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实验研究表明,随着乳化液泵曲柄轴承的不断磨损,振动信号频谱中出现了以连杆固有振动频率为中心的高频带,并且振动信号的能量具有向高频带集中的趋势,因此高频带的能量明显上升。利用小波包频带能量特征提取技术所提取的振动信号各频带相对能量的特征信息,为曲柄轴承磨损程度的识别提供了定量的依据,结合故障分类识别算法,能够实现故障的早期诊断。
Experimental results show that with the constant wear of the crankcase bearing of emulsion pump, the high frequency band centering on the natural frequency of the connecting rod appears in the vibration signal spectrum, and the energy of the vibration signal tends to concentrate towards the high frequency band. Therefore, The energy of the band rises significantly. The characteristic information of the relative energy of each frequency band of the vibration signal extracted by the wavelet packet energy feature extraction technology provides a quantitative basis for the identification of the wear degree of the crank bearing. Combined with the fault classification and identification algorithm, the early diagnosis of the fault can be realized.