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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...
The order bi-cepstrum technique is introduced and applied effectively to gearbox faults diagnosis under run-up condition. This new method combines order tracking technique with bi-cepstrum analysis. The resampling signal can be obtained by resampling of the vibration signal that has been sampled in the time domain. Therefore, the time domain transient signal is changed into angle domain stationary...
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...
This paper deals with the detection of gear crack faults in gearbox under non-stationary run-up of gear drives. In order to process the non-stationary vibration signals such as run-up or run-down vibration signals effectively, the order bi-spectrum technique is presented. This new method combines computed order tracking technique with bi-spectrum analysis. Firstly, the vibration signal is sampled...
A study is presented to apply order cepstrum and radial basis function (RBF) artificial neural network (ANN) for gear fault detection during speed-up process. This method combines computed order tracking, cepstrum analysis with ANN. Firstly, the vibration signal during speed-up process of the gearbox is sampled at constant time increments and then is resampled at constant angle increments. Secondly,...
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