基于支持向量机的摩擦焊超声检测缺陷识别  

Blemish Identify in Ultrasonic Testing of Friction Welded Joints Based on Support Vector Machine

作　　者：秦东浩[1] 王玉[1] 高大路[1] 孙涛[1] 

机构地区：[1]西北工业大学机电学院,陕西西安710072

出　　处：《机械与电子》2010年第4期36-39,共4页Machinery & Electronics

摘　　要：为准确识别摩擦焊试件接头主要缺陷类型,采用小波包变换对一维超声信号进行处理,利用能量故障"法提取信号特征值,并将特征值引入一对多"支持向量机进行分类识别.通过验证发现,支持向量机较好解决了小样本、非线性和高维数问题,准确率高、容易在线实施,具有较强推广能力.For identificating main kinds of defi- ciencies in the friction welded joints accurately, then using wavelet packet tansform to analyse de- tectional signal of one - demension in the experi- ence,extract the eigenvalues with ’energy-fail- ure＇ method,then cite these eigenvalues in ‘1 -v- r＇ support vector machine to classficate and identi- float. The experiment shows that, support vector machine works accuractly and can be implied online easily, solve relatively well less samples, nonlinear, high dimension problems and is practical.

关 键 词：摩擦焊 无损检测 超声波 小波包 支持向量机 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]