摘要
针对齿轮磨损故障信号非平稳性的特点,提出一种基于改进经验模态分解(EMD)频率族分离的齿轮磨损故障诊断方法。该方法采用改进经验模态分解方法将齿轮磨损振动信号分解成若干阶表征齿轮自身信息的固有模态函数(IMF),各阶IMF对应齿轮箱振动信号的各个频率族,通过对各频率族分量的分析来提取齿轮磨损振动信号的故障特征。仿真分析表明该方法能有效应用于齿轮故障分析,试验研究证明了基于改进EMD的频率族分离法能够有效地提取齿轮磨损故障特征信息。
The gear wear vibration signal is proved to be non-stationary. In view of this characteristic, a fault diagnosis method based on improved empirical mode decomposition （EMD） frequency family separation method is proposed. In this technique, the vibration signal of the gear box is decomposed with improved EMD method into a number of intrinsic mode functions, and the intrinsic mode functions are also the frequency family of the signal. The fault information can be obtained by analysis the frequency family. The simulation and experiment results indicate that this method can effectively extract fault characteristics and diagnose the fault of the gear box.
作者
杨恭勇
周小龙
李家飞
梁秀霞
Yang Gongyong Zhou Xiaolong Li Jiafei Liang Xiuxia(The Engineering Training Teaching Center, Northeast Electric Power University, Jilin Jilin 132012 Henan Xinyu Petroleum Machinery Manufacturing Company, Puyang Henan 457001)
出处
《东北电力大学学报》
2017年第5期39-43,共5页
Journal of Northeast Electric Power University
关键词
经验模态分解
频率族分离法
齿轮磨损
故障诊断
Empirical mode decomposition
Frequency family separation method
Gear wear
Fault diagnosis
