摘要
为解决提取齿轮故障特征时去除外部噪声的问题,以连续小波变换和自相关系数法为理论依据,以缺齿齿轮故障为例,提出了一种齿轮故障诊断方法。该方法能从所测量的含噪信号中确定出故障脉冲所对应的时间节点。利用多通带滤波器进行滤波处理,可以从提取的故障特征中有效地剔除寄生脉冲。实验表明,该方法能准确识别断齿振动信号的故障特征。
In order to solve the problem that can not denoising the external noise when extracting fault feature of gear,this paper introduces a method that can identify the time of periodic impulsive fault signatures from the measured noisy signal mixture on the basis of CWT （Continuous Wavelet Transfon） and auto-correlation coefficient method.A comb filter can be applied to extract fault features in time-scale domain,the spurious impulses can be removed effectively from the extracted fault feature.Experiments show that this method can accurately identifiy the fault feature of impulsive signals with missing tooth.
出处
《吉林大学学报（信息科学版）》
CAS
2014年第2期172-176,共5页
Journal of Jilin University（Information Science Edition）
基金
引进国际先进林业科学技术"948"基金资助项目(2013-4-20)
关键词
连续小波变换
自相关系数
齿轮
故障诊断
特征提取
continuous wavelet transfon （CWT）
autocorrelation coefficient
gear
fault diagnosis
feature extraction
