基于被动视觉感知的MIG焊缝跟踪智能监测与模糊控制

IF 2.4 4区 材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING
Ming Zhu, Qingsong Ma, Runji Lei, Jun Weng, Yu Shi
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引用次数: 0

摘要

为了降低人员操作的风险,进一步提高焊接效率,必须开发MIG焊接过程电弧的焊缝跟踪技术,实现自动化制造。焊缝跟踪系统主要包括智能监测和模糊控制。在监测部分,建立了光学检测平台和被动视觉检测装置,对坡口和圆弧位置进行分析。建立了预处理流程和自适应增强算法,提高了图像的灰度值。利用深度学习程序对感兴趣区域进行选择和定位,提高检测的准确性。提出了圆弧位置计算模型,提取地理位置。控制部分,根据焊工的操作技巧,编制模糊逻辑规则,控制间隙中间圆弧位置。进行了控制实验,并与手动调节进行了比较。结果表明:(1)采用预处理流程和自适应增强算法,槽区和圆弧区的平均灰度值分别提高了114%和100%;(2)利用深度学习,兴趣区域包含槽形和振荡弧位置信息,可准确选取,mAP指数高达99.27%;(3)基于预置偏差测试,对准偏差检测像素误差在8像素以内。并配合对中偏差,距离可控制在±0.5 mm之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Intelligent monitoring and fuzzy control of MIG welding seam tracking based on passive visual sensing

Intelligent monitoring and fuzzy control of MIG welding seam tracking based on passive visual sensing

To reduce the risk of personnel operation and further improve welding efficiency, weld seam tracking in MIG welding process arc has to be developed for automatic manufacturing. Weld seam tracking system mainly contains intelligent monitoring and fuzzy control. For monitoring part, an optical testing platform and a passive visual detecting device are established to analyze groove and arc position. Also, preprocessing workflow and adaptive enhancement algorithm are built to increase image gray values. Deep learning program is used to select and locate interest area to improve the accuracy of detection. The arc position calculation model is also proposed to extract geographic location. For control part, based on welder’s operation skills, fuzzy logic rules are programmed to control the arc position at the middle of gap. Also, control experiments are carried out and compared with manual adjustment. Results show that: (1) with preprocessing workflow and adaptive enhancement algorithm, the average gray value of the groove area and the arc area increased by 114% and 100%; (2) by using deep learning, the interest area contains information of groove shape and oscillating arc position and could be selected accurately, and the mAP index is as high as 99.27%; and (3) based on the preset deviation test, the pixel error of the alignment deviation detection is within 8 pixels. And with the alignment deviation, distance can be controlled between ± 0.5 mm.

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来源期刊
Welding in the World
Welding in the World METALLURGY & METALLURGICAL ENGINEERING-
CiteScore
4.20
自引率
14.30%
发文量
181
审稿时长
6-12 weeks
期刊介绍: The journal Welding in the World publishes authoritative papers on every aspect of materials joining, including welding, brazing, soldering, cutting, thermal spraying and allied joining and fabrication techniques.
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