数据采集与处理2012，Vol.27Issue(3)：378-384,7.
基于多尺度小波支持向量机的脉冲漏磁缺陷三维轮廓重构
3-D Defect Profile Reconstruction from PMFL Signals Based on Multi-scale Wavelet SVM
摘要
Abstract
The wavelet and the support vector machine (SVM) are combined to form wavelet SVM(WSVM) based on the idea of multi-resolution approximation. Then, the method is introduced into a 3-D defect reconstruction. In the experiments, the horizontal component of magnetic flux density Bx is chosen as the input of WSVM nets , the defect geometric parameters, including length, width and depth are output. A mapping of pulsed magnetic flux leakage (PMFL) response signals onto 3-D profiles of defects is established, and the inversion of 3-D profiles of defects from magnetic flux leakage inspection signals is achieved. Experimental results show that the proposed method can combine the advantages of SVM and wavelet and has a high precision, a good generalization and tolerance of noise.关键词
脉冲漏磁/小波/支持向量机/三维轮廓重构Key words
pulsed magnetic flux leakage (PMFL)/ wavelet/ support vector machine (SVM)/ 3-D defect profile reconstruction分类
矿业与冶金引用本文复制引用
张韬,左宪章,田贵云,费骏骉..基于多尺度小波支持向量机的脉冲漏磁缺陷三维轮廓重构[J].数据采集与处理,2012,27(3):378-384,7.基金项目
河北省自然科学基金(E2008001258)资助项目. （E2008001258）
