• CN:11-2187/TH
  • ISSN:0577-6686

›› 2005, Vol. 41 ›› Issue (11): 109-114.

• 论文 • 上一篇    下一篇

GMAW电弧声的参数化模型及应用

马跃洲;陈剑虹;梁卫东   

  1. 兰州理工大学材料学院
  • 发布日期:2005-11-15

PARAMETRIC MODELING OF THE ARC SOUND IN GMAW FOR ON-LINE QUALITY MONITORING

Ma Yuezhou;Chen Jianhong;Liang Weidong   

  1. College of Material Engineering, Lanzhou University of Science and Technology
  • Published:2005-11-15

摘要: 以焊接质量在线监控为目的,针对短路过渡气体保护焊(GMAW)电弧声信号进行了时域和频域特征分析,提出电弧声道的概念,建立其参数化等效电气模型。利用线性预测(LPC)模型参数构造径向基函数(RBF)神经网络输入样本空间,对焊接保护气流量不足进行了在线模式识别。研究认为:电弧声呈现振铃形信号,主要发生于短路结束再引弧时刻,大部分能量分布在10 kHz以下频带。电弧声源于电弧能量变化,电弧及其周边的物理和几何形态形成分布参数的声道系统。电弧声是声源和声道共同作用的结果,其频谱主要取决于声道的作用。声道可用时变系数的数字滤波器等效,LPC是其参数化模型的一个估计,在焊接质量在线监控方面具有应用价值。

关键词: 电弧声, 径向基函数神经网络, 熔化极气体保护电弧焊, 时频分析, 线性预测模型, 质量监控

Abstract: Aiming at on-line monitoring of welding quality, the time and frequency characteristics are analyzed of the arc sound signals in short circuit gas metal arc welding (GMAW). The concept of tone channel and its equivalent electrical model are suggested. The radical basis function (RBF) neural networks are applied for on-line pattern recognition of the gas-lack in welding, in which the input vectors of samples are constructed by the linear prediction coding (LPC) coefficients of sound signals. The research indicates that, the arc sound presents a ringing series of that occurs at the end of short circuit transfer or moment of arc re-ignition, and its energy mostly distributes in frequency band below 10 kHz. The arc tone channel is a time dependent distributed parameters system, of which the transmission properties depend upon many physical and geometrical factors of the arc and surroundings, and is excited by the sound source that generates from the change of arc energy, so that results in the sound. The tone channel can be equated with a time dependent coefficients digital filter, and can be represented parametrically with the LPC model of arc sound. The arc sound and its parametric model are valuable in on-line monitoring and controlling of welding quality.

Key words: Arc sound, Gas metal arc welding (GMAW), Linear prediction coding (LPC) model, Quality monitoring, Radical basis function (RBF) neural network, Time and frequency analysis

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