首页> 外文会议>Computational Intelligence for Measurement Systems and Applications, 2009. CIMSA '09 >Deviation recognition of high speed rotational arc sensor based on support vector machine
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Deviation recognition of high speed rotational arc sensor based on support vector machine

机译:基于支持向量机的高速旋转电弧传感器偏差识别

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Signal patterns of high speed rotational arc sensor in gas metal arc welding (GMAW) have been studied. For V-groove butt joint, a geometry model of the weld bead profile and torch rotating has been developed. Welding current waveforms of both simulations and experiments have been analyzed. The welding current waveforms simulated based on the mathematical model are consistent with those captured in welding experiments, which proves that the mathematical model is correct. The signal features are analyzed as torch deviation from V-groove centre varied. The results show that the deviation of the welding torch is in proportion with the asymmetry of the current waveform in corresponding arc rotational cycle. A SVM is used to recognize the torch deviation. The results of this study are helpful to the design and application of high speed rotational arc sensors.
机译:研究了气体保护金属电弧焊(GMAW)中高速旋转电弧传感器的信号模式。对于V型槽对接,已开发出焊缝轮廓和焊枪旋转的几何模型。分析了模拟和实验的焊接电流波形。基于数学模型模拟的焊接电流波形与焊接实验中获得的波形一致,证明该数学模型是正确的。分析信号特征,即割炬偏离V形槽中心的偏差。结果表明,在相应的电弧旋转周期中,焊炬的偏差与电流波形的不对称性成正比。 SVM用于识别割炬偏差。这项研究的结果有助于高速旋转电弧传感器的设计和应用。

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