电子测量与仪器学报

巩晓赟,王宏超,杜文辽,丁丽丽.EEMD方法在转子碰摩故障诊断中的研究[J].电子测量与仪器学报,2017,31(3):415-421

EEMD方法在转子碰摩故障诊断中的研究

Research on EEMD in rub impact fault diagnosis of rotor system

DOI：10.13382/j.jemi.2017.03.013

英文关键词:fault diagnosis rotor rubbing EEMD fault characteristic

基金项目:国家自然科学基金（51405453）、国家自然科学基金（51205371）、河南省高等学校重点科研项目（16A460012）资助

作者	单位
巩晓赟	郑州轻工业学院机电工程学院郑州450002
王宏超	郑州轻工业学院机电工程学院郑州450002
杜文辽	郑州轻工业学院机电工程学院郑州450002
丁丽丽	郑州轻工业学院机电工程学院郑州450002

Author	Institution
Gong Xiaoyun	School of Mechanical and Electronic Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002，China
Wang Hongchao	School of Mechanical and Electronic Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002，China
Du Wenliao	School of Mechanical and Electronic Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002，China
Ding Lili	School of Mechanical and Electronic Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002，China

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中文摘要:

转子系统发生局部碰摩故障时，故障特征呈现出复杂的高倍频或分数倍频成分。为了实现多频率碰摩故障特征的有效提取，将集合经验模态分解方法（ensemble empirical mode decomposition, EEMD）应用到转子局部碰摩故障诊断中。首先利用仿真碰摩信号，验证了EEMD时频分析方法在碰摩故障诊断的有效性，其次通过对转子系统水平方向碰摩、竖直方向碰摩、水平竖直同时碰摩和正常4种不同振动状态的EEMD分解，计算基本模态分量（IMF）的振动强度，得出不同状态的振动强度趋势分布图。实验结果表明，EEMD方法能够从强噪声背景信号中提取出微弱碰摩特征，实现转子系统的碰摩故障诊断。

英文摘要:

For vibration signal generated by rubbing fault in rotary machinery including the single point rubbing and the partial rubbing, multi component harmonic frequencies are presented. An ensemble empirical mode decomposition (EEMD) method was introduced to resolve the difficulty of multi component fault feature extraction of rubbing fault. The rubbing fault signals created by simulation were decomposed clearly into different single frequency data by using EEMD method. The vibration signals from experiment rig of rub impact rotor were then analyzed under different directions rubbing, which include in horizontal, in vertical, in horizontal and vertical at the same time. The vibration strength belonged to different fault frequency in the frequency spectrum was obtained from the intrinsic mode function (IMF) based on EEMD respectively. The analysis results of the rubbing signals indicate that the multiple features can be better extracted with the EEMD, and is effective in analysis and recognition of rubbing fault.

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