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A signal analysis technique for bearing fault diagnosis based on ensemble empirical mode decomposition (EEMD) and Hilbert-Huang transform (HHT) is presented. EEMD can adaptively decompose vibration signal into a series of zero mean Amplitude Modulation-Frequency Modulation (AM-FM) Intrinsic Mode Functions (IMFs) without mode mixing. Hilbert transform tracks the modulation energy of the interesting...
Varying speed machinery fault diagnosis is more difficult due to non-stationary machine dynamics and vibration. A new approach to fault diagnosis of bearing under running up based on angle domain average and Hilbert-Huang transform (HHT) phase map is presented. The non-stationary vibration signals are transformed from the time domain transient signal to angle domain stationary one using order tracking...
Varying speed machinery condition detection and fault diagnosis are more difficult due to non-stationary machine dynamics and vibration. A new approach to fault diagnosis of bearing under running up based on order tracking and Hilbert-Huang transform (HHT) is presented. The non-stationary vibration signals are transformed from the time domain transient signal to angle domain stationary one using order...
A new approach to fault diagnosis of gear wear based on Teager-Huang transform is presented. This method is based on Empirical Mode Decomposition (EMD) and Teager Kaiser Energy Operator (TKEO) technique. 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...
A new approach to fault diagnosis of gear crack based on ensemble empirical mode decomposition (EEMD) and Hilbert-Huang transform (HHT) technique is presented. Firstly, the time-domain vibration signal of the gearbox with gear crack fault is measured. Then the original vibration signal is separated into intrinsic oscillation modes, using the ensemble empirical mode decomposition. Secondly, Hilbert...
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