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作 者:张海霞[1] Zhang Haixia(Department of Information Engineering,Henan Vocational College of Industry and Trade,Zhengzhou Henan 450000,China)
机构地区:[1]河南工业贸易职业学院信息工程系,河南郑州450000
出 处:《机械管理开发》2024年第1期7-8,12,共3页Mechanical Management and Development
基 金:河南省软科学研究计划项目(152400410203);河南省科技攻关项目(192102210134)。
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。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 muliple 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.
分 类 号:TN911[电子电信—通信与信息系统]
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