首页> 外文OA文献 >Application of Empirical Mode Decomposition Method for Characterization of Random Vibration Signals
【2h】

Application of Empirical Mode Decomposition Method for Characterization of Random Vibration Signals

机译:经验模态分解方法在随机振动信号表征中的应用

摘要

Characterization of finite measured signals is a great of importance in dynamical modeling and system identification. This paper addresses an approach for characterization of measured random vibration signals where the approach rests on a method called empirical mode decomposition (EMD). The applicability of proposed approach is tested in one numerical and experimental data from a structural system, namely spar platform. The results are three main signal components, comprising: noise embedded in the measured signal as the first component, first intrinsic mode function (IMF) called as the wave frequency response (WFR) as the second component and second IMF called as the low frequency response (LFR) as the third component while the residue is the trend. Band-pass filter (BPF) method is taken as benchmark for the results obtained from EMD method.
机译:有限测量信号的表征在动力学建模和系统识别中非常重要。本文介绍了一种用于表征测量的随机振动信号的方法,该方法基于一种称为经验模式分解(EMD)的方法。该方法的适用性在结构系统即spar平台的一个数值和实验数据中进行了测试。结果是三个主要信号分量,包括:作为第一分量嵌入到被测信号中的噪声,被称为波频率响应(WFR)的第一本征模函数(IMF)作为第二分量和被称为低频响应的第二IMF (LFR)作为第三成分,而残留物是趋势。以带通滤波器(BPF)方法为基准,以EMD方法获得的结果为基准。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

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