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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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【Citations】
Chinese Journal Full-text Database 4 Hits
1 LIU Zhi-chuan;TANG Li-wei;CAO Li-jun;Department of Artillery Engineering,Ordnance Engineering College;;Feature extraction of rolling bearing's weak fault based on MED and FSK[J];振动与冲击;2014-14
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【Co-citations】
Chinese Journal Full-text Database 10 Hits
1 TANG Guiji;PANG Bin;School of Energy,Power and Mechanical Engineering,North China Electric Power University;;Application of ITT transform in fault diagnosis of wind turbine rolling bearing[J];电力自动化设备;2017-09
2 ZHANG Wen-jing;ZHANG Lei;LIU Ming;Zhengzhou Coal Mining Machinery Manufacturing School;Key Laboratory of State Monitoring and Control of the Ministry of Education (North China Electric Power University);;Fault Diagnosis of Wind Turbine Gearbox Based on Wavelet Transform and BP Neural Network[J];自动化技术与应用;2017-06
3 CHEN Haizhou;WANG Jiaxu;TANG Baoping;LI Junyang;State Key Laboratory of Mechanical Transmission,Chongqing University;School of Aeronautics and Astronautics,Sichuan University;;Helicopter rolling bearing hybrid faults diagnosis using minimum entropy deconvolution and Teager energy operator[J];振动与冲击;2017-09
4 Jin Xiaohang;Sun Yi;Shan Jihong;Wu Genyong;Key Laboratory of E & M,MOE,Zhejiang University of Technology;College of Mechanical Engineering,Zhejiang University of Technology;Institute of Ocean Research,Zhejiang University of Technology;Zhejiang Windey Co.,LTD.;State Key Laboratory of Wind Power System;;Fault diagnosis and prognosis for wind turbines:An overview[J];仪器仪表学报;2017-05
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6 SUN Shoubao;GUO Yu;WU Xing;Key Laboratory of Vibration & Noise under Ministry of Education of Yunnan Province,Kunming University of Science and Technology;;Double impulse phenomenon extraction of outer race spalled rolling element bearings based on acoustic emission signals[J];振动与冲击;2017-04
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