齿轮局部故障振动信号分析及提取方法研究  

Study on the analysis and extraction method of gear local fault vibration signal

作　　者：杨秀芳[1] 张西宁[2] YANG Xiufang;ZHANG Xi’ning(School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China;School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

机构地区：[1]西安理工大学机械与精密仪器工程学院,陕西西安710048 [2]西安交通大学机械工程学院,陕西西安710049

出　　处：《西安理工大学学报》2019年第1期28-33,共6页Journal of Xi'an University of Technology

基　　金：国家自然科学基金资助项目(51775433;51421004)

摘　　要：以齿轮局部故障为研究对象,建立了齿轮故障的振动模型,导出了齿轮局部故障的振动机理,分析了齿轮无故障振动信号和齿轮局部故障振动信号成分的异同点。在MATLAB环境下,采用小波变换算法对故障信号进行降噪处理,用希尔伯特变换对故障振动信号进行解调处理。结果表明,小波变换对强噪声干扰的机械振动信号能够进行有效的降噪处理,希尔伯特变换能从降噪后的故障振动信号中提取齿轮局部故障的特征信息。该结果在机械故障诊断中具有良好的实用价值。In this paper,a gear fault vibration model is established,with the gear vibration mechanism of local failure occurs exported,and the similarities and differences between the gear fault-free vibration signal and the local fault vibration signal analyzed.In the MATLAB environment,the wavelet transform algorithm is used to de-noising the fault signal,with the fault vibration signal demodulated with Hilbert transform.The results show that the wavelet transform can effectively reduce the noise of the mechanical vibration signal with strong noise.Hilbert transform can extract the local fault feature information from the fault vibration signals after noise reduction.The results have important theoretical significance and good practical value in mechanical fault diagnosis.

关 键 词：齿轮局部故障 振动机理 小波变换 希尔伯特变换 特征提取 

分 类 号：TH212[机械工程—机械制造及自动化] TH213.3