Based on the CO&lt;sub&gt;2&lt;/sub&gt; Gas Shielded Welding Molten Pool Image Edge Detection Algorithm

Liu, Xiao Gang; Zhao, Bin

doi:10.4028/www.scientific.net/amm.437.840

Cited by 5 publications

(3 citation statements)

References 1 publication

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“…The product of the edge detection operator and pixel gray value is often used to characterize image gradient. Common simple edge detection filters include the Sobel, Prewitt, and Roberts operators. Because of the advantages of simple operation and rapid computation, the Sobel operator was used to detect the edge of the image and extract contour features.…”

Section: Methodsmentioning

confidence: 99%

Experimental and Numerical Study of the Nitrogen Transformation Mechanism in the Reburning Zone

et al. 2022

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In this work, image spectroscopy and numerical simulation were applied to reveal NH 3 /NO conversion in the reburning zone where NH 3 and NO coexist. Methane premixed flame doped with the mixture of NH 3 and NO was utilized to investigate the nitrogen conversion in the reburning zone in which NO and NH 3 existed simultaneously. Meanwhile, the premixed methane flames doped with NH 3 /NO/the mixture of NH 3 and NO were compared to acquire the mechanism of effect on NO reduction and NH 3 oxidation in the presence of NH 3 and NO. Sensitivity analysis was applied to obtain the key radicals in the process of NO generation and transformation. The spatial distribution characteristics of these radicals were further obtained by using image spectroscopy. The results of image spectroscopy showed that the simultaneous presence of NO and NH 3 led to the decrease of OH and the increase of NH and CN. It was also found that the reduction of NO occurred earlier than the oxidation of NH. In addition, the spatial distribution of the reaction rate between NH and OH was obtained by calculating the product of spontaneous emission intensity of NH and OH. The rate of production (ROP) of NO was used to generate the mechanism of NH 3 and NO coexistence on nitrogen transformation. The results showed that in NO + NH 3 flames, the acceleration of the oxidation reaction rate of nitrogenous intermediates was limited, but the reduction reaction rate of NO increased rapidly relative to other flames, which led to the decrease of NO when NO and NH 3 coexist. This study revealed the mechanism of the coupling effect of NO reduction and NH 3 oxidation on the nitrogen conversion, which provides theoretical guidance for improving the NOx removal effect in the reburning zone.

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Section: Methodsmentioning

confidence: 99%

Experimental and Numerical Study of the Nitrogen Transformation Mechanism in the Reburning Zone

et al. 2022

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“…At present, image segmentation methods for molten pools can be divided into two categories, including methods based on traditional image algorithms and those based on active contour models [10]. Liu et al [11] analyzed the results of six different edge detection operators and finalized the Canny operator (with a threshold between 0.1 and 0.5) to obtain ideal edge features for a molten pool. Chen et al [12] utilized a traditional image algorithm to extract the molten pool's width, trailing length, and surface height, which were used as the input signals of the data-driven model to predict the backside width.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Recognition of Molten Pools Based on Improved DeepLabV3+ in Keyhole Tungsten Inert Gas Welding Applications

Yang,

Dai,

Cui

et al. 2024

Electronics

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During the Keyhole Tungsten Inert Gas (K-TIG) welding process, a significant amount of information related to the weld quality can be obtained from the weld pool and the keyhole of the topside molten pool image, which provides a vital basis for the control of welding quality. However, the topside molten pool image has the unstable characteristic of strong arc light, which leads to difficulty in contour extraction. The existing image segmentation algorithms cannot satisfy the requirements for accuracy, timing, and robustness. Aiming at these problems, a real-time recognition method, based on improved DeepLabV3+, for identifying the molten pool more accurately and effectively was proposed in this paper. First, MobileNetV2 was selected as the feature extraction network with which to improve detection efficiency. Then, the atrous rates of atrous convolution layers were optimized to reduce the receptive field and balance the sensitivity of the model to molten pools of different scales. Finally, the convolutional block attention module (CBAM) was introduced to improve the segmentation accuracy of the model. The experimental results verified that the proposed model had a fast segmentation speed and higher segmentation accuracy, with an average intersection ratio of 89.89% and an inference speed of 103 frames per second. Furthermore, the trained model was deployed in a real-time system and achieved a real-time performance of up to 28 frames per second, thus meeting the real-time and accuracy requirements of the K-TIG molten pool monitoring system.

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“…The shape, characteristics, and dynamic changes of the weld pool are important factors to determine the welding forming quality. Some papers define different image-processing techniques for weld pools, such as the research work by Xiao and Bing [11] that proposed the classic processes like Sobel, Canny, and the threshold segmentation for the CO 2 weld image processing. Xu et al [12] investigated the robot GMAW process and integrated multiple classical image-processing algorithms to extract weld visual image edges through restoration, filtering, edge detection, edge scanning, and curve fitting.…”

Section: Introductionmentioning

confidence: 99%

Image Processing and Feature Extraction for Hull Structure GMAW Based on Weld Pool Visual Sensing

et al. 2023

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Image processing and feature information extraction based on the visual perception of the weld pool are considered essential components of intelligent welding quality monitoring of hull structure gas metal arc welding (GMAW). The unstable characteristics, such as large spatter, much smoke, and strong arc light during hull structure GMAW, lead to the blurring of image acquisition and the difficulty of contour extraction of the weld pool. The present study is aimed at addressing the practical issues from two perspectives, i.e., a spectrum-visual-sensing acquisition system and an image-processing and feature extraction algorithm. First of all, by analyzing the light energy distribution law and acquiring the optical parameters relevant to the cut-off composite dimming and near-infrared narrowband filtering, spectral sensing is employed in establishing models of arc light radiation to detect the strength of continuously distinctive spectral lines. Besides, an appropriate high-speed charge-coupled device (CCD) camera is selected to build a visual acquisition system, which can reduce the external interference of the arc light on the image acquisition of the weld pool. Afterwards, the implementation of an image-processing fusion model based on the spatial information fuzzy C-means (FCM) clustering analysis and Sobel edge detection operator accompanies the investigation of the geometric aspects of the weld pool image. In terms of clear segmentation of the interest region, the edge detection and accurate extraction of the target contour are successfully obtained. In the subsequent section, the Hough transform analysis is adopted to establish the geometric feature extraction model of the weld pool, with corner detection, conversion, and camera calibration as the core technology. Additionally, the left and right views of the image contour are calibrated to achieve the lossless conversion of corner pixels and physical coordinates. Finally, three other distinct image-processing methods are designed to compare the segmentation effect of the edge contour with the fusion model, and then, the extraction accuracy of the geometric features of the weld pool is verified. The interference of the arc light and smoke has been demonstrated to be substantially diminished, which is attributable to the visual-sensing system during image acquisition of the weld pool. The results of edge fusion of the weld pool image show that based on the GMAW using the FCM-Sobel fusion method, a superior extraction accuracy of geometric features characterized by smoothness, continuousness, no breakpoints, and less noise has fulfilled the engineering requirements.

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Based on the CO<sub>2</sub> Gas Shielded Welding Molten Pool Image Edge Detection Algorithm

Cited by 5 publications

References 1 publication

Experimental and Numerical Study of the Nitrogen Transformation Mechanism in the Reburning Zone

Experimental and Numerical Study of the Nitrogen Transformation Mechanism in the Reburning Zone

Real-Time Recognition of Molten Pools Based on Improved DeepLabV3+ in Keyhole Tungsten Inert Gas Welding Applications

Image Processing and Feature Extraction for Hull Structure GMAW Based on Weld Pool Visual Sensing

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