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基于小波包变换的复合材料分层缺陷信号特征分析
引用本文:张冬雨,刘小方,杨剑,成坤.基于小波包变换的复合材料分层缺陷信号特征分析[J].兵工自动化,2009,28(11):56-58,68.
作者姓名:张冬雨  刘小方  杨剑  成坤
作者单位:第二炮兵工程学院,504室,陕西,西安,710025
摘    要:通过自行设计的超声波检测系统对模拟分层试样进行实验,提取出缺陷信号,并对缺陷信号进行频域分析,在此基础上进行了基于小波包乏换的缺陷信号特征提取和BP神经网络识别。通过“能量-缺陷”的信号特征提取方法,比较不同分层位置之间的信号特征,得到一些有用的数据和信息,为复合材料的质量评估提供了重要的参考依据。

关 键 词:复合材料  超声波检测  分层  小波包变换  BP神经网络

Signal Characteristic Analysis of Composite Delamination Defects Based on Wavelet Packet Transform
ZHANG Dong-yu,LIU Xiao-fang,YANG Jian,CHENG Kun.Signal Characteristic Analysis of Composite Delamination Defects Based on Wavelet Packet Transform[J].Ordnance Industry Automation,2009,28(11):56-58,68.
Authors:ZHANG Dong-yu  LIU Xiao-fang  YANG Jian  CHENG Kun
Affiliation:ZHANG Dong-yu,LIU Xiao-fang,YANG Jian,CHENG Kun (No. 504 Staff Room,Second Artillery Engineering College,Xi\'an 710025,China)
Abstract:Adopt self designed ultrasonic testing system to test the simulation delamination sample,extract defects signal,and make frequency spectral analysis on defects signal. On that basis,it extracted defects signal characteristic based on wavelet packet transform and identified the defects by means of the BP neural network. Through energy-defect method of signal characteristic extraction,it compared signal characteristic among different delamination parts,gets some useful data and information,provided a consulti...
Keywords:Composite  Ultrasonic testing  Delamination  Wavelet packet transform  BP neural network  
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