Weak fault feature extraction of bearing based on sparse decomposition and frequency domain correlation kurtosis
ZHAO Le1,2, YANG Shaopu1,2, LIU Yongqiang2, GU Xiaohui1,2, WANG Jiujian2
1.School of Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, China; 2.State Key Laboratory of
Mechanical Behavior and System Safety of Traffic Engineering Structures, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Abstract：Under interference of strong background noise and complex excitation, early weak fault features of rolling bearing are often difficult to extract.The sparse representation method is an effective way to analyze non-stationary signals, and adopting K-SVD algorithm to construct an adaptive dictionary and OMP algorithm to sparsely decompose the acquired data is a common method in bearing fault diagnosis.Here, a method combining sparse decomposition and frequency domain correlation kurtosis was proposed to extract bearings’ early weak fault features.The frequency domain correlation kurtosis with the advantage to be able to accurately recognize bearing, etc.rotating machineries’ cyclic impact sequence features was used to construct the adaptive dictionary.Firstly, the frequency domain correlation kurtosis of the signal approached by each iteration was solved when performing sparse decomposition.Secondly, the position for the maximum frequency domain correlation kurtosis value was found.Finally, the signal corresponding to this position was used to reconstruct the original signal, calculate its envelope and envelope spectrum, and analyze bearing fault types.The analysis results of simulated signals and ones obtained in tests showed that the proposed method can be used to accurately identify bearing faults, and verify the effectiveness and superiority of this method in identifying cyclic impact sequences.
赵乐1,2，杨绍普1,2，刘永强2，顾晓辉1,2，王久健2. 基于稀疏分解和频域相关峭度的轴承微弱故障特征提取[J]. 振动与冲击, 2019, 38(23): 196-202.
ZHAO Le1,2, YANG Shaopu1,2, LIU Yongqiang2, GU Xiaohui1,2, WANG Jiujian2. Weak fault feature extraction of bearing based on sparse decomposition and frequency domain correlation kurtosis. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(23): 196-202.
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