小波分析与人工神经网络在木质材料无损检测中的应用

孙建平; 王逢瑚; 于海鹏

doi:10.19455/j.mcgy.2004.05.008

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小波分析与人工神经网络在木质材料无损检测中的应用
Non-destructive Test for Wood Materials Based on Wavelet and Artificial Neural Network
1. 东北林业大学材料科学与工程学院
2. 东北林业大学材料科学与工程学院,哈尔滨,150040
2004年第5期页码：24-26
DOI： 10.19455/j.mcgy.2004.05.008

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[1]孙建平,王逢瑚,于海鹏.小波分析与人工神经网络在木质材料无损检测中的应用[J].木材工业,2004(05):24-26+33.

SUN Jian-ping, WANG Feng-hu, YU Hai-peng. Non-destructive Test for Wood Materials Based on Wavelet and Artificial Neural Network[J]. China Wood Industry, 2004,(5):24-26.
[1]孙建平,王逢瑚,于海鹏.小波分析与人工神经网络在木质材料无损检测中的应用[J].木材工业,2004(05):24-26+33. DOI： 10.19455/j.mcgy.2004.05.008.

SUN Jian-ping, WANG Feng-hu, YU Hai-peng. Non-destructive Test for Wood Materials Based on Wavelet and Artificial Neural Network[J]. China Wood Industry, 2004,(5):24-26. DOI： 10.19455/j.mcgy.2004.05.008.

摘要

介绍了小波变换和人工神经网络在无损检测中的工作原理,分析了小波变换处理非平稳信号提取特征值、人工神经网络进行模式识别的优点,并提出小波、人工神经网络以及松散型和紧致型小波神经网络在木质材料的无损检测中的应用。

Abstract

The principles of wavelet transmission and the application of artificial neural network in non-destruction testing（NDT）were reviewed and presented in this paper. Two types of wavelet and artificial neural network methods of NDT for wood materials were studied: laxation and densification. The advantages of wavelet transmission in getting eigenvalue and the merits of artificial neural network in realizing pattern recognition were described.