Fault diagnosis of sludge return pump based on MEEMD and ICA

TIAN Liyong; ZHANG Yizhe

doi:10.13873/J.1000-9787(2020)07-0142-03

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Fault diagnosis of sludge return pump based on MEEMD and ICA

更新时间：2025-09-11

- Fault diagnosis of sludge return pump based on MEEMD and ICA
- Vol. 39, Issue 7, Pages: 142-144+149(2020)
- 作者机构：
  
  辽宁工程技术大学机械工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)07-0142-03
  CLC： TH38
- Published：2020
- 稿件说明：
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[1]田立勇,张一辙.基于MEEMD与ICA的污泥回流泵故障诊断[J].传感器与微系统,2020,39(07):142-144+149.

TIAN Liyong, ZHANG Yizhe. Fault diagnosis of sludge return pump based on MEEMD and ICA[J]. 2020, 39(7): 142-144+149.
[1]田立勇,张一辙.基于MEEMD与ICA的污泥回流泵故障诊断[J].传感器与微系统,2020,39(07):142-144+149. DOI： 10.13873/J.1000-9787(2020)07-0142-03.

TIAN Liyong, ZHANG Yizhe. Fault diagnosis of sludge return pump based on MEEMD and ICA[J]. 2020, 39(7): 142-144+149. DOI： 10.13873/J.1000-9787(2020)07-0142-03.

摘要

针对污泥回流泵故障分析时常见的信号干扰

提出使用改进的集成经验模态分解（MEEMD）与ICA方法来进行故障诊断与分析。将振动信号进行MEEMD

得出一系列的IMF分量

通过计算各分量与原始信号的互相关系数

选出对应的分量重构

并与原始信号组成矩阵进行ICA计算

选取出符合条件的ICA成分进行频谱分析。通过对比MEEMD与ICA方法处理前后的正常运行和故障运行的特征频率

对污泥回流泵进行故障分析和诊断。实验结果表明:经过MEEMD与ICA方法处理后可以降低噪声的影响

有效进行故障诊断。

Abstract

In view of the common signal interference in the fault analysis of sludge return pump

the MEEMD and ICA methods are proposed for fault diagnosis and analysis. The vibration signal is decomposed by MEEMD to obtain a series of IMF components. By calculating the correlation coefficient between each component and the original signal

the corresponding components are selected for reconstruction. The corresponding components are formed into a matrix with the original signal for ICA calculation. By comparing the characteristic frequency of normal operation and failure operation before and after MEEMD and ICA treatment

the fault analysis and diagnosis of sludge reflux pump are carried out. The experimental results show that the MEEMD and ICA methods can reduce the influence of noise and effectively carry out fault diagnosis.

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references

基于Zoom-FFT的排污泵故障诊断与分析 [J]. 田立勇,吴境林. 机械设计与研究 . 2018(03)

基于无源振动传感器标签的轴承故障在线诊断技术 [J]. 肖艳霞,田杰,何怡刚,汪涛. 传感器与微系统 . 2018(05)

基于硬件自冗余的称重设备传感器故障检测方法 [J]. 卢赢,欧文,刘洋,卢圣文. 微型机与应用 . 2017(15)

LMD-ICA联合降噪方法在滚动轴承故障诊断中的应用 [J]. 卞家磊,朱春梅,蒋章雷,吕俊燕. 中国机械工程 . 2016(07)

钻井泥浆泵系统可用度Bayes置信限 [J]. 苏子美,朱丽平,苑惠娟,郭建英,于明友. 机械工程学报 . 2014(14)

基于双树复小波变换的轴承复合故障诊断研究 [J]. 胥永刚,孟志鹏,赵国亮. 仪器仪表学报 . 2014(02)

改进的EEMD算法及其应用研究 [J]. 郑近德,程军圣,杨宇. 振动与冲击 . 2013(21)

独立成分分析[M]. 电子工业出版社 , 海韦里恩, 2014

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