Underdetermined blind source separation method of machine faults based on empirical mode decomposition

LI Zhi-nong; L Ya-ping; FAN Tao; LENG Chuan-guang

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Underdetermined blind source separation method of machine faults based on empirical mode decomposition

更新时间：2026-07-07

- Underdetermined blind source separation method of machine faults based on empirical mode decomposition
- Vol. 24, Issue 8, (2009)
- 作者机构：
  
  1. 郑州大学机械工程学院,郑州,450001
  2. 河南交通职业技术学院汽车工程系,郑州,450005
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009
- 稿件说明：
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LI Zhi-nong, L Ya-ping, FAN Tao, et al. Underdetermined blind source separation method of machine faults based on empirical mode decomposition[J]. 2009, 24(8).
DOI：

LI Zhi-nong, L Ya-ping, FAN Tao, et al. Underdetermined blind source separation method of machine faults based on empirical mode decomposition[J]. 2009, 24(8). DOI：

摘要

针对传统的机械故障源分离方法限于非高斯、平稳和相互独立的源信号

且传感器的观测数多于源数

机械故障源信号通常不易满足这些假设的局限性

提出了一种基于经验模态分解的机械故障欠定盲源分离方法.该方法对混合观测信号进行经验模态分解

然后重组本征模函数分量作为新的观测信号进行盲源分离

仿真和实验结果表明

该方法是有效的.

Abstract

The traditional mechanical fault source separation method is restricted to nongaussian

stationary and mutually independent source signals

and the number of observations is assumed to be more than the number of sources.These deficiencies may cause many problems in the application of fault diagnosis

because fault signals generally do not meet these conditions.Based on these deficiencies

an underdetermined blind separation method of machine faults based on empirical mode decomposition(EMD) was proposed.The proposed method was that the mixture signals were decomposed into a series of intrinsic mode functions(IMF) by the EMD method.These IMFs and original observations were composed into new observations

which was blindly separated.The simulation and experiment results show that the proposed method is very effective.

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