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通过脉冲热成像技术在碳纤维增强聚合物板材中进行缺陷检测时选择独立分量的方法。

Method of selecting independent components for defect detection in carbon fiber-reinforced polymer sheets via pulsed thermography.

作者信息

Rengifo Carlos Javier, Restrepo Andrés David, Nope Sandra Esperanza

出版信息

Appl Opt. 2018 Nov 20;57(33):9746-9754. doi: 10.1364/AO.57.009746.

Abstract

Carbon fiber-reinforced polymer (CFRP) is increasingly used by large industries because its characteristics are more favorable than those of traditional materials. However, due to mechanical stresses, or even manufacturing defects, CFRP tends to have internal defects, thus lowering the quality of the industrial processes in which it is used and compromising safety. A method for the early detection of internal defects in these materials, applicable to active pulsed thermography experiments, is presented herein. This method aims to select the most relevant components identified via the independent component analysis of sequences of thermographic images (thermograms) generated from the inspection of CFRP sheets to acquire a synthesis image that highlights the defects in the material. An application of this methodology to a CFRP sheet detects at least 20 of the 23 defects considered.

摘要

碳纤维增强聚合物(CFRP)因其特性优于传统材料而越来越多地被大型工业所使用。然而,由于机械应力甚至制造缺陷,CFRP往往存在内部缺陷,从而降低了其使用的工业生产过程的质量并危及安全。本文提出了一种适用于主动脉冲热成像实验的早期检测这些材料内部缺陷的方法。该方法旨在通过对碳纤维增强塑料板材检测生成的热成像序列(热图)进行独立成分分析,选择最相关的成分,以获取突出材料中缺陷的合成图像。将该方法应用于一块碳纤维增强塑料板材,能检测出所考虑的23个缺陷中的至少20个。

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