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Establishing Correlation Between Current and Voltage Signatures of the Arc and Weld Defects in GMAWProcess

机译:在GMAW工艺中建立电弧和焊接缺陷的电流和电压特征之间的相关性

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摘要

Welding is one of the major metal-joining process employed in fabrication industries, especially in manufacturing of boilers and pressure vessels. Control of weld quality is very important for such industries considering the severe operating conditions. Industries are looking for some kind of real-time process monitoring/control that will ensure the weld quality online and prevent the occurrence of defects. In this paper an attempt is made to establish a correlation between the current and voltage signatures with the good weld and weld with porosity and burn through defect during the welding of carbon steel using gas metal arc welding (GMAW) process. Experimental setup has been established and experiments were conducted using a welding robot integrated with GMAW power source. The experimental setup includes online current and voltage sensors, data loggers, and signal processing hardware and software. Welding conditions are carefully designed to produce good weld and weld with defects such as burn through and porosity. Current and voltage signatures are captured using data acquisition system (DAS). Software has been developed to analyze the data captured by the DAS. Statistical methods are employed to study the transient data. The probability density distributions of the current and voltage signature demonstrates a good correspondence between the current and voltage signatures with the welding defect.
机译:焊接是制造行业,尤其​​是锅炉和压力容器制造中使用的主要金属连接工艺之一。考虑到苛刻的操作条件,控制焊接质量对于此类行业非常重要。工业界正在寻找某种实时过程监控/控制,以确保在线焊接质量并防止缺陷的发生。在本文中,尝试建立具有良好焊缝的电流和电压特征之间的相关性,以及在采用气金属电弧焊(GMAW)进行碳钢焊接过程中,具有气孔和烧穿缺陷的焊缝之间的关系。建立了实验装置,并使用集成了GMAW电源的焊接机器人进行了实验。实验设置包括在线电流和电压传感器,数据记录器以及信号处理硬件和软件。焊接条件经过精心设计,以产生良好的焊缝,并具有诸如烧穿和气孔之类的缺陷。使用数据采集系统(DAS)捕获电流和电压信号。已经开发了用于分析DAS捕获的数据的软件。采用统计方法研究瞬态数据。电流和电压信号的概率密度分布证明了电流和电压信号与焊接缺陷之间的良好对应性。

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