Feed forward control of welding process parameters through on-line ultrasonic thickness measurement

Vasilev, Momchil; MacLeod, Charles N.; Javadi, Yashar; Pierce, S. Gareth; Gachagan, Anthony

doi:10.1016/j.jmapro.2021.02.005

Cited by 15 publications

(3 citation statements)

References 19 publications

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“…This method has shown promise as the rate of change of the received Lamb waves’ amplitude was found to be correlated to the weld penetration depth. In [ 45 ], a split-crystal ultrasonic wheel probe was attached to the welding torch and was utilised for thickness measurement of samples with a varying loss of wall thickness, as shown in Figure 12 . The measured thickness was used to control and adapt the welding arc current, torch travel speed and wire feed rate on-the-fly.…”

Section: Ultrasonic Inspectionmentioning

confidence: 99%

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE

Vasilev

MacLeod

Loukas

et al. 2021

Sensors

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The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.

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Section: Ultrasonic Inspectionmentioning

confidence: 99%

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE

Vasilev

MacLeod

Loukas

et al. 2021

Sensors

Self Cite

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show abstract

“…Thomas [4] reconstructed the thermal images of cold metal transfer process to monitor the porosity defects and improper weld beads. Vasilev [5] utilized an ultrasonic thickness measurement system to control the welding current and welding speed. These methods have mostly focused on improving the welding process with information from one-dimensional or two-dimensional welding pool surface data.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Reconstruction of Welding Pool Surface by Binocular Vision

Chen

2021

Chin. J. Mech. Eng.

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Current research of binocular vision systems mainly need to resolve the camera’s intrinsic parameters before the reconstruction of three-dimensional (3D) objects. The classical Zhang’ calibration is hardly to calculate all errors caused by perspective distortion and lens distortion. Also, the image-matching algorithm of the binocular vision system still needs to be improved to accelerate the reconstruction speed of welding pool surfaces. In this paper, a preset coordinate system was utilized for camera calibration instead of Zhang’ calibration. The binocular vision system was modified to capture images of welding pool surfaces by suppressing the strong arc interference during gas metal arc welding. Combining and improving the algorithms of speeded up robust features, binary robust invariant scalable keypoints, and KAZE, the feature information of points (i.e., RGB values, pixel coordinates) was extracted as the feature vector of the welding pool surface. Based on the characteristics of the welding images, a mismatch-elimination algorithm was developed to increase the accuracy of image-matching algorithms. The world coordinates of matching feature points were calculated to reconstruct the 3D shape of the welding pool surface. The effectiveness and accuracy of the reconstruction of welding pool surfaces were verified by experimental results. This research proposes the development of binocular vision algorithms that can reconstruct the surface of welding pools accurately to realize intelligent welding control systems in the future.

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“…[ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. However, with the increase of the area of the forming area, the temperature gradient at both ends of the scanning line increases sharply [ 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. When the layer-by-layer accumulated thermal stress exceeds the yield strength of the formed material, it will cause local warpage and deformation of the workpiece.…”

Section: Introductionmentioning

confidence: 99%

Slicing Algorithm and Partition Scanning Strategy for 3D Printing Based on GPU Parallel Computing

Lai

Wei

2021

Materials

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Aiming at the problems of over stacking, warping deformation and rapid adjustment of layer thickness in electron beam additive manufacturing, the 3D printing slicing algorithm and partition scanning strategy for numerical control systems are studied. The GPU (graphics processing unit) is used to slice the 3D model, and the STL (stereolithography) file is calculated in parallel according to the normal vector and the vertex coordinates. The voxel information of the specified layer is dynamically obtained by adjusting the projection matrix to the slice height. The MS (marching squares) algorithm is used to extract the coordinate sequence of the binary image, and the ordered contour coordinates are output. In order to avoid shaking of the electron gun when the numerical control system is forming the microsegment straight line, and reduce metal overcrowding in the continuous curve C0, the NURBS (non-uniform rational b-splines) basis function is used to perform curve interpolation on the contour data. Aiming at the deformation problem of large block components in the forming process, a hexagonal partition and parallel line variable angle scanning technology is adopted, and an effective temperature and deformation control strategy is formed according to the European-distance planning scan order of each partition. The results show that the NURBS segmentation fits closer to the original polysurface cut line, and the error is reduced by 34.2% compared with the STL file slice data. As the number of triangular patches increases, the algorithm exhibits higher efficiency, STL files with 1,483,132 facets can be cut into 4488 layers in 89 s. The slicing algorithm involved in this research can be used as a general data processing algorithm for additive manufacturing technology to reduce the waiting time of the contour extraction process. Combined with the partition strategy, it can provide new ideas for the dynamic adjustment of layer thickness and deformation control in the forming process of large parts.

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Feed forward control of welding process parameters through on-line ultrasonic thickness measurement

Cited by 15 publications

References 19 publications

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE

Three-Dimensional Reconstruction of Welding Pool Surface by Binocular Vision

Slicing Algorithm and Partition Scanning Strategy for 3D Printing Based on GPU Parallel Computing

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