基于降维双谱分析法的航空发动机轴承磨损故障分析

Fault analysis of aero-engine bearing wear based on bi-spectrum′s dimension reduction

航空发动机轴承发生故障时,其振动信号受周期脉冲力的影响多为含噪非平稳随机信号,采用传统的频谱分析法很难提取轴承故障的振动特征。对双谱进行对角切片处理形成降维双谱,并将其引入到航空发动机轴承故障振动信号分析中。采用降维双谱对仿真和实测的发动机轴承磨损振动数据进行处理,成功提取到轴承振动信号的调制频率成分,并准确判定故障。数据处理结果表明,降维双谱能够有效提取发动机轴承磨损振动特征频率,对轴承磨损故障具有较高的诊断率。

When fault was found on aero-engine bearing,due to the influence of periodic impulse excita⁃tion,vibration signals were usually noisy,non-stationary and random.It is difficult to be accurately extract⁃ed vibration characteristics of bearing fault from the vibration measurements via traditional frequency do⁃main analysis methods.To address this problem,the dimensionality-reduction bi-spectrum analysis meth⁃od via diagonal slice processing of the bi-spectrum was introduced for fault diagnosis of the aero-engine bearings in this research.The method was applied to analyze both the simulated and experimentally mea⁃sured vibration signals of the tested bearing with rub-impact fault.Results revealed that the modulation fre⁃quency signature was successfully extracted and the bearing fault part was accurately ascertained.Accord⁃ingly,the dimensionality-reduction bi-spectrum analysis method could effectively extract the fault charac⁃teristic frequency and is promising for rub-impact fault diagnosis of aero-engine bearings in application.