A Novel Method Based on Support Vector Machine for Pipeline Defect Identification

摘要：

Based on introducing the basic theory and principle of support vector machine (SVM), after de-noising the ultrasonic echo signals using wavelet transform and with a view of data mining, a novel approach using SVM classification is discussed to identify the defects. The experiment results show that unlike conventional and artificial neural networks (ANN) identification methods the new technique performs better than conventional evaluation ones with advantages of high efficiency, lower cost, easy implement on-line, excellent generalization. The approach provides a novel technique means for nondestructive defect identification of various defects.

关键词： support vector machine (SVM) defect identification pattern classification ultrasonic inspection

作者: HUANG Jing CHEN Tian GUAN Binglei ZHOU Shiguan

作者单位: School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, Zhejiang, School of Electronic Engineering, Xidian University, Xian, Shaanxi, China, 710071

会议类型: 国际会议

会议名称: 第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)

会议地点: 重庆

会议语种:英文

页码: 155-158

在线出版日期: 2009-08-01（万方平台首次上网日期，不代表论文的发表时间）