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| A compound fault features separation method of rolling bearing based on spectral kurtosis combined with maximum correlated kurtosis deconvolution |
| HU Aijun,ZHAO Jun,SUN Shangfei,HUANG Shenshen |
| Mechanical Engineering Department, North China Electric Power University,Baoding 071003, Hebei Province, China |
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Abstract Aiming at the problem that the compound fault features in vibration signal is difficult to be separated accurately,a compound fault separation method was proposed based on spectral kurtosis (SK) and maximum correlated kurtosis deconvolution (MCKD).Firstly,the fault signal was analyzed by spectral kurtosis,and resonance band was selected to carry out band-pass filtering to extract several fault signals.Secondly,the envelope demodulation method was used to analyze the extract vibration signals,complete the separation process for the vibration signal that can extract single fault feature.Finally,the maximum correlation kurtosis deconvolution was applied to the vibration signals that can separate single fault feature.The effectiveness of the method was verified by the improved compound fault simulation model.The analysis results of measured fault signals of rolling bearing show that the method can realize accurate separation of compound faults.
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Received: 04 September 2017
Published: 15 February 2019
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| Cite this article: |
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HU Aijun,ZHAO Jun,SUN Shangfei, et al. A compound fault features separation method of rolling bearing based on spectral kurtosis combined with maximum correlated kurtosis deconvolution[J]. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(4): 158-165.
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| URL: |
| http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2019/V38/I4/158 |
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