Narrow Butt Research Articles

Real-time detection and localization method for weld seam of narrow butt joint based on semantic segmentation

Structured light measurement is widely used in welding seam tracking because of its high precision and robustness. For the narrow butt joint, the positioning method by reconstructing the weld contour is not suitable for the welding of the narrow butt joint because it is difficult for the laser stripe to produce obvious deformation when projected to the weld. In this study, high-quality images with laser stripes and narrow butt joints are captured by the improved structured light vision sensor, which is equipped with an auxiliary light source. A two-step processing framework, including semantic segmentation and groove positioning, is raised to locate the feature point of the narrow butt joint. Firstly, we design the strip pooling ENet (SP-ENet), a real-time network specifically designed to accurately segment narrow weld images. Our proposed network outperforms other classical segmentation networks in terms of segmentation accuracy and proves to be highly suitable for the detection of narrow butt joint welds. Secondly, a combining method of random sample consensus (RANSAC) and iterative fitting to calculate the sub-pixel coordinates of weld feature points accurately. Finally, a trajectory smoothing model based on the Kalman filter is proposed to reduce the trajectory jitter. The above methods were tested on a self-built robotic welding experimental platform. Experimental results show that the proposed method can be used for real-time detection and positioning of narrow butt joints. The positioning trajectory is smooth, with most positioning errors less than 2 pixels. The mean tracking error reaches 0.207 mm, which can meet the practical welding requirements.

The 3D narrow butt weld seam detection system based on the binocular consistency correction

The 3D narrow butt weld seam detection system based on the binocular consistency correction

A robust weld seam detection method based on particle filter for laser welding by using a passive vision sensor

Vision sensor systems with an auxiliary light source such as structured light–based vision sensor have been widely used for weld seam detection. However, the main drawback of this method is the preview distance between the welding position and the sensing position, which can generate unavoidable detecting errors. Laser welding of the small workpiece or narrow butt joint is especially vulnerable to detection error caused by preview distance. Meanwhile, only one point of the weld seam can be measured each time, which makes the corresponding image processing very sensitive to light noise. Consequently, a seam measurement method based on a passive vision sensor for narrow gap butt joint is proposed in this article. The weld pool is observed directly by this vision sensor so that there is no preview distance. An adequately adjusted telecentric lens is used to increase the contrast between the seam feature and the background welding noise. By this manner, a long and noticeable weld seam feature, as well as the weld pool, can be obtained in the captured images. A corresponding image processing algorithm based on particle filter is designed to extract the captured long weld seam. The particle filter is used to track the slope and intercept of the weld seam, which combines the advantage of both particle filter and Hough transform. As the particle filter algorithm could generate the result by evaluating both the previous and the current measurement results, the corresponding image processing can be robust even when a few images are of poor quality. Finally, laser welding experiments were carried out, and the results revealed that the proposed method could achieve detection accuracy of 0.08 mm when welding 0.1 mm width narrow butt joint at 2000 mm/min welding speed.

A Vision Based Detection Method for Narrow Butt Joints and a Robotic Seam Tracking System.

Automatic joint detection is of vital importance for the teaching of robots before welding and the seam tracking during welding. For narrow butt joints, the traditional structured light method may be ineffective, and many existing detection methods designed for narrow butt joints can only detect their 2D position. However, for butt joints with narrow gaps and 3D trajectories, their 3D position and orientation of the workpiece surface are required. In this paper, a vision based detection method for narrow butt joints is proposed. A crosshair laser is projected onto the workpiece surface and an auxiliary light source is used to illuminate the workpiece surface continuously. Then, images with an appropriate grayscale distribution are grabbed with the auto exposure function of the camera. The 3D position of the joint and the normal vector of the workpiece surface are calculated by the combination of the 2D and 3D information in the images. In addition, the detection method is applied in a robotic seam tracking system for GTAW (gas tungsten arc welding). Different filtering methods are used to smooth the detection results, and compared with the moving average method, the Kalman filter can reduce the dithering of the robot and improve the tracking accuracy significantly.

Automatic extraction and identification of narrow butt joint based on ANFIS before GMAW

To improve the automation level of the welding robots, the automatic extraction and identification of the weld seam is the pre-requisite of the intelligent welding robots. During the real industrial environment, the welding environment often has the characteristics of weak texture, poor contrast, reflections from metallic surfaces, and imperfections on the work piece. These characteristics will seriously affect the accurate extraction of weld seam. To realize the automatic path planning of welding robots, a new method of automatic extraction and identification of narrow butt joint under weak contrast is realized to serve the 3D path teaching of welding robots. To achieve accurate extraction of narrow butt joint under weak contrast, this paper designs a new seam extraction operator to achieve accurate and fast extraction of weld seam with various shapes and sizes. And the shape feature of weld seam is used to construct feature vector. Finally, to get optimal classification performance, the adaptive network-based fuzzy inference system (ANFIS) is adopted in this paper to finish identification of narrow butt joints. The experimental results show that the proposed algorithm could quickly and accurately realize the extraction and identification of the narrow butt joints under weak contrast.

A precise seam tracking method for narrow butt seams based on structured light vision sensor

At present, most popular approaches of seam detection are based on structured light vision sensors owing to features of high accuracy and robustness. However, the deformation of laser stripe is not obvious enough when it is projected onto narrow butt seam, whose width is less than 0.2 mm, so the traditional structured light vision sensor cannot detect the seam feature of narrow butt seam. In this paper, a precise seam tracking method for narrow butt seams based on structured light vision sensor is proposed. Firstly, a new structured light vision sensor with optical filters and an extra LED light is developed to filtered out most of noises from strong arc lights and acquire the image including laser stripe and narrow butt seam. In addition, an image processing method for the vision sensor is designed to obtain welding torch deviations of narrow butt seams both in horizontal and vertical directions. Based on the obtained deviations, two independent Fuzzy-PID controllers are designed to achieve seam tracking control accurately. Finally, in order to verify the effectiveness of the proposed method in this paper, a welding experimental system is setup and welding experiments are carried out. Experimental results demonstrate that this method can meet the requirement of narrow butt seams tracking accuracy.

A novel weld seam detection method for space weld seam of narrow butt joint in laser welding

Structured light measurement is widely used for weld seam detection owing to its high measurement precision and robust. However, there is nearly no geometrical deformation of the stripe projected onto weld face, whose seam width is less than 0.1 mm and without misalignment. So, it’s very difficult to ensure an exact retrieval of the seam feature. This issue is raised as laser welding for butt joint of thin metal plate is widely applied. Moreover, measurement for the seam width, seam center and the normal vector of the weld face at the same time during welding process is of great importance to the welding quality but rarely reported. Consequently, a seam measurement method based on vision sensor for space weld seam of narrow butt joint is proposed in this article. Three laser stripes with different wave length are project on the weldment, in which two red laser stripes are designed and used to measure the three dimensional profile of the weld face by the principle of optical triangulation, and the third green laser stripe is used as light source to measure the edge and the centerline of the seam by the principle of passive vision sensor. The corresponding image process algorithm is proposed to extract the centerline of the red laser stripes as well as the seam feature. All these three laser stripes are captured and processed in a single image so that the three dimensional position of the space weld seam can be obtained simultaneously. Finally, the result of experiment reveals that the proposed method can meet the precision demand of space narrow butt joint.

A Vision-Aided 3D Path Teaching Method before Narrow Butt Joint Welding

For better welding quality, accurate path teaching for actuators must be achieved before welding. Due to machining errors, assembly errors, deformations, etc., the actual groove position may be different from the predetermined path. Therefore, it is significant to recognize the actual groove position using machine vision methods and perform an accurate path teaching process. However, during the teaching process of a narrow butt joint, the existing machine vision methods may fail because of poor adaptability, low resolution, and lack of 3D information. This paper proposes a 3D path teaching method for narrow butt joint welding. This method obtains two kinds of visual information nearly at the same time, namely 2D pixel coordinates of the groove in uniform lighting condition and 3D point cloud data of the workpiece surface in cross-line laser lighting condition. The 3D position and pose between the welding torch and groove can be calculated after information fusion. The image resolution can reach 12.5 μm. Experiments are carried out at an actuator speed of 2300 mm/min and groove width of less than 0.1 mm. The results show that this method is suitable for groove recognition before narrow butt joint welding and can be applied in path teaching fields of 3D complex components.

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding.

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process.

Compact visual control system for aligning and tracking narrow butt seams with CO2 gas-shielded arc welding

In this paper, a visual control system is proposed to locate the start welding position and track the narrow butt welding seam in container manufacturing. It estimates the error between the welding torch and the welding seam with a camera and a panel computer. It adjusts the torch's position via a stepper motor to eliminate the error. A decision controller with three gates is designed to decide the working procedure. Feature extraction algorithms are designed according to the seams and pre-weld spots. The seam line and the position of the pre-weld spot are detected to locate the start welding position in initial aligning. Then the torch is aligned to the seam. In the welding stage, the reference feature is determined with many frames of images based on their statistical property. The current estimated feature is checked to ensure only normal features to be used for welding seam tracking. Experiments are well conducted to verify the effectiveness of the proposed system and methods.

Determining seam profile tracking of very narrow butt welding on sheet metal

In this study, a welding manipulator has been designed in order to perform the butt-welding operation automatically of cylindrical sheet metals used in natural gas and heating systems. After the design procedure, the elements related to welding manipulator desired, has been defined and the test apparatuses was manufactured. In order to obtain profile of surface that will be welded on sheet metal, 2D laser profile sensor was used. A Personal Computer (PC) based software was developed and tested on the experiment set up in order to define the position of welding torch depends on profile data of welded area. The butt-welding process of two sheet metal shopped cylindrically was carried out automatically on test apparatuses. Key words: Image processing, seam tracking, laser 2D profile sensor, visual control algorithm, butt seam.