|本期目录/Table of Contents|

[1]陈宗祥,陈明星,焦民胜,等. 基于改进 EMD 和双谱分析的电机轴承故障诊断实现[J].电机与控制学报,2018,22(05):78-8.[doi:10.15938/j.emc.2018.05.010]
 CHEN Zong-xiang,CHEN Ming-xing,JIAO Min-sheng,et al. Fault diagnosis of motor bearings using modified empiricalmode decomposition and bi-spectrum[J].,2018,22(05):78-8.[doi:10.15938/j.emc.2018.05.010]
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 基于改进 EMD 和双谱分析的电机轴承故障诊断实现()
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
22
期数:
2018年05
页码:
78-8
栏目:
出版日期:
2018-05-15

文章信息/Info

Title:
 Fault diagnosis of motor bearings using modified empiricalmode decomposition and bi-spectrum
作者:
 陈宗祥 陈明星 焦民胜 葛芦生
 (安徽工业大学 电气与信息工程学院,安徽 马鞍山 243000)
Author(s):
  CHEN Zong-xiangCHEN Ming-xingJIAO Min-shengGE Lu-sheng
 (College of Electrical and Information Engineering,Anhui University of Technology,Ma’anshan 243000,China)
关键词:
电机轴承 故障检测 改进经验模态分解 双谱
Keywords:
 motor bearings fault diagnosis modified empirical mode decomposition bi-spectrum
分类号:
TM307
DOI:
10.15938/j.emc.2018.05.010
文献标志码:
A
摘要:
 轴承是电机设备极重要的部件。轴承故障检测是非常必要的。通过将改进的经验模态分解和双谱分析相结合的故障检测方法来有效诊断电机轴承的早期故障。首先,针对 EMD 分解无法得到严格单分量 IMF 的问题,利用小波包分解将轴承振动信号分解为窄带信号并选取能量最集中的频带进行重构,从而降低故障信号的复杂性,抑制模态混叠问题; 然后利用经验模态分解方法根据信号的固有波动模式将其分解为一系列 IMF 分量; 再通过方差贡献率检验去除其中的虚假分量; 最后,利用双谱分析信号的调制关系进行解耦,得到故障特征频率。验证结果表明,所提出的分析方法能有效诊断轴承故障。
Abstract:
 Bearing plays an important role in the area of Motor. To ensure the safe and reliable operationof the motor,fault diagnosis of motor bearings is required. A fault feature extraction approach based onmodified empirical mode decomposition and bi-spectrum was proposed to detect bearing incipient faults ofmotors in running condition. Firstly,the vibration signals were decomposed into individual frequencybands by wavelet packet and the highest energy band was reconstructed. Then EMD method was used todecompose the signal and gete a series of intrinsic mode function component,variance contribution wasused to eliminate false components in EMD. Finally,the bi-spectrum was applied to identify these inter-actions and detect the bearing faults while it is still in an incipient stage. Through processing and analy-zing the rolling bearing experimental data of West Reserve University,it shows the method is effective.

参考文献/References:

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备注/Memo

备注/Memo:
 收稿日期: 2016 - 10 - 18
基金项目: 国家自然科学基金( 51277003)
作者简介: 陈宗祥( 1975—) ,男,博士,副教授,研究方向为电力电子与电机控制技术;
陈明星( 1994—) ,男,博士研究生,研究方向为电机控制理论;
焦民胜( 1992—) ,男,硕士研究生,研究方向为电力电子技术与电机控制理论;
葛芦生( 1962—) ,男,博士,教授,研究方向为电力电子及其控制技术。
更新日期/Last Update: 2018-07-02