Use of Artificial Neural Networks in Identification of Modulated Pulses Due to Flaws

被引：0
作者：
V. S. Khandetskii
I. N. Antonyuk
机构：
[1] Dnepropetrovsk National University,
来源：
Russian Journal of Nondestructive Testing | 2001年 / 37卷
关键词：
Neural Network; Artificial Neural Network; Nondestructive Testing; Noise Intensity; Modulate Pulse;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The analysis of a number of publications proved that artificial neural networks show much promise in identification of signals and images in nondestructive testing. A three-layered neural network with backward propagation has been used in separating noisy signals due to flaws from spurious signals (due to a slant or separation of an eddy-current transducer) in the process of eddy-current testing. Network characteristics at different numbers of neurons in its layers have been investigated. Probabilities of signal identification at different rms noise intensities have been determined.
引用
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页码：278 / 285
页数：7
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