摘要
针对转子产生故障时的振动信号受噪声干扰大、故障特征不明显这一难题,提出基于集合经验模式分解(EEMD)降噪和傅里叶变换(FFT)的转子振动信号分析方法。首先利用EEMD方法将原始故障信号分解成若干本征模态分量(IMF),然后计算各分量与原始信号之间的相关系数,筛选出有用分量并进行信号重构。最后对重构信号进行傅里叶变换(FFT)得到振动信号的特征频率。数值模拟和实验结果证明该方法的有效性和实用性。
Due to the fact that rotor fault features are not obvious under the influence of strong background noise,a method based on ensemble empirical mode decomposition(EEMD)and FFT analysis is proposed.Firstly,the original signal is decomposed into several IMF components.Then,the correlation coefficient between each component and the original signal is calculated.According to these coefficients,the useful components are selected and the signal is reconstructed.Finally,characteristic frequency of the vibration signal is obtained by FFT.Numerical simulation and experimental results show the validity and practicability of this method.
作者
马转霞
费维科
周新涛
刘涛
MA Zhuanxia;FEI Weike;ZHOU Xintao;LIU Tao(Department of Mechanical Engineering,Xi’an Automotive Technology Vocational College,Xi’an 710038,China)
出处
《噪声与振动控制》
CSCD
2018年第4期165-168,共4页
Noise and Vibration Control
基金
陕西省教育厅专项科研计划资助项目(17JK1061)
西安汽车科技职业学院科研基金重点资助项目(2016KJ004)
关键词
振动与波
EEMD降噪
相关系数
FFT
故障特征
vibratuion and wave
EEMD noise reduction
correlation coefficient
FFT
fault feature
