基于改进傅里叶分解的齿轮箱振动信号处理
Vibration Signal Processing of Gear Box Based on Improved Fourier Decomposition
张海霞1
作者信息
- 1. 河南工业贸易职业学院信息工程系,河南 郑州 450000
- 折叠
摘要
为了提高齿轮箱运行精度,设计了基于改进傅里叶分解的故障诊断方法.把一个复杂非平稳信号以自适应方式分解成包含多个瞬时频率的傅里叶本征模态函数(FIMF),再对各FIMF分量瞬时幅值与频率实施预估,获得分量边际谱与初始信号时间频率的能量分布状态.对转子碰摩信号分析可以看到计算得到的第一个IMF包络谱与最初的4个IMF频谱.对滚动轴承中存在内圈故障振动信号分析,FIMF分量形成的包络谱内含有更少的低频信号.该研究可以拓宽到其他的传动领域,具有很好的应用价值.
Abstract
In order to improve the running accuracy of gear box,a fault diagnosis method based on improved Fourier decomposition is designed.A complex non-stationary signal is decomposed into Fourier intrinsic mode functions(FIMF)containing multiple instantaneous frequencies in an adaptive manner.Then,the instantaneous amplitudes and frequencies of each FIMF component are estimated to obtain the energy distribution of the marginal spectrum of the component and the time and frequency of the initial signal.The first IMF envelope spectrum calculated and the first 4 IMF spectra can be seen from the analysis of rotor rubbing signals.The analysis of vibration signals with inner ring faults in rolling bearings shows that the envelope spectrum formed by the FIMF component contains less low-frequency signals.This research can be extended to other transmission fields and has good application value.
关键词
振动信号/改进傅里叶分解/故障诊断/传动系统Key words
vibration signal/improved fourier decomposition/fault diagnosis/transmission system引用本文复制引用
基金项目
河南省软科学研究计划(152400410203)
河南省科技攻关计划(192102210134)
出版年
2024
NETL
NSTL
维普
万方数据