2rra3w33.pdf

A point cloud-based welding trajectory planning method for plane welds

WeldNet: A voxel-based deep learning network for point cloud annular weld seam detection

This paper presents a method for extracting intersecting pipelines weld seam based on point cloud. Firstly, the collected point cloud is filtered by PassThrough filter to extract the region of interest, and the intersecting pipelines model is reconstructed by using the camera calibration results and the pose of robot. Then VoxelGrid filtering and Moving Least Squares filtering are performed on the reconstructed model to smooth the error caused by camera and robot. The Fast Point Feature Histograms of point cloud is used to calculate the entropy map, and the weld seam region is extracted by threshold segmentation. Finally, an iterative algorithm for weld point extraction based on entropy is proposed. Through experimental verification, the algorithm can extract the weld points of the actual intersecting pipelines and obtain the real position of the weld points in the robot base coordinate frame, which has great application value in robot automatic welding area. 

Weld Seam Extraction of Intersecting Pipelines Based on Point Cloud Entropy

Photogrammetry has gained the interest of professionals and researchers for activities related to construction projects’ progress monitoring via attaining precise 3D point models. However, the precision of the generated models is directly linked with the precise scaling of the point cloud to ground truth dimensions (GTDs). Available scaling-up procedures for the close-range photogrammetry technique are complex, time consuming, and require human intervention, which adds the risk of error in the scaled-up model dimensions. Such a scenario creates hesitation among industry professionals toward implementing point cloud technologies. This paper devises an automated scaling-up methodology to overcome the said concerns by considering the construction progress monitoring theme. The intact process of automated scaling up of point cloud model to GTDs is controlled by two main parameters, that is, Python-based modules and designed ArUco-supported controlled markers. Remarkable outcomes are achieved with less than 1% scaled-up error compared with GTDs, which will improve the confidence of industry professionals toward point cloud technologies. 

Automated Scaling of Point Cloud Rebar Model via ArUco-Supported Controlled Markers

Identification of the seam to be welded in automatic welding is an important challenge, especially on a complex 3D surface. At present, most studies on weld extraction are for butt joints and fillet joints. Few studies focus on D-type welds, which connect to pipelines or pressure vessels. In this paper, a method of identification and extraction of pipeline joint welds based on 3D point clouds is proposed. First, the problem that the surface of pipe fittings cannot be effectively stitched owing to lack of markings is solved by putting marker points on the surface to allow accurate splicing of the point cloud. Second, according to the contour feature information of the workpiece, a processing method for D-type welding seams is proposed. Finally, a boundary extraction algorithm based on the point cloud normal is used to obtain the point cloud of the weld. The experimental results show that this method can effectively extract the weld. The running time for the point cloud weld extraction method is less than half that of the existing methods. The accuracy of the proposed method is improved in all three directions: by 28.2% in the X direction, 19.1% in the Y direction and 16.0% in the Z direction. Moreover, this method is convenient for transforming weld coordinates to robot-based coordinates for the automatic welding of spatially complex welds.

/pdf/a-method-of-d-type-weld-seam-extraction-based-on-point-1ddibxagzg.pdf

A Method of D-Type Weld Seam Extraction Based on Point Clouds

In view of the classical visual servoing trajectory planning method which only considers the camera trajectory, this paper proposes one homography matrix based trajectory planning method for robot uncalibrated visual servoing. Taking the robot-end-effector frame as one generic case, eigenvalue decomposition is utilized to calculate the infinite homography matrix of the robot-end-effector trajectory, and then the image feature-point trajectories corresponding to the camera rotation is obtained, while the image feature-point trajectories corresponding to the camera translation is obtained by the homography matrix. According to the additional image corresponding to the robot-end-effector rotation, the relationship between the robot-end-effector rotation and the variation of the image feature-points is obtained, and then the expression of the image trajectories corresponding to the optimal robot-end-effector trajectories (the rotation trajectory of the minimum geodesic and the linear translation trajectory) are obtained. Finally, the optimal image trajectories of the uncalibrated visual servoing controller is modified to track the image trajectories. Simulation experiments show that, compared with the classical IBUVS method, the proposed trajectory planning method can obtain the shortest path of any frame and complete the robot visual servoing task with large initial pose deviation.

pdf/homography-matrix-based-trajectory-planning-method-for-robot-2ozzbqbk.pdf

Homography matrix based trajectory planning method for robot uncalibrated visual servoing

Laser soldering is a crucial soldering technique in the realm of electronic assembly. The temperature of the solder joint is intimately connected with the quality of the solder. This paper introduces an adjustable power upper limit variable-structure Proportional–Integral–Derivative (PID) intelligent control method for regulating the temperature of the solder joint during laser soldering. Distinct laser power limits are employed for workpieces with varying heat capacities. The solder joint temperature is monitored through an infrared thermometer, which enables closed-loop temperature control via a variable-structure PID algorithm. Residual neural network (ResNet) models are utilized to predict key soldering process parameters. This method has been executed and validated on a practical testing platform. Compared to other laser soldering control techniques, the proposed method demonstrates a low overshoot, rapid dynamic response, and swift adjustment capabilities, effectively enhancing the soldering quality and production efficiency.

Variable-Structure Proportional–Integral–Derivative Laser Solder Joint Temperature Intelligent Control Method with Adjustable Power Upper Limit

To address the high-precision thermal control requirements of semiconductor lasers in laser soldering applications, we propose a thermal control method based on long short-term memory model predictive control (LSTM-MPCs). First, we constructed precise mathematical models for the thermoelectric cooler and components of the thermal control system using non-equilibrium thermodynamics and other methods. The LSTM-MPC thermal control system was derived by introducing the diophantine equation, and an experimental platform for the thermal control of semiconductor lasers in laser soldering was established. The experimental results from random current input variations showed that the average temperature overshoot caused by changes in the laser input current remained within 0.86%. The stability of the laser’s central wavelength improved, with the proposed method reducing the central wavelength drift by 88%. In laser soldering performance experiments, this control method effectively controlled the output power of the semiconductor laser, enhancing the linear fit of the weld point temperature curve to the ideal temperature curve by 21.05%. These findings provide theoretical and engineering guidance for the development of high-performance, reliable laser soldering systems.

LSTM-MPC control of thermal management system for high-power fiber-coupled diode lasers

Laser soldering has been gradually applied to the soldering of electronic components due to the rapid development of microelectronics. However, it is inefficient to use a mechanical shaft to move a laser beam. Here, a laser soldering system is constructed using galvanometer scanning, and an intelligent algorithm is also introduced to optimize the soldering path. Firstly, a laser soldering system for scanning of galvanometers is established, and the functions of visual monitoring, motion planning and parameter integration are presented. Secondly, the position of the laser beam and the corresponding soldering spot are determined, and the coordinate information is provided to plan a route by camera calibration and coordinate system transformation. Finally, the problem of path planning in this system is decomposed into the generation of the soldering point full coverage processing frame, and the route optimization of processing platform and laser beam motion. Furthermore, an improved clustering algorithm, based on the characteristics of system structure, and a hybrid optimization algorithm are designed to deal with the generation of the soldering point full coverage processing frame, the route optimization of processing platform and laser beam motion. In addition, the simulations and experiments are verified by test board. These findings shown that the established system and designed optimization algorithm can promote the efficiency of laser soldering.

/pdf/path-planning-of-laser-soldering-system-based-on-intelligent-1r52q7g5.pdf

Path Planning of Laser Soldering System Based on Intelligent Algorithm

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