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Assessment of partially conductive cracks from eddy current non-destructive testing signals using support vector machine

机译:使用支持向量机从涡流无损检测信号评估部分导电裂纹

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摘要

This paper deals with a three-dimensional non-destructive evaluation of partially conductive cracks from eddy current testing signals. An SUS316L plate specimen containing a crack is non-destructively inspected by the eddy current method using numerical simulations. An extensive database of eddy current response signals is prepared while dimensional parameters of a crack together with its partial conductivity are varied in wide ranges. A Support Vector Machine classification algorithm is employed to solve the electromagnetic inverse problem. The acquired signals are employed for training the algorithm and for testing its performance. It is demonstrated that the Support Vector Machine algorithm is able to properly classify detected defects into proper classes with very high probability even the partial conductivity of a detected crack together with its width are unknown.
机译:本文针对涡流测试信号对部分导电裂纹进行了三维无损评估。使用数值模拟,通过涡流法对包含裂纹的SUS316L钢板试样进行无损检查。准备了一个广泛的涡流响应信号数据库,同时裂缝的尺寸参数及其部分电导率在很大范围内变化。支持向量机分类算法用于解决电磁逆问题。所采集的信号用于训练算法并测试其性能。事实证明,即使未知的裂纹的部分导电性及其宽度,支持向量机算法也能够以很高的概率将检测到的缺陷正确分类为适当的类别。

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