基于小波包分析的航空发动机轴承故障诊断

Fault diagnosis of aero-engine bearings based on wavelet package analysis

关键词:  滚动轴承  航空发动机  主轴轴承+  故障诊断  小波包分解+  特征提取+

Key words:  Rolling bearing  Aircraft-engine  Main shaft bearings+  Fault diagnosis  Wavelet package decomposition+  Fault feature extraction+

摘要:

振动分析是进行滚动轴承状态监测与故障诊断的重要手段。当轴承某一元件表面出现局部损伤时,产生周期性的冲击脉冲力。因此,原来的平稳振动信号变成了非平稳振动信号。傅里叶变换在频域上是完全局部化的,但它不能提供任何时域的局部化特征,而窗口傅立叶变换尽管在时域和频域均具有一定的局部化特征,但其局部化却是固定不变的。针对常规方法难以准确分析非平稳信号的局限性,提出了基于小波分析的滚动轴承故障诊断方法,通过滚动轴承外表面损伤的实验信号进行小波包频谱分析,验证了基于小波分析的滚动轴承故障诊断方法是可靠、准确的,可进一步应用于航空发动机主轴轴承的状态监测和故障诊断。

Abstract:

Vibration analysis is widely used in the condition monitoring and fault detection of the rolling elernent bearings.When locally scathed,the bearings would bump the other parts periodically with the result that the seasonal impulses come into being.With enough broad band to overcast each connatural frequency of the whole bearings,the impulses necessarily arose each connatural vibrations and thereby the stationary vibrations turn into transients.Although well localized in frequency,the Fourier transform was localized none too well in time which makes it a cumbersome tool for transients.Moreover,a local time-frequency composition as the windowed Fourier transform,the short-time Fourier transform namely,it has the same resolution across the time-frequency plane because of the same spread of the window on which the resolution depends.If using conventional method for the vibration signal analysis,the non-stationary signals are hard to analyze.This paper investigates rolling bearings fault diagnosis based on wavelet analysis method,and the surface damnification fault signals are diagnosed by using the frequency domain analysis method of wavelet package decomposition.Experimental results show that the analysis methods of wavelet transform are reliable and accurate.They are useful for the condition monitoring and fault diagnosis to aero-engine rolling bearings.