Papers by Keyword: Seam Tracking

Abstract: With the development of economy, the seam tracking technology for arc welding becomes one of the major research tasks in the manufacturing area with robots. In this study, the objectives aim to develop an intelligent and cost-effective algorithm based on the laser vision sensor for image processing in Gas Metal Arc (GMA) welding. Images of welded seam were captured from the CCD camera. These images were then processed by the algorithms in the proposed image processing. To optimize the effective image process, popular algorithms in use were verified, compared and finally selected for every step in the image processing. Moreover, owing to the simple interactive environment and abundant toolboxes, MATLAB was employed to realize those algorithms, which offer a sample for engineers to achieve the goal of algorithm developed by this new but easier approach. Finally, weld seam images obtained with different welding environments were processed to enhance the proposal validity, and it’s proved to have significant effect of getting rid of the variable noises to extract the feature points and centerline for seam tracking in GMA welding and is capable for industrial application.

Abstract: Aimed at the goal of improving the quality and the efficiency of welding for T-type welding seam, This paper put forward a method to track the seam by using the vision sensor. Machine tool main motion trajectory is generated from the numerical model of the parts. The position of two welding torches are adjusted independently based on the machine tool main motion trajectory to ensure the welding precision. Two sets of adjusting mechanism are needed for T-type welding seam. The vision sensor measure the seam and pass the deviation signal to the CNC system. The CNC system adjust the position of the welding torch installed on the cross slide table to reach the goal of seam tracking and dual-beam laser welding for T-type welding seam. Practice shows that this system for T-type welding seam dual-beam laser welding is easy to operate and can improve the quality and the efficiency.

Abstract: In view of the strong arc weld of images, using combined MCD correlation matching method with genetic algorithm of traversing search the real-time image and target the best match position between the template image, build tracking motion model, accurately track the weld seam. Experiments show that the method in background、interference problem and tracking stability has achieved expected effect.

Abstract: Seam tracking technology is an important area of research automatic arc welding, precise seam tracking is crucial to achieve high quality welds. In order to achieve precise seam tracking, seam deviation (the weld center arc deviation) detection is a key. Unlike the conventional method by image processing techniques to obtain the seam deviation information directly, but selected image processing area (including the distal end portion of the molten pool welds and the front end of the pool), and analyzed as a pool image centroid characteristic parameters of the weld deviation. Study these parameters to create a new method for visual weld deviation measurement model, establish the weld center neural network model using artificial neural network modeling technology.

Abstract: Seam tracking technology is an important area of research automatic arc welding, precise seam tracking is crucial to achieve high quality welds. In order to achieve precise seam tracking, seam deviation ( the weld center arc deviation) detection is a key. Unlike the conventional method by image processing techniques to obtain the seam deviation information directly, but selected image processing area (including the distal end portion of the molten pool welds and the front end of the pool), and analyzed as a pool image centroid characteristic parameters of the weld deviation. Study these parameters to create a new method for visual weld deviation measurement model, establish the linear regression model between pool image centroid deviation and the weld based on regression analysis theory.

Abstract: In order to solve the problems of seam tracking for automation welding of large welding structure, this paper has respectively built mathematic model for length of magnetic-control arc according to two typical forms of weld pass in multi-pass welding for V-groove seam. By using Matlab/Simulink to analyze the transformation discipline of welding currents, a method for deviation acquisition based on magnetic-control arc sensing for multi-pass welding is proposed. Welding experiments demonstrates that the method proposed can effectively resolve the dilemma of deviation acquisition during multi-pass welding for thick plates with V-groove seam.

Abstract: With the exploration of marine sources becoming more and more important, underwater welding is widely needed. Because of the special working condition, underwater weld seam tracking technology is urgently needed, for the automation control of the underwater welding process is the inevitable development trend because of the rigorous environment. This paper used ultrasonic sensor to monitor the weld seam position in underwater wet welding process, and signal process algorithm was developed to obtain the weld seam information, experiment results showed that this method could detect the weld seam shape correctly, this load the foundation for further automatically controlling the welding process.

Abstract: This paper presents a vision-based curve-shaped seam tracking system. The measurement of the curve trajectory is based on a camera that is installed ahead of the end effector of the robot. Effective image processing method is designed to extract the feature points of the curve. Then a fuzzy controller is proposed to control the position of the robot to track the curve. To improve the performance of the controller, a self-tuning mechanism is added to the controller. Finally, experiments are fully conducted to verify the effectiveness of the proposed method.

Abstract: Weld automation is the development trend of underwater welding, and underwater weld seam tracking is one of the key technologies in weld automation. This paper used active visual sensor to automatically monitor the weld seam in underwater wet weld process, and image processing algorithms were developed to automatically obtain the weld torch deviation, then the weld torch was adjusted automatically according to the deviation obtained by the image, experiment results showed that this method could be used in underwater wet welding.

Abstract: Weld seam tracking system is urgently needed in weld automation process, but it has not been well studied in underwater weld applications. This paper used visual sensor to automatically monitor the weld seam in underwater wet weld process, and image processing algorithms were developed to remove the influence of water environment on the captured image and automatically obtain the weld torch deviation, and the weld torch was adjusted automatically according to the deviation obtained by the image, experiment results showed that the system could meet the requirements of underwater wet welding process.