Optimization of pulsed thermography inspection by partial least-squares regression

被引：93

作者：

Lopez, Fernando ^{[1
]}

Ibarra-Castanedo, Clemente ^{[2
]}

Nicolau, Vicente de Paulo ^{[1
]}

Maldague, Xavier ^{[2
]}

机构：

[1] Univ Fed Santa Catarina, Dept Mech Engn, BR-88040900 Florianopolis, SC, Brazil

[2] Univ Laval, Dept Elect & Comp Engn, Quebec City, PQ G1K 704, Canada

来源：

NDT & E INTERNATIONAL | 2014年 / 66卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Partial least squares regression; Pulsed thermography; Signal processing techniques; Composite materials; Thermal nondestructive testing; IMAGES;

D O I：

10.1016/j.ndteint.2014.06.003

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

This paper introduces and tests a statistical correlation method for the optimization of the pulsed thermography inspection. The method is based on partial least squares regression, which decomposes the thermographic PT data sequence obtained during the cooling regime into a set of latent variables. The regression method is applied to experimental PT data from a carbon fiber-reinforced composite with simulated defects. The performance of the regression technique is evaluated in terms of the signal-to-noise ratio. The results showed an increase in the SNRs for 96% of the defects after processing the original sequence with PLSR. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：128 / 138

页数：11

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