东南大学学报（英文版）2021，Vol.37Issue(1)：22-32,11.DOI:10.3969/j.issn.1003-7985.2021.01.004
基于复合字典降噪和优化傅里叶分解的齿轮箱故障特征提取方法
A fault feature extraction method of gearbox based on compound dictionary noise reduction and optimized Fourier decomposition
摘要
Abstract
Aimed at the problem that Fourier decomposition method(FDM)is sensitive to noise and existing mode mixing cannot accurately extract gearbox fault features,a gear fault feature extraction method combining compound dictionary noise reduction and optimized FDM(OFDM)is proposed.Firstly,the characteristics of the gear signals are used to construct a compound dictionary,and the orthogonal matching pursuit algorithm(OMP)is combined to reduce the noise of the vibration signal.Secondly,in order to overcome the mode mixing phenomenon occuring during the decomposition of FDM,a method of frequency band division based on the extremum of the spectrum is proposed to optimize the decomposition quality.Then,the OFDM is used to decompose the signal into several analytic Fourier intrinsic band functions(AFIBFs).Finally,the AFIBF with the largest correlation coefficient is selected for Hilbert envelope spectrum analysis.The fault feature frequencies of the vibration signal can be accurately extracted.The proposed method is validated through analyzing the gearbox fault simulation signal and the real vibration signals collected from an experimental gearbox.关键词
傅里叶分解/复合字典/模态混叠/齿轮箱故障/特征提取Key words
Fourier decomposition/compound dictionary/mode mixing/gearbox fault/feature extraction分类
机械制造引用本文复制引用
毛一帆,许飞云..基于复合字典降噪和优化傅里叶分解的齿轮箱故障特征提取方法[J].东南大学学报（英文版）,2021,37(1):22-32,11.基金项目
The National Natural Science Foundation of China(No.51975117),the Key Research&Development Program of Jiangsu Province(No.BE2019086). （No.51975117）
