Application of Self-Adaptive Wavelet Neural Networks in Ultrasonic Detecting

被引：0
|
作者：
Yin, Xi-Peng [1 ]
Fan, Yang-Yu [1 ]
Duan, Zhe-Min [1 ]
Cheng, Wei [1 ]
机构：
[1] NW Polytech Univ, Dept Elect Engn, Xian, Shaanxi, Peoples R China
来源：
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ANTI-COUNTERFEITING, SECURITY, AND IDENTIFICATION IN COMMUNICATION | 2009年
关键词：
ultrasonic; self-adaptive; wavelet analysis; neural networks;
D O I：
10.1109/ICASID.2009.5276998
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
It is important to remove the noise signal effectively in non-destructive testing. Using the wavelet and neural network algorithm, the author constructed self-adaptive wavelet neural networks in the ultrasonic testing. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet neuron and optimized scale parameter. The simulation results showed less distortion and better noise cancellation, and the method can be widely applied ton ultrasonic detecting.
引用
收藏
页码：600 / 602
页数：3
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