| 基于电弧声ARMA双谱分析对熔滴过渡类型SVM模式识别 |
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| 引用本文： | 樊丁,黄健康,石玗,陈剑虹.基于电弧声ARMA双谱分析对熔滴过渡类型SVM模式识别[J].上海交通大学学报,2008(Z1). |
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| 作者姓名： | 樊丁 黄健康 石玗 陈剑虹 |
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| 作者单位： | 兰州理工大学甘肃省有色金属新材料省部共建国家重点实验室，兰州理工大学有色金属合金省部共建教育部重点实验室 |
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| 摘 要： | 运用电弧声对熔滴过渡模式进行识别,获取不同熔滴过渡的电弧声信号,利用ARMA双谱对不同熔滴过渡的电弧声进行分析,并提取其特征向量,采用支持向量机(SVM)方法对所获得的特征向量进行模式识别,由此成功地识别了各种熔滴过渡类型.
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| 关 键 词： | 电弧声 ARMA双谱 熔滴过渡 支持向量机(SVM) 模式识别 |
Droplet Transfer Pattern Recognition by SVM Based on Arc Acoustic ARMA Bispectrum Analysis |
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| FAN Ding.Droplet Transfer Pattern Recognition by SVM Based on Arc Acoustic ARMA Bispectrum Analysis[J].Journal of Shanghai Jiaotong University,2008(Z1). |
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| Authors: | FAN Ding |
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| Abstract: | In order to do rapid recognition for droplet transfer in gas metal arc welding simply and effectively,welding arc sound was used to do droplet transfer pattern recognition.Through obtaining welding arc sound signals of different droplet tansifer,this paper analyzed welding arc sound of different droplet transfer by ARMA bispectrum and extracting eigenvector,then did pattern recognition to the obtained eigenvector by support vector machine(SVM).It can succeed in recognizing kinds of types of droplet transfer. |
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| Keywords: | welding arc acoustic ARMA bispectrum droplet transfer SVM pattern recognition |
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