Parameter optimized time-varying filter based empirical mode decomposition method for the fault diagnosis of rotors

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Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (10) : 162-168.

TANG Guiji,ZHOU Chong,PANG Bin,LI Nannan

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Abstract

In order to overcome the subjectivity and blindness of using the time-varying filter empirical mode decomposition (TVFEMD) to diagnose rotor faults, a method based on parameter optimization TVFEMD and Hilbert transform (HT) was proposed.First, the particle swarm optimization (PSO) was used to search for the best combination of parameters.Then, the TVFEMD was used to obtain a series of intrinsic mode functions (IMF).Finally, the HT was applied to the IMF to obtain the Hilbert time-frequency diagram and marginal spectrum of the signal, so as to diagnose the rotor fault type.The method has been applied to diagnose two typical rotor faults, i.e.unbalanced rotor with constant speed and oil film whirl with variable speed.The results show that the method based on the parameter optimized time-varying empirical mode decomposition and Hilbert transform can not only automatically select the parameters and achieve good decomposition results, but also accurately identify the typical faults such as rotor imbalance and oil film whirl.Compared with the modal decomposition method, it has obvious advantages.

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rotor / fault diagnosis / time-varying filtering / empirical mode decomposition / parameter optimization / Hilbert transform

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TANG Guiji,ZHOU Chong,PANG Bin,LI Nannan. Parameter optimized time-varying filter based empirical mode decomposition method for the fault diagnosis of rotors[J]. Journal of Vibration and Shock, 2019, 38(10): 162-168

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