离心式压缩机转子故障识别的EEMD-PCA方法研究

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Abstract Aiming at small vibration but vibration signal characterized of non-stationary, non-linear and interfered with noise, fault identification method through EEMD together with PCA is proposed for rotor system in centrifugal compressor. Based on the choice of IMFs by correlation analysis combined with FFT, fluctuant variation index is constructed to recognize amplitude of added noise quantitatively. At that moment, 14 kinds of vibration estimated index are calculated further to form a standardized feature data set. Consequently, dimension reduction method of PCA can be used to obtain categories of vibration modes from different faults. Analysis results of typical faults vibration signal from rotor system in centrifugal compressor suggest that based on the elimination of interference from non-stationary and non-linear, primary vibration modes can be extracted fast and independent, thus feature regions which represent different fault categories can be formulated and also improved fault identification ability of centrifugal compressor efficiently.

Received: 08 August 2014 Published: 15 February 2016

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2016/V35/I4/148

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