摘要
针对齿轮故障信号易受噪声干扰导致故障特征难以提取的问题,提出一种基于变分模态分解(variational mode decomposition,VMD)和最大重叠离散小波包变换(maximal overlap discrete wavelet packet transform,MODWPT)相结合的信号去噪方法。采用VMD方法将齿轮振动信号分解成一系列不同中心频率的固有模态函数(intrinsic mode function,IMF),对VMD分解过程中影响其精度的主要参数选择方法进行了探究,提出相关参数的选取依据。结合能量熵增量-频域互相关系数准则以剔除分解出的高频噪声和虚假干扰成分;采用MODWPT方法对包含高频噪声的IMF分量进行去噪,以进一步提升信号的去噪效果和性能指标;最后将去噪后高频IMF分量同表征信号自身特征的敏感模态分量重构为去噪信号。通过仿真信号和齿轮断齿故障信号的分析,证明了所提方法的有效性和实用性。
Aiming at the problem that gear vibration signal is easily affected by noise and it is difficult to extract the fault feature of it,a method for gear vibration signal de-noising based on variational mode decomposition(VMD)and maximal overlap discrete wavelet packet transform(MODWPT)was proposed.Firstly,VMD was used to decompose the gear vibration signal into a number of intrinsic mode functions(IMFs)in different center frequency scales.For this method,the parameter selection that affects the accuracy of VMD decomposition has been deeply studied,and the solution to this problem was given.Then,a joint de-noising algorithm based on the criterion of energy entropy increment and frequency domain cross correlation coefficient was used to eliminate high frequency noise components and false components,in order to improve the de-noising effect and performance index.Finally,the high frequency noise components were decomposed by MODWPT,the high frequency IMF component after de-noising and the IMF components representing the characteristics of the signal itself reconstructed the de-noising signal.This method was applied in fault diagnosis of simulation signal and measured gear breakage fault signal.The results proved the effectiveness and practicality of the proposed method.
作者
周小龙
徐鑫莉
王尧
刘薇娜
姜振海
马风雷
ZHOU Xiaolong;XU Xinli;WANG Yao;LIU Weina;JIANG Zhenhai;MA Fenglei(Mechanical Engineering College,Beihua University,Jilin 132021,China;Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China;College of Mechanical and Electric Engineering,Changchun University of Science and Technology,Changchun 130022,China;School of Mechatronic Engineering,Changchun University of Technology,Changchun 130012,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2021年第12期265-274,289,共11页
Journal of Vibration and Shock
基金
国家自然科学基金(51505038)
吉林省科技厅重点科技攻关项目(222170102058)
吉林省教育厅“十三五”科学研究规划项目(JJKH20190639KJ)。
关键词
变分模态分解
最大重叠离散小波包变换
去噪
齿轮
特征提取
variational mode decomposition
maximal overlap discrete wavelet packet transform
de-noising
gear
feature extraction
