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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...
A novel method for detection and diagnosis the bearing inner and outer race fault according to bi-spectrum analysis technique is presented. The bi-spectrum analysis is widely recognized as an effective technique for machinery fault diagnosis using vibration signals since it can be used to eliminate the effect of strong noise. This advantage makes it very suitable for extracting useful features from...
The damaged gearbox is often related to non-linear effects that may lead to non-linearity in the machine vibration signal. This paper introduces the application of modern signal processing technique based on higher order spectrum to the fault detection and diagnosis of gearbox. The bi-spectrum can effectively eliminate the effect of random noise and extract useful features from the noisy mechanical...
Rolling element bearings vibrations are random cyclostationary signals which are a combination of periodic and random processes due to the machine's rotation cycle and interaction with the real world. The combinations of such components are best considered as cyclostationary. This paper discusses which second order cyclostationary statistics should be used for fault diagnosis of bearing. The second...
A new demodulation approach to fault diagnosis of bearing based on Teager energy operator (TEO) technique is presented. Firstly, TEO can tracks the modulation energy of the vibration signal and estimates the instantaneous amplitude. Secondly, the envelope spectrum is applied to the instantaneous amplitude. Therefore, the character of the bearing faults can be recognized according to the envelope spectrum...
In order to overcome the shortcomings of the traditional envelope analysis in which manually specifying a resonant frequency band is required, a novel approach based on the ensemble empirical mode decomposition (EEMD) and envelope spectrum is proposed for detecting Localized defects in rolling bearings. This approach can extract the characteristic frequencies related to the defect from the resonant...
The bi-cepstrum technique is presented based on bi-spectrum and cepstrum analysis. This new method combines bi-spectrum technique with cepstrum analysis. Firstly, in order to eliminate the noise effects, the bi-spectrum is calculated. Then the bi-spectrum is processed by bi-cepstrum technique. The experimental results show that bi-cepstrum technique can effectively diagnosis the faults of the gear.
A signal analysis technique for bearing fault detection based on empirical mode decomposition (EMD) and Teager Kaiser energy operator (TKEO) is presented. EMD can adaptively decompose vibration signal into a series of zero mean amplitude modulation-frequency modulation (AM-FM) intrinsic mode functions (IMFs). TKEO tracks the modulation energy of the interesting Intrinsic Mode Functions (IMFs) and...
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