Separation of Impulse from Oscillation for Detection of Bearing Defect in the Vibration Signal

Author(s):  
Anil Kumar ◽  
Ravi Prakash ◽  
Rajesh Kumar
2019 ◽  
Vol 24 (3) ◽  
pp. 467-475
Author(s):  
Mohamed El Morsy ◽  
Gabriela Achtenova

The present article’s intent is to measure and identify the roller bearing inner race defect width and its corresponding characteristic frequency based on filtered time-domain vibration signal. In case localized fault occurs in a bearing, the rolling elements encounter some slippage as the rolling elements enter and leave the bearing load zone. As a consequence, the incidence of the impacts never reproduce exactly at the same position from one cycle to another. Moreover, when the position of the defect is moving with respect to the load distribution zone of the bearing, the series of impulses are modulated in amplitude in time-domain and the conforming Bearing Characteristic Frequencies (BCFs) arise in frequency domain. In order to verify the ability of time-domain in measuring the fault of rolling bearing, an artificial fault is introduced in the vehicle gearbox bearing: an orthogonal placed groove on the inner race with the initial width of 0.6mm approximately. The faulted bearing is a roller bearing quantification of the characteristic features relevant to the inner race bearing defect. It is located on the gearbox input shaft—on the clutch side. To jettison the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter based on an optimal daughter Morlet wavelet function whose parameters are optimized based on maximum Kurtosis (Kurt.). The residual signal is performed for the measurement of defect width. The proposed technique is used to analyse the experimental signal of vehicle gearbox rolling bearing. The experimental test stand is equipped with two dynamometer machines; the input dynamometer serves as an internal combustion engine, the output dynamometer introduces the load on the flange of the output joint shaft. The Kurtosis and Pulse Indicator (PI) are selected as the evaluation parameters of the de-noising effect. The results show the reliability of the proposed approach for identification and quantification of the characteristic features relevant to the inner race bearing defect.


2020 ◽  
Vol 4 (2) ◽  
pp. 115-123
Author(s):  
Berli Paripurna Kamiel

Rolling element bearings often suffer damage due to harsh operating and environmental conditions. The method commonly used in detecting faults in a bearing is envelope analysis. However, this method requires setting the central frequency and the correct bandwidth - which corresponds to the resonance frequency of the bearing - for signal demodulation to be effective. This study proposes a kurtogram to determine the correct central frequency and bandwidth to obtain the frequency band with the highest impulse content or the highest kurtosis value. Analysis envelope is applied to the filtered vibration signal using the central frequency and bandwidth parameters obtained from the kurtogram. The results showed that the envelope-kurtogram method is effective for faulty bearing detection as shown in the envelope spectrum where the peaks coincide with the bearing defect characteristic frequency (BPFO) with high accuracy. Likewise, it can be observed several BPFO harmonics which provide information on the level of bearing fault.


Author(s):  
Anil Kumar ◽  
Rajesh Kumar

Bearing failure is one of the reasons for centrifugal pump breakdown. Existing methods developed for bearing fault diagnosis do not work satisfactorily when the vibration signature of bearing is overlapped by the signature from other defect sources such as an impeller defect. A vibration signal processing scheme making use of ensemble empirical mode decomposition and dual Q-factor wavelet decomposition is proposed to extract information of the bearing defect in a pump. A criterion called as frequency factor is also proposed to find the best decomposition level for the given high and low Q-factor wavelet decomposition parameters. The transient impulses due to bearing defect are effectively extracted separating traces of oscillatory signature of impeller defect and the noise in the signal. The same has been demonstrated using simulation analysis and experimental study. A comparison of the proposed method with existing signal processing methods is also presented.


2009 ◽  
Vol 413-414 ◽  
pp. 575-582
Author(s):  
Ru Qiang Yan ◽  
Robert X. Gao

This paper introduces a quantitative measure based on the energy-to-Shannon entropy ratio for base wavelet selection in vibration signal analysis. The Gaussian-modulated sinusoidal signal and a realistic vibration signal measured from a ball bearing have been used to evaluate the effectiveness of the measure. Experimental results demonstrate that the wavelet selected using the developed measure is effective in diagnosing structural defects in the bearing and the method developed provides systematic guidance in wavelet selection.


2013 ◽  
Vol 765-767 ◽  
pp. 2715-2719 ◽  
Author(s):  
Qing Xiong ◽  
Wei Hua Zhang ◽  
Gui Ming Mei

To deal with the demodulation problem of rolling bearing defect vibration signal in heavy noise, a new method based on time-delayed correlation algorithm and ensemble empirical mode decomposition (EEMD) is presented. Introduced the time-delayed autocorrelation de-noising principle. After the discretization and unbiased estimation of the original signals autocorrelation function , de-noising pretreatment is implemented by appending a rectangle window. Then an envelope signal can be obtained by the first Hilbert transform. After the EEMD decomposition, some interested intrinsic mode functions (IMFs) can be collected. By making the second Hilbert transform of the IMFs, we can get the local Hilbert marginal spectrum from which the defects in a rolling bearing can be identified. By repeated analysis of simulation signals and actual rolling bearings defect vibration signal, the results show that the proposed method is more effective than direct modulation or only time-delayed correlation demodulation or combine time-delayed correlation with EMD demodulation in de-noising and diagnosing the rolling bearing's defect information.


2008 ◽  
Vol 14 (11) ◽  
pp. 1675-1690 ◽  
Author(s):  
X. Chiementin ◽  
F. Bolaers ◽  
O. Cousinard ◽  
L. Rasolofondraibe

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