基于电弧声ARMA双谱分析对熔滴过渡类型SVM模式识别

Droplet Transfer Pattern Recognition by SVM Based on Arc Acoustic ARMA Bispectrum Analysis

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.

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...