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Spatial-Time-Step Features Fusion Algorithm in Eddy Current Pulsed Thermography

机译:涡流脉冲热成像中的空间 - 时间步长功能融合算法

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Eddy Current Pulsed Thermograph (ECPT) has received extensive attention due to high sensitivity detection with surface and subsurface cracks. However, it has unsolved detection problem of blind defect location without any prior knowledge. This paper presents a spatial-time-step features fusion algorithm to obtain defects reconstruction of whole specimen by blind scanning. The proposed method is intended to use features extraction by independent component analysis (ICA) and features selection by skewness. Finally, the optimal feature of each step is fused to obtain defects reconstruction image by using common orthogonal basis extraction (COBE). Experiments have been conducted to validate this study and it shows that this algorithm has a great effect on feature selection.
机译:由于具有表面和地下裂缝的高灵敏度检测,涡流脉冲温度计(ECPT)已经受到广泛的关注。然而,在没有任何先前知识的情况下,它具有盲目缺陷位置的未解决的检测问题。本文介绍了空间 - 时限特征融合算法,通过盲扫描获得整个样本的缺陷重建。所提出的方法旨在使用独立分量分析(ICA)和特征选择来使用特征提取和偏斜的特征。最后,通过使用公共正交基础提取(COBE)来融合每个步骤的最佳特征以获得缺陷重建图像。已经进行了实验以验证这项研究,并表明该算法对特征选择具有很大的效果。

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