中国机械工程 ›› 2010, Vol. 21 ›› Issue (20): 2434-2437,2467.

• 机械基础工程 • 上一篇    下一篇

高压水射流反射声信号特征值提取方法的研究

杨洪涛;王从东;张东速;李梦;孙玉玲
  

  1. 安徽理工大学,淮南,232001
  • 出版日期:2010-10-25 发布日期:2010-10-29

Research on Feature Extraction Method of High Pressure Water-jet Reflective Sound Signals

Yang Hongtao;Wang Congdong;Zhang Dongsu;Li Meng;Sun Yuling
  

  1. Anhui University of Science & Technology,Huainan,Anhui,232001
  • Online:2010-10-25 Published:2010-10-29

摘要:

为了实现高压水射流靶物反射声特征值的有效提取,应用小波降噪方法和模极大值法分别获取对应靶物材质与几何形状参数声信号特征值。介绍了其基本原理,编制了相应的特征值提取程序。利用前混合磨料射流设备、传声器和高速数据采集设备等建立了反射声信号采集的试验装置,进行了对应模拟防步兵地雷、泥地和石块水射流探测试验并采集了数据,应用上述程序对数据进行处理,优化选用小波参数。试验结果显示:应用小波降噪的方法可以有效地将靶物反射声信号与水射流声信号、环境声信号分离,获得对应不同材料靶物的声信号特征值;利用模极大值法可以有效地获得对应不同几何形状参数靶物边界的声信号突变点特征值。这些特征值可以用于后续的靶物材质与几何形状参数的识别。

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Abstract:

In order to extract different eigenvalues of high pressure water-jet target effectively, the sound signal eigenvalues of target material and physical dimension were acquired by applying wavelet noise reduction and module maximum method. The basic principles were described in detail. The corresponding eigenvalues extracting software was programmed. The experimental facility collecting reflective sound signals was built by using mixed abradant water-jet equipment, mike and high-speed data acquisition equipment. The experiments detecting protecting arms mine, mud and stone by water-jet were done, and the data was acquired. The data was processed based on the software mentioned above. The wavelet parameters were well selected. The result shows that the sound signals of target reflection, water-jet and environment can be separated effectively by using wavelet noise reduction and the sound signal eigenvalues of different material target are obtained. The sound signal mutate spot eigenvalues of different physical dimension border are obtained effectively by using the module maximum method. These eigenvalues can be used to identify target material and physical dimension.

Key words: high pressure water-jet, reflective sound signal, target material, physical dimension, wavelet noise reduction, module maximum method

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