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A novel feature extraction method of eddy current testing for defect detection based on machine learning
یک روش جدید استخراج ویژگی آزمایش جریان ادی برای تشخیص نقص بر اساس یادگیری ماشین-2019 In eddy current testing, the trajectory of the impedance data due to a defect is presented as a Lissajous curve (LC)
in the complex plane. This paper proposes a novel analytical model for describing a LC. Further, a new feature
extraction method is implemented which automatically computes four geometric features (amplitude, width,
angle and symmetry) from Lissajous figures. In addition, six machine learning-based classifiers are used for
automatic defect identification based on these features. High detection rates are achieved for both the simulated
and experimental data, which demonstrates the flexibility of the analytical model and the validity of the
methodology. Keywords: Eddy current testing | Lissajous figure | Feature extraction | Machine learning |
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