液压泵的轴承特征信号提取及故障诊断

Bearing Signature Extraction for Hydraulic Pump Diagnostics

本文利用细化FFT分析和包络检测原理,检测蕴含于振动响应中的液压泵轴承故障特征。与传统的轴承故障检测技木相比,其优越性在于可以提取振动信号的高频能量中的低频调制信号,从而大大提高了故障特征信号的信噪比。关于轴承滚子点蚀故障的对比实验表明,包络分析是提取微弱低频调制信号的有效方法,尤其适于液压泵一类存在强烈动力噪声和其它振源干扰的场合。

Envelope Analysis based on ZOOM-FFT is investigated in detail for extracting weak frequency information of the bearing so as to develop an applicable algorithm of bearing fault diagnostics. Compared with traditional bearing fault diagnosis method, the approach proposed in this paper can detect the low frequency modulated components from high frequency band. Signal-noise ratio is greatly increased. The experimental work on the fault of bearing rolling element detection proved that the Envelope Analysis is a powerful method for bearing diagnostics, especially suitable to the mechanical system(?) with strong vibration contamination, such as piston pump and vane pump.