基于平移不变多小波变换的齿轮故障诊断  

Fault Diagnosis of Gear based on Translation Invariant Multiwavelet Transform

作　　者：华伟[1,2] 行志刚[2] 荆双喜[2] 

机构地区：[1]中国矿业大学机电与信息工程学院,北京100083 [2]河南理工大学机械与动力工程学院,河南焦作454003

出　　处：《机械传动》2016年第2期142-145,共4页Journal of Mechanical Transmission

摘　　要：机械设备发生故障时,反映设备故障特征的振动信号常淹没在背景噪声中,直接做频谱分析,很难提取其故障特征。将平移不变多小波降噪方法应用到仿真加噪冲击信号,提取出隐藏在噪声中的冲击特征。然后将该方法应用于齿轮箱试验台信号分析中,试验结果表明,平移不变多小波降噪方法能够有效地提取出齿轮箱断齿故障的冲击特征频率,诊断出齿轮箱的断齿故障,为故障诊断提供了准确的依据。仿真与试验分析验证了平移不变多小波降噪方法在故障诊断中的有效性。The vibration signal which reflecting the equipment fault feature often drowned in background noise when mechanical equipment occurring fault. The fault feature is very difficult to extract through frequency spectrum analysis. The translation invariant multiwavelet denoising method is applied to noisy impact simulation signal and extract impact features hidden in the noise. Then the method is applied to the signal analysis of gearbox test bed,the experimental results show that the impact feature frequency of broken tooth gearbox can be effectively extracted through the translation invariant multiwavelet denoising method and broken teeth fault can be diagnosed,an accurate basis for fault diagnosis is provided. Through the simulation and experiment analysis,the effectiveness of translation invariant multiwavelet denoising method in fault diagnosis is verified.

关 键 词：多小波 平移不变 信号降噪 故障诊断 

分 类 号：TH132.41[机械工程—机械制造及自动化]