首页> 外文会议>Conference on Independent Component Analyses, Wavelets, and Neural Networks Apr 22-25, 2003 Orlando, Florida, USA >Analysis of Characteristic Parameters in Nonideal Shock Wave Data: Wavelet Thresholds
【24h】

Analysis of Characteristic Parameters in Nonideal Shock Wave Data: Wavelet Thresholds

机译:非理想冲击波数据中的特征参数分析:小波阈值

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

A set of experiment was conducted to study the initial shock wave, which is generated in early launching stage and harmful to human and equipment. Profile of pressure-time history consists of shock wave and rocket noise,which are the two inherent flow features of rocket exhaust flow. This makes it difficult to calculate the typical parameters such as peak overpressure, positive duration and waveform coefficient. Thus the intensity of shock wave is hard to determine by traditional methods. Wavelet threshold de-noise is used in this paper to detect shock wave profile from noise. Daubechies and Symlets wavelet families are compared in threshold treating of shock wave data. Wavelet threshold plus apriori knowledge makes the initial shock wave well detected from rocket noise. Three characteristic parameters of shock wave are determined. The results show that low order wavelet with small support width can keep singularity of shock wave.
机译:进行了一系列实验来研究初始冲击波,该冲击波是在发射初期产生的,对人体和设备有害。压力-时间历史的轮廓包括冲击波和火箭噪声,这是火箭排气流的两个固有流动特征。这使得难以计算典型参数,例如峰值超压,正持续时间和波形系数。因此,传统方法很难确定冲击波的强度。本文使用小波阈值去噪从噪声中检测冲击波轮廓。比较Daubechies和Symlets小波族在冲击波数据的阈值处理中。小波阈值加上先验知识使得可以从火箭噪声中很好地检测出初始冲击波。确定了冲击波的三个特征参数。结果表明,低阶小波具有较小的支持宽度,可以保持激波的奇异性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号