小波降噪与快速包络谱峭度相结合的轴承组件故障诊断技术

作为飞轮重要的旋转支撑部件，轴承组件的性能对飞轮寿命有着重大影响,因此如何在早期对轴承组件进行筛选显得尤为重要。轴承组件在故障初期，其故障特征比较微弱，故障信号很容易淹没在背景噪声信号中，给轴承组件的早期故障判断和定位带来了很大的困难。本文以飞轮常用轴承组件为研究对象，基于快速包络谱峭度的振动测试方法，先通过对采集的轴承组件振动信号进行小波降噪，提高特征信号的信噪比，然后对振动信号进行全频段的峭度分析，可以对轴承组件进行早期的故障诊断并进行故障定位，得到轴承组件故障频率，为后续轴承组件故障诊断研究提供方法手段。

Fault Diagnosis Technology of Bearing Assembly Based on Wavelet Denoising and Fast Envelope Kurtogram

As the most important part of flying wheel, the characteristics of bearing assembly influence life of flying wheel. So it is very important for bearing assembly to diagnose incipient faults. At the initial stage of bearing assembly failure, its fault characteristics are relatively weak, and the fault signal is easily submerged in the background noise signal, which brings great difficulties to the early fault judgment and positioning of bearing assembly. Based on the vibration test method of fast envelope kurtogram, the vibration signal of the collected bearing assembly is denoised by wavelet to improve the signal-to-noise ratio of the special diagnosis signal firstly. Then the full-frequency kurtosis analysis of the vibration signal is carried out. The incipient fault of bearing assembly is diagnosed and located exactly in order to get the fault frequency, which will offer an effective method for screening bearing assembly.