Wavelet-Neural Network for Detection Signals From Transverse Cracks in the Rail Head

被引：0
|
作者：
Nichoga, Vitalij [1 ]
Vashchyshyn, Liubomyr [2 ]
机构：
[1] Lviv Polytech Natl Univ, Lvov, Ukraine
[2] NAS Ukraine, Karpenko Phys Mech Inst, Lvov, Ukraine
来源：
2015 16th International Conference on Computational Problems of Electrical Engineering (CPEE) | 2015年
关键词：
rail; transverse crack; CWT; ANN;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the implementation of artificial neural network (ANN) for detection signals from transverse cracks in the rails is presented. As input parameters, this network uses the coefficients of continuous wavelet transform (CWT), which are obtained from the analysis of signals recorded during the magnetodynamic flaw detection of rails.
引用
收藏
页码：132 / 134
页数：3
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