RESUMEN
In order to ensure the production quality of high-speed laser welding, it is necessary to simultaneously monitor multiple state properties. Monitoring methods combining vision sensing and deep learning models are popular but most models used can only make predictions on single welding state property. In this contribution, we propose a multi-output model based on a lightweight convolutional neural network (CNN) architecture and introduce the particle swarm optimization (PSO) technique to optimize the loss function of the model, to simultaneously monitor multiple state properties of high-speed laser welding of AISI 304 austenitic stainless steel. High-speed imaging is performed to capture images of the melt pool and the dataset is built. Test results of different models show that the proposed model can achieve monitoring of multiple welding state properties accurately and efficiently. In addition, we make an interpretation and discussion on the prediction of the model through a visualization method, which can help to deepen our understanding of the relationship between the melt pool appearance and welding state. The proposed method can not only be applied to the monitoring of high-speed laser welding but also has the potential to be used in other procedures of welding state monitoring.
RESUMEN
Web-core sandwich panels have gained the popularity in various fields, especially aviation and shipbuilding, etc. Penetration welding was considered as an effective process to manufacture such a structure through a T-joint. To ensure the formation quality and mechanical properties of weld, the welding torch needs to be aligned with the T-joint position. However, it is difficult to locate the T-joint position (i.e., the position of core panel) because of the shielding of the face panels. This paper investigated the detection of T-joint position from the face panel side in web-core sandwich panels based on eddy current technology. First, we designed an experimental system for the weld position detection of T-joints from the face panel side. The relationships are investigated between the characteristics of the eddy current detection signal and the primary parameters of the detection system (including excitation frequency, coil outer diameter, and lift off distance) and the T-joint (including thickness of the core panel, gap distance, and thickness of the cover panel). Corresponding experiments were carried out with variable primary parameters, and the influence mechanism of the primary parameters on the detection results in terms of sensitivity and dynamic performance was elaborated to set up the theoretical basis for the detection. Finally, weld position detection experiments were carried out on TC4 titanium alloy T-joint specimens with 3 mm-thick face panel and 5 mm-thick core panel. Results showed that the maximum detection error was 0.482 mm, and the average error was 0.234 mm. This paper provided a possible technical solution to the automatic tracking problem for the welding of T-joints in the web-core sandwich panels.
RESUMEN
In the process of electron-beam freeform fabrication deposition, the surface of the deposit layer becomes rough because of the instability of the feeding wire and the changing of the thermal diffusion condition. This will make the droplet transfer distance change in the deposition process, and the droplet transfer cannot always be stable in the liquid bridge transfer state. It is easy to form a large droplet or make wire and substrate stick together, which makes the deposition quality worsen or even interrupts the deposition process. The current electron-beam freeform fabrication deposition is mostly open-loop control, so it is urgent to realize the real-time and closed-loop control of the droplet transfer and to make it stable in the liquid bridge transfer state. In this paper, a real-time monitoring method based on machine vision is proposed for the droplet transfer of electron-beam freeform fabrication. The detection accuracy is up to ± 0.08 mm. Based on this method, the measured droplet transfer distance is fed back to the platform control system in real time. This closed-loop control system can stabilize the droplet transfer distance within ± 0.14 mm. In order to improve the detection stability of the whole system, a droplet transfer detection algorithm suitable for this scenario has been written, which improves the adaptability of the droplet transfer distance detection method by means of dilatation/erosion, local minimum value suppression, and image segmentation. This algorithm can resist multiple disturbances, such as spatter, large droplet occlusion and so on.
RESUMEN
In the process of electron beam freeform fabrication (EBF3), due to the continuous change of thermal conditions and variability in wire feeding in the deposition process, geometric deviations are generated in the deposition of each layer. In order to prevent the layer-by-layer accumulation of the deviation, it is necessary to perform online geometry measurement for each deposition layer, based on which the error compensation can be done for the previous deposition layer in the next deposition layer. However, the traditional three-dimensional reconstruction method that employs structured laser cannot meet the requirements of long-term stable operation in the manufacturing process of EBF3. Therefore, this paper proposes a method to measure the deposit surfaces based on the position information of electron beam speckle, in which an electron beam is used to bombard the surface of the deposit to generate the speckle. Based on the structured information of the electron beam in the vacuum chamber, the three-dimensional reconstruction of the surface of the deposited parts is realized without need of additional structured laser sensor. In order to improve the detection accuracy, the detection error is theoretically analyzed and compensated. The absolute error after compensation is smaller than 0.1 mm, and the precision can reach 0.1%, which satisfies the requirements of 3D reconstruction of the deposited parts. An online measurement system is built for the surface of deposited parts in the process of electron beam freeform fabrication, which realizes the online 3D reconstruction of the surface of the deposited layer. In addition, in order to improve the detection stability of the whole system, the image processing algorithm suitable for this scene is designed. The reliability and speed of the algorithm are improved by ROI extraction, threshold segmentation, and expansion corrosion. In addition, the speckle size information can also reflect the thermal conditions of the surface of the deposited parts. Hence, it can be used for online detection of defects such as infusion and voids.
RESUMEN
Web-core sandwich panels are a typical lightweight structure utilized in a variety of fields, such as naval, aviation, aerospace, etc. Welding is considered as an effective process to join the face panel to the core panel from the face panel side. However, it is difficult to locate the joint position (i.e., the position of core panel) due to the shielding of the face panel. This paper studies a weld position detection method based on X-ray from the face panel side for aluminum web-core sandwich panels used in aviation and naval structures. First, an experimental system was designed for weld position detection, able to quickly acquire the X-ray intensity signal backscattered by the specimen. An effective signal processing method was developed to accurately extract the characteristic value of X-ray intensity signals representing the center of the joint. Secondly, an analytical model was established to calculate and optimize the detection parameters required for detection of the weld position of a given specimen by analyzing the relationship between the backscattered X-ray intensity signal detected by the detector and the parameters of the detection system and specimen during the detection process. Finally, several experiments were carried out on a 6061 aluminum alloy specimen with a thickness of 3 mm. The experimental results demonstrate that the maximum absolute error of the detection was 0.340 mm, which is sufficiently accurate for locating the position of the joint. This paper aims to provide the technical basis for the automatic tracking of weld joints from the face panel side, required for the high-reliability manufacturing of curved sandwich structures.
RESUMEN
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.
RESUMEN
Lack of fusion can often occur during ultra-thin sheets edge welding process, severely destroying joint quality and leading to seal failure. This paper presents a vision-based weld pool monitoring method for detecting a lack of fusion during micro plasma arc welding (MPAW) of ultra-thin sheets edge welds. A passive micro-vision sensor is developed to acquire clear images of the mesoscale weld pool under MPAW conditions, continuously and stably. Then, an image processing algorithm has been proposed to extract the characteristics of weld pool geometry from the acquired images in real time. The relations between the presence of a lack of fusion in edge weld and dynamic changes in weld pool characteristic parameters are investigated. The experimental results indicate that the abrupt changes of extracted weld pool centroid position along the weld length are highly correlated with the occurrences of lack of fusion. By using such weld pool characteristic information, the lack of fusion in MPAW of ultra-thin sheets edge welds can be detected in real time. The proposed in-process monitoring method makes the early warning possible. It also can provide feedback for real-time control and can serve as a basis for intelligent defect identification.
RESUMEN
Multi-layer/multi-pass welding (MLMPW) technology is widely used in the energy industry to join thick components. During automatic welding using robots or other actuators, it is very important to recognize the actual weld pass position using visual methods, which can then be used not only to perform reasonable path planning for actuators, but also to correct any deviations between the welding torch and the weld pass position in real time. However, due to the small geometrical differences between adjacent weld passes, existing weld position recognition technologies such as structured light methods are not suitable for weld position detection in MLMPW. This paper proposes a novel method for weld position detection, which fuses various kinds of information in MLMPW. First, a synchronous acquisition method is developed to obtain various kinds of visual information when directional light and structured light sources are on, respectively. Then, interferences are eliminated by fusing adjacent images. Finally, the information from directional and structured light images is fused to obtain the 3D positions of the weld passes. Experiment results show that each process can be done in 30 ms and the deviation is less than 0.6 mm. The proposed method can be used for automatic path planning and seam tracking in the robotic MLMPW process as well as electron beam freeform fabrication process.
RESUMEN
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.
RESUMEN
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.
RESUMEN
Increasing welding speed can promote the productivity of laser welding. However, humping defects often occur, which limits the application of this strategy. The existing explanations for the humping formation remain vague, and mitigation and suppression methods are limited. In this research, high-speed imaging experiments and numerical simulation of the high-speed laser welding process are performed. Through careful examination, the humping phenomenon is explained. At high welding speed, the high-speed melt flow caused by recoil pressure is hindered by the solidified region in the melt pool, leading to the occurrence of a swelling. The swelling then grows, forming a valley in front of the swelling under the effect of surface tension. The solidification of the valley results in the occurrence of a second swelling. This process repeats and humping defect forms. Marangoni force and viscous force also have influence on this process. In addition, it is found that adding a Tungsten Inert Gas arc behind the laser beam can effectively suppress the humping.
RESUMEN
Fe-based amorphous alloys with excellent mechanical properties are suitable for preparing wear resistant coatings by laser cladding. In this study, a novel Fe-based amorphous coating was prepared by laser cladding on 3Cr13 stainless steel substrates. The influence of scanning speeds on the microstructures and properties of the coatings was investigated. The microstructure compositions and phases were analyzed by scanning electron microscope, electron probe microanalyzer, and x-ray diffraction respectively. Results showed that the microstructures of the coatings changed significantly with the increase of scanning speeds. For a scanning speed of 6 mm/s, the cladding layer was a mixture of amorphous and crystalline regions. For a scanning speed of 8 mm/s, the cladding layer was mainly composed of block grain structures. For a scanning speed of 10 mm/s, the cladding layer was composed entirely of dendrites. Different dilution rates at the bonding zones were the main reasons for the microstructure change for different claddings. For all three scanning speeds, the coatings had higher hardness and wear resistance when compared with the substrate; as the scanning speed increased, the hardness and wear resistance of the coatings gradually decreased due to the change in microstructure.
RESUMEN
In the laser deposition of single crystal and directionally-solidified superalloys, it is desired to form laser deposits with high volume fractions of columnar grains by suppressing the columnar-to-equiaxed transition efficiently. In this paper, the influence of beam profile (circular and square shapes) and cooling conditions (natural cooling and forced cooling) on the geometric morphology and microstructure of deposits were experimentally studied in the laser deposition of a directionally-solidified superalloy, IC10, and the mechanisms of influence were revealed through a numerical simulation of the thermal processes during laser deposition. The results show that wider and thinner deposits were obtained with the square laser beam than those with the circular laser beam, regardless of whether natural or forced cooling conditions was used. The heights and contact angles of deposits were notably increased due to the reduced substrate temperatures by the application of forced cooling for both laser beam profiles. Under natural cooling conditions, columnar grains formed epitaxially at both the center and the edges of the deposits with the square laser beam, but only at the center of the deposits with the circular laser beam; under forced cooling conditions, columnar grains formed at both the center and the edges of deposits regardless of the laser beam profile. The high ratios of thermal gradient and solidification velocity in the height direction of the deposits were favorable to forming deposits with higher volume fractions of columnar grains.
RESUMEN
To obtain satisfactory welds in positional laser beam welding, it is necessary to know how process parameters will influence the quality of welds in different welding positions. In this study, the titanium alloy Ti6Al4V sheets were laser welded in two vertical welding positions (vertical up and vertical down), and the appearance, porosity, strength, and ductility of the laser joints were evaluated. Results show that undercuts of the vertical up welds were greater than that of vertical down welds, while the porosity contents were much higher in vertical down welds than that in vertical up welds. When welding with a higher heat input, the vertical up welding position resulted in poor weld profiles (undercuts and burn-through holes), whereas the vertical down welding position led to excessive porosity contents in welds. Both severe undercut and excessive porosity were detrimental to the tensile properties of the welds. Weld appearance was improved and porosity contents were reduced by using a lower heat input, achieving better weld quality. Therefore, it is suggested that process parameter settings with relatively high laser powers and welding speeds, which can result in lower heat inputs, are used when laser welding the Ti6Al4V titanium alloys vertically.