Seam tracking based on Kalman filtering of micro-gap weld using magneto-optical image

Gao, Xiangdong; Mo, Lingfei; Zhenlin, Xiao; Chen, Xiaohui; Katayama, Seiji

doi:10.1007/s00170-015-7560-x

Cited by 44 publications

(7 citation statements)

References 11 publications

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“…17 However, the result picture obtained by this method is not clear enough. Gao et al 18 established the state equation based on the position parameters of the stitching line and the measurement equation of the position of the stitching line. Considering that the dynamic noise of the system is white noise, a traditional Kalman filter algorithm based on white noise was proposed, and the optimal state estimation of the position of the stitching line was obtained, which improved the anti-interference ability.…”

Section: Related Researchmentioning

confidence: 99%

Research on image stitching method based on improved ORB and stitching line calculation

Yang

Han

2022

J. Electron. Imag.

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Image matching is one of the hot issues in recent years. Image matching determines the effect of image mosaic to a large extent. Therefore, a stable, accurate, and fast image matching algorithm is very important for the subsequent processing of image information. Most of the traditional image matching methods have the problems of high-error matching rate and difficulty in to eliminating false matching. To resolve the shortcomings listed here, an improved algorithm was proposed in which a combined measure of Hamming distance. Similarity measurement with Tanimoto similarity measurement was adopted to dispose binary feature vectors. In addition, as an important step in the process of image mosaics, the calculation of the best mosaics can eliminate the ghosting and ghosting that may appear in the mosaics. However, the traditional dynamic planning method is easy to pass through the obstacles and form obvious stitching traces when searching for stitching lines in images with large obstacles. In view of the aforementioned content, we propose a fast and robust method to search the image difference matrix and structure difference matrix of the overlapping area of the input image according to the search strategy to determine the pixel coordinates of the splicing line. Finally, from an optimal splicing line, the experimental results show that our algorithm performs well for eliminating error matching points. Compared with traditional algorithms, matching accuracy is improved by 25%. In terms of calculating the optimal splicing line, the method proposed is faster than the traditional method and has good robustness.

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Section: Related Researchmentioning

confidence: 99%

Research on image stitching method based on improved ORB and stitching line calculation

Yang

Han

2022

J. Electron. Imag.

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“…In the selection of welding sensors, research institutions and manufacturers have applied sensors with various measurement principles to measure welding pieces. Welding sensors [4][5][6][7][8][9][10][11] could be divided into two types: direct type and indirect type. The direct type includes rotating arc type, swinging arc type, double wire arc type; the indirect type can be divided into contact type and non-contact type, the former and the latter of which includes probe contact type, electrode contact type, probe touch type and electromagnetic type, ultrasonic type, photoelectric type respectively.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Guidance Programming of Welding Robot for 3D Curved Welding Seam

et al. 2021

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Due to the limitations of welding complexity and machining error, traditional manual teaching and offline programming are not intelligent enough and have weak adaptability to workpiece. At present, the 2D perception visual welding guidance programming method is commonly used which cannot accurately locate and model the complicated 3D spatial curve welding seam. The 2D perception method can hardly meet the requirements of welding process. In this paper, a welding seam perception method based on a line structure light sensor was proposed, which optimizes the generation of the weld seam trajectory, and builds a highly adaptable intelligent guidance programming system for welding robots. Firstly, 3D modeling perception of welding parts is realized through eye-in-hand system of robot, which solves the problem that offline programming system cannot be applied when the welding model is not precise enough or partly miss. Secondly, aiming at solving extraction problem of common types of 3D space curve welding seam, corresponding types of weld extraction algorithms are proposed according to the characteristics of different types of welds under the general process of weld extraction. These methods not only can directly extract the weld from the ordered point cloud with high precision and resolution, but also are less affected by the welding environment, which solve the problem of low perception accuracy of complex curved welds in 3D space. Then, on the basis of welding seam extraction, NURBS curves are used to realize the optimal generation of weld trajectory. Finally, the feasibility and effectiveness of all the methods proposed in this paper are verified by a large number of experiments.

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“…When the set of parameters in the extracted features is sufficient to describe a weld groove section uniquely, then the process of feature extraction can also be referred to as weld groove parametrization. Typical sensor technologies are ultrasound sensors [ 1 ], infrared sensors [ 2 ], arc-sensing [ 3 ], magneto-optical sensors [ 4 ], and computer vision sensors [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Laser Scanning and Parametrization of Weld Grooves with Reflective Surfaces

Cibicik

Tingelstad

Egeland

2021

Sensors

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This paper presents a novel weld groove parametrization algorithm, which is developed specifically for weld grooves in typical stub and butt joints between large tubular elements. The procedure is based on random sample consensus (RANSAC) with additionally proposed correction steps, including a corner correction step for grooves with narrow root weld, and an iterative error elimination step for improving the initially obtained data fit. The problem of curved groove sides (due to the pipe geometry) is attributed and solved. In addition, the procedure detects and eliminates several types of data noise due to laser line reflections. The performance of the procedure is studied experimentally using small-scale test objects, which have been ground using typical industrial power tools to achieve a realistic level of reflections. The execution times and data fit errors of the proposed procedure are compared to a procedure based on a more conventional RANSAC approach for line segment detection.

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Seam tracking based on Kalman filtering of micro-gap weld using magneto-optical image

Cited by 44 publications

References 11 publications

Research on image stitching method based on improved ORB and stitching line calculation

Research on image stitching method based on improved ORB and stitching line calculation

Intelligent Guidance Programming of Welding Robot for 3D Curved Welding Seam

Laser Scanning and Parametrization of Weld Grooves with Reflective Surfaces

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