计算机工程 ›› 2019, Vol. 45 ›› Issue (9): 270-275.doi: 10.19678/j.issn.1000-3428.0052458

• 开发研究与工程应用 • 上一篇    下一篇

基于改进HHT的脉搏信号分析方法

况雪1, 李智2, 王勇军1,2, 张绍荣1,2   

  1. 1. 桂林电子科技大学 电子工程与自动化学院, 广西 桂林 541004;
    2. 桂林航天工业学院 电子信息与自动化学院, 广西 桂林 541004
  • 收稿日期:2018-08-21 修回日期:2018-10-05 出版日期:2019-09-15 发布日期:2019-09-03
  • 作者简介:况雪(1993-),女,硕士研究生,主研方向为信号分析、模式识别;李智,教授、博士生导师;王勇军、张绍荣,讲师、博士研究生。
  • 基金项目:
    广西自动检测技术与仪器重点实验室基金(YQ19209);桂林航天工业学院基金(YJ1402)。

Pulse Signal Analysis Method Based on Improved HHT

KUANG Xue1, LI Zhi2, WANG Yongjun1,2, ZHANG Shaorong1,2   

  1. 1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China;
    2. College of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin, Guangxi 541004, China
  • Received:2018-08-21 Revised:2018-10-05 Online:2019-09-15 Published:2019-09-03

摘要: 利用传统希尔伯特-黄变换(HHT)处理脉搏信号时,经验模态分解(EMD)分解精度低,并且存在模态混叠问题。为此,提出一种改进的HHT方法。结合时变滤波(TVF)对脉搏信号进行EMD得到一系列本征模态函数(IMF),采用相关系数法提取有效的IMF分量,并对其运用希尔伯特变换得到脉搏信号的Hilbert谱和边际谱。实验结果表明,该方法可提高分解精度,有效解决模态混叠问题,同时去除信号中的干扰成分,得到的Hilbert谱和边际谱能够准确反映脉搏信号的时频特性。

关键词: 脉搏信号, 希尔伯特-黄变换, 模态混叠, 时变滤波, 相关系数法

Abstract: The traditional Hilbert-Huang Transform(HHT) has low accuracy in Empirical Mode Decomposition(EMD) when processing pulse signals,and there are mode mixing problems.In response to this problem,this paper proposes an improved HHT method.Combined with Time Varying Filtering(TVF),the pulse signal is decomposed by EMD to obtain a series of Intrinsic Mode Functions(IMFs).The correlation coefficient method is used to extract the effective IMF components,to which the Hilbert transform is applied to obtain the Hilbert spectrum and the marginal spectrum of the pulse signal.Experimental results show that the proposed method improves the accuracy of decomposition,effectively solves the mode mixing problem,and can remove the interference components in the signal.The obtained Hilbert spectrum and the marginal spectrum can more accurately reflect the time-frequency characteristics of the pulse signal.

Key words: pulse signal, Hilbert-Huang Transform(HHT), mode mixing, Time Varying Filtering(TVF), correlation coefficient method

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