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《Journal of Vibration and Shock》 2015-22
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Fault diagnosis for rolling bearings based on phase space reconstruction and stationary subspace analysis

LIU Shang-kun;TANG Gui-ji;PANG Bin;Mechanical Engineering Department,North China Electric Power University;  
Rolling bearing's fault feature signals are non-stationary,transient and often submerged in background signals associated with the components of rotating speed and other noises. How to separate the fault feature signals from the rolling bearing's blind sources is an important issue. A method combining the phase space reconstruction technique with the stationary subspace analysis( SSA) was proposed. The fault vibration signal's dimension was increased by the phase space technique and the non-stationary source components in the high-dimensional signals were distinguished from the stationary components by using the SSA. Then,the selected non-stationary component with the maximum kurtosis value was de-noised by the minimum entropy deconvolution( MED). Finally,the de-noised non-stationary component was analyzed by the envelope spectrum to extract the fault characteristic frequency. The simulation and experiment results indicate that the proposed method can extract the fault frequency better than the envelope demodulation method based on empirical mode decomposition( EMD).
【Fund】: 河北省自然科学基金(E2014502052);; 中央高校基本科研业务费专项资金资助项目(2014MS156)
【CateGory Index】: TH133.33;TH165.3
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