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GTAW填丝增材制造熔池尾部固液分界点跟踪算法

皮宇鹏, 熊俊, 赵慧慧, 陈辉

皮宇鹏, 熊俊, 赵慧慧, 陈辉. GTAW填丝增材制造熔池尾部固液分界点跟踪算法[J]. 焊接学报, 2019, 40(2): 104-109. DOI: 10.12073/j.hjxb.2019400051
引用本文: 皮宇鹏, 熊俊, 赵慧慧, 陈辉. GTAW填丝增材制造熔池尾部固液分界点跟踪算法[J]. 焊接学报, 2019, 40(2): 104-109. DOI: 10.12073/j.hjxb.2019400051
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PI Yupeng, XIONG Jun, ZHAO Huihui, CHEN Hui. Tracking algorithm for solid-liquid separation point of molten pool tail in GTAW-based additive manufacturing[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(2): 104-109. DOI: 10.12073/j.hjxb.2019400051
Citation: PI Yupeng, XIONG Jun, ZHAO Huihui, CHEN Hui. Tracking algorithm for solid-liquid separation point of molten pool tail in GTAW-based additive manufacturing[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(2): 104-109. DOI: 10.12073/j.hjxb.2019400051
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GTAW填丝增材制造熔池尾部固液分界点跟踪算法

  • 1. 西南交通大学 材料先进技术教育部重点实验室，成都　610036;

  • 2. 上海航天设备制造总厂有限公司，上海　200245

基金项目: 

国家重点研发计划资助项目(2016YFB1100202)；国家自然科学基金资助项目(61573293)；上海市青年科技启明星计划(18QB1401700)

详细信息
    作者简介:

    皮宇鹏，男，1995年出生，硕士研究生. 主要从事电弧填丝增材制造过程检测研究. Email：yupengPI@163.com

  • 中图分类号: TG 402

Tracking algorithm for solid-liquid separation point of molten pool tail in GTAW-based additive manufacturing

  • 1. Key Laboratory of Advanced Technologies of Materials, Ministry of Education, Southwest Jiaotong University, Chengdu 610036, China;

  • 2. Shanghai Aerospace Equipments Manufacturer Co., Ltd., Shanghai 200245, China

摘要

    摘要
  • 摘要: 针对GTAW填丝增材制造熔池尾部固液分界点检测难题，基于熔池液态边缘波动大，固态成形金属边缘波动小的特性，提出一种连续图像采集处理的熔池尾部固液分界点跟踪算法. 采用去噪、高斯滤波、边缘检测和阈值分割等算法预处理熔池尾部图像，根据连续图像熔池尾部边缘像素点坐标变化，计算其差异系数，通过多项式函数拟合像素点差异系数曲线，并求取其一阶导数，据此判定差异系数曲线折点，确定熔池尾部固液分界点. 结果表明，该算法有效地实现了GTAW填丝增材制造熔池尾部固液分界点的实时跟踪，算法简易、高效，具有良好的抗干扰能力.
    Abstract: This study aims at the solid-liquid separation point detection of molten pool tail in GTAW-based additive manufacturing. Based on characteristics of a large fluctuation of molten pool edge and a small fluctuation of solidified metal edge, a tracking algorithm for solid-liquid separation point of molten pool tail was proposed through continuous image acquisition. The image preprocessing including denoising, Gaussian filtering, edge detection and threshold segmentation was performed on molten pool tail image. The coefficient of variation was calculated according to the pixels coordinates, and the pixel coefficient of variation curve was fitted by the polynomial function. Then, the first-order derivative of the curve was obtained, and the coefficient of variation curve break point was determined to define the solid-liquid separation point. The results show that the proposed algorithm can effectively realize the real-time tracking of the solid-liquid separation point of the molten pool tail in GTAW-based additive manufacturing. The algorithm is simple, efficient and has a good anti-interference ability.
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    • 参考文献(15)
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  • 收稿日期:  2017-09-06

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