Real Time Flaw Detection and Characterization in Tube through Partial Least Squares and SVR: Application to Eddy Current Testing

被引：8

作者：

Ahmed, Shamim ^{[1
]}

Miorelli, Roberto ^{[1
]}

Calmon, Pierre ^{[1
]}

Anselmi, Nicola ^{[2
]}

Salucci, Marco ^{[2
]}

机构：

[1] CEA, LIST, Lab Simulat & Modelisat Electromagntisme, Saclay, France

[2] Univ Trento, ELEDIA Res Ctr ELEDIA UniTN, Via Sommar 9, I-38123 Trento, Italy

来源：

44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 37 | 2018年 / 1949卷

关键词：

D O I：

10.1063/1.5031523

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

This paper describes Learning-By-Examples (LBE) technique for performing quasi real time flaw localization and characterization within a conductive tube based on Eddy Current Testing (ECT) signals. Within the framework of LBE, the combination of full-factorial (i.e., GRID) sampling and Partial Least Squares (PLS) feature extraction (i.e., GRID-PLS) techniques are applied for generating a suitable training set in offline phase. Support Vector Regression (SVR) is utilized for model development and inversion during offline and online phases, respectively. The performance and robustness of the proposed GIRD-PLS/SVR strategy on noisy test set is evaluated and compared with standard GRID/SVR approach.

引用

页数：10

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