文章摘要
殷冬萌,王军,刘云飞.木塑复合材料缺陷及损伤的声发射信号特征分析及神经网络模式识别[J].,2007,26(6):352-356
木塑复合材料缺陷及损伤的声发射信号特征分析及神经网络模式识别
Characteristic analysis and pattern recognition of acoustic emission signals from flaw or damage in wood-plastic composites
  
中文摘要:
      针对木塑复合材料五种典型的缺陷及损伤机制,选择合适的木塑试样,应用三点弯曲的加载方法采集声发射信号。对主损伤区附近的声发射事件,应用小波变换提取特征参数,确定五类主要损伤机制所对应的声发射信号特征。采用B-P型反向传播神经网络构成的智能化模式分类器,对此五类声发射信号进行识别,获得了满意的效果.
英文摘要:
      Proper wood-plastic composite samples are chosen for five kinds of typical flaws or damages.Acoustic emission(AE)signals are collected in the three-point flexural tests.AE events near the main damage section are studied.Wavelet transform is ap- plied to extract characteristic parameters from major AE events.An intelligent pattern classifier with B-P neural network is used in recognition of those five kinds of AE signals successfully.
DOI:10.11684/j.issn.1000-310X.2007.06.006
中文关键词: 声发射  小波变换  神经网络  模式识别
英文关键词: Acoustic emission  Wavelet transform  Neural network  Pattern recognition
基金项目:
作者单位
殷冬萌 南京林业大学信息科学技术学院,南京,210037 
王军 南京林业大学信息科学技术学院,南京,210037 
刘云飞 南京林业大学信息科学技术学院,南京,210037 
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