摘要
为提高变速器齿轮早期故障诊断的准确性和可靠性,提出了一种基于分数阶傅里叶变换(fractional Fourier transform,FRFT)滤波的全息阶比解调谱方法。对变速器变转速过程的水平与垂直测点振动包络信号进行分数阶滤波,分离出调制频率分量,再对分离后信号进行全息阶比谱分析,得到调制分量的全息阶比解调谱,并对齿轮早期点蚀故障进行故障诊断。试验结果表明,基于分数阶滤波的全息阶比解调谱,兼具分数阶滤波分离频率变化分量的特点与全息阶比谱融合多维特征的优势,既能有效分离变转速过程的调制分量,隔离其他分量和噪声干扰,又能有效融合两个方向的关键特征信息,有效诊断出单测点单特征方法难以识别的齿轮早期故障。
In order to improve the accuracy and reliability of early fault diagnosis of transmission gear,a holographic-order envelop demodulation spectrum based on fractional Fourier transform(FRFT) filter was proposed.Firstly,the FRFT filter method was adopted to filter the vibration envelope signals in horizontal and vertical directions of the transmission acceleration process,and the modulation component was separated.Then the separated component was analyzed by order envelop demodulation spectrum,and the holographic-order envelop demodulation spectrum of modulation order component was obtained,and the pitting failure of gear was diagnosed.The experimental results show that the holographic order spectrum based on FRFT filtering combines the advantages of the FRFT filtering that can separate frequency variation components and the holographic-order spectrum that can fuse multi-dimensional features,it can effectively separate the modulation component from acceleration process,isolate other components and noise interference,and integrate the feature information of the two directions.Compared with the single measurement point single feature method,it is more effective in diagnosing the early pitting fault of the gear.
作者
梅检民
常春
沈虹
赵慧敏
王双朋
MEI Jianmin;CHANG Chun;SHEN Hong;ZHAO Huimin;WANG Shuangpeng(School of Mechanical Engineering,Tianjin University,Tianjin 300072,China;Department of Military Vehicle Engineering,Army Military Transportation University,Tianjin 300161,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2023年第10期273-277,288,共6页
Journal of Vibration and Shock
基金
陆军装备部重点项目(LJ20202A050622)。
关键词
分数阶傅里叶变换(FRFT)滤波
全息阶比解调谱
早期故障
微弱特征
fractional Fourier transform(FRFT)filter
holographic order envelop demodulation spectrum
early failure
weak characteristics
