基于Hilbert能量重心法的轴承状态识别方法研究

Condition recognition of rolling bearing based on Hilbert energy spectrum gravity center

状态识别是机械系统状态监测中重要的一环,而信号的特征提取又是其中的重要一步。时域中特征中有幅值、峰-峰值等,频域中有各阶频率幅值等,上述指标各有其优缺点。时频分析中,局域波利用了希尔伯特变换的瞬时频率的概念,使得它在信号的时频表示方面得心应手。本文以轴承在10Hz、15Hz、25Hz下正常、内环故障、外环故障为例利用希尔伯特能量重心值为特征来对希尔伯特能量重心进行研究和验证。

Pattern recognition is the key to the condition monitoring of mechanical system, and feature extraction of the signal is important too. The peak value is a common index in the time domain and the frequency domain. In the time-frequency domain, the local wave based on the instantaneous frequency is better than other methods. In this paper, the method of Hilbert energy spectrum gravity center will be showed.