Bearing fault detection and diagnosis based on order tracking and Teager-Huang transform |
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Authors: | Hui Li Yuping Zhang Haiqi Zheng |
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Affiliation: | 1.Department of Electromechanical Engineering,Shijiazhuang Institute of Railway Technology,Shijiazhuang,P.R. China;2.First Department,Shijiazhuang Mechanical Engineering College,Shijiazhuang,P.R. China |
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Abstract: | The vibration signal of the run-up or run-down process is more complex than that of the stationary process. A novel approach
to fault diagnosis of roller bearing under run-up condition based on order tracking and Teager-Huang transform (THT) is presented.
This method is based on order tracking, empirical mode decomposition (EMD) and Teager Kaiser energy operator (TKEO) technique.
The nonstationary vibration signals are transformed from the time domain transient signal to angle domain stationary one using
order tracking. EMD can adaptively decompose the vibration signal into a series of zero mean amplitude modulation-frequency
modulation (AM-FM) intrinsic mode functions (IMFs). TKEO can track the instantaneous amplitude and instantaneous frequency
of the AM-FM component at any instant. Experimental examples are conducted to evaluate the effectiveness of the proposed approach.
The experimental results provide strong evidence that the performance of the Teager-Huang transform approach is better to
that of the Hilbert-Huang transform approach for bearing fault detection and diagnosis. The Teager-Huang transform has better
resolution than that of Hilbert-Huang transform. Teager-Huang transform can effectively diagnose the faults of the bearing,
thus providing a viable processing tool for gearbox defect monitoring. |
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