| Characteristics analyzing and parametric modeling of the arc sound in CO2 GMAW for on-line quality monitoring |
| |
| 引用本文： | 马跃洲 马文斌 瞿敏 陈剑虹. Characteristics analyzing and parametric modeling of the arc sound in CO2 GMAW for on-line quality monitoring[J]. 中国焊接, 2006, 15(2): 6-13 |
| |
| 作者姓名： | 马跃洲 马文斌 瞿敏 陈剑虹 |
| |
| 作者单位： | State Key Laboratory of Gansu Advanced Non-ferrous Metal Materials, Lanzhou University of Technology, Lanzhou, 730050 |
| |
| 基金项目： | 国家高技术研究发展计划(863计划) |
| |
| 摘 要： | For on-line monitoring of welding quality, the characteristics of the arc sound signals in short circuit CO2 GMAW were analyzed in the time and frequency domains. The arc sound presents a series of ringing-like oscillations that occur at the end of short circuit i. e. the moment of arc re-ignition, and distributes mainly in the frequency band below 10 kHz. A concept of the arc tone channel and its equivalent electrical model were suggested, which is considered a time-dependent distributed parametric system of which the transmission properties depend upon the geometric and physical characteristics of the arc and surroundings, and is excited by the sound source results from the change of arc energy so that results in arc sound. The linear prediction coding （ LPC ） model is an estimation of the tone channel. The radial basis function （ RBF ） neural networks were built for on-line pattern recognition of the gas-lack in welding, in which the input vectors were formed with the LPC coefficients. The test results proved that the LPC model of arc sound and the RBF networks are feasible in on-line quality monitoring.
|
| 关 键 词： | LPC模型 RBF神经网络 GMAW 焊接 质量控制 |
Characteristics analyzing and parametric modeling of the arc sound in CO2 GMAW for on-line quality monitoring |
| |
| Ma Yuezhou,Ma Wenbin,Qu Min,Chen Jianhong. Characteristics analyzing and parametric modeling of the arc sound in CO2 GMAW for on-line quality monitoring[J]. China Welding, 2006, 15(2): 6-13 |
| |
| Authors: | Ma Yuezhou Ma Wenbin Qu Min Chen Jianhong |
| |
| Abstract: | For on-line monitoring of welding quality, the characteristics of the arc sound signals in short circuit CO2 GMAW were analyzed in the time and frequency domains. The arc sound presents a series of ringing-like oscillations that occur at the end of short circuit i. e. the moment of arc re-ignition, and distributes mainly in the frequency band below 10 kHz. A concept of the arc tone channel and its equivalent electrical model were suggested, which is considered a time-dependent distributed parametric system of which the transmission properties depend upon the geometric and physical characteristics of the arc and surroundings, and is excited by the sound source results from the change of arc energy so that results in arc sound. The linear prediction coding ( LPC) model is an estimation of the tone channel. The radial basis function ( RBF) neural networks were built for on-line pattern recognition of the gas-lack in welding, in which the input vectors were formed with the LPC coefficients. The test results proved that the LPC model of arc sound and the RBF networks are feasible in on-line quality monitoring. |
| |
| Keywords: | arc sound signal analysis LPC model RBF neural network GMAW quality monitoring |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
