Variational mode decomposition based symmetric single valued neutrosophic cross entropy measure for the identification of bearing defects in a centrifugal pump

Kumar, Anil; Gandhi, C.P.; Zhou, Yuqing; Kumar, Rajesh; Xiang, Jiawei

doi:10.1016/j.apacoust.2020.107294

Cited by 63 publications

(26 citation statements)

References 43 publications

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“…To cope with this issue, a multiscale approach is proposed that shortens the time series at higher scales, which results in higher fluctuations of entropy values at scale factors [20]. Permutation entropy can also be applied in the analysis of vibration signals [21]. However, entropy methods tend to exclude high-frequency information, yielding limited diagnostic performance in identifying bearing health states [22].…”

Section: Introductionmentioning

confidence: 99%

Short-Time/-Angle Spectral Analysis for Vibration Monitoring of Bearing Failures under Variable Speed

et al. 2021

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Vibration-condition monitoring aims to detect bearing damages of rotating machinery’s incipient failures mainly through time–frequency methods because of their efficient analysis of nonstationary signals. However, by having failures with impulse behavior, short-term events have a tendency to be diluted under variable-speed conditions, while information on frequency changes tends to be lost. Here, we introduce an approach to highlighting bearing impulsive failures by measuring short-term spectral components to deal with variable-speed vibrations. The short-term estimator employs two sliding windows: a small one that measures the instantaneous amplitude level and tracks impulsive components and a large interval that evaluates the average background amplitude. Aiming to characterize cyclo-non-stationary processes with impulsive behavior, the emphasizing high-order-based estimator based on the principle of spectral entropy is introduced. For evaluation, both visual inspection and classifier performance are assessed, contrasting the spectral-entropy estimator with the widely used spectral-kurtosis approach for dealing with impulsive signals. The validation of short-time/-angle spectral analysis performed on three datasets at variable speed showed that the proposed spectral-entropy estimator is a promising indicator for emphasizing bearing failures with impulse behavior.

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Section: Introductionmentioning

confidence: 99%

Short-Time/-Angle Spectral Analysis for Vibration Monitoring of Bearing Failures under Variable Speed

et al. 2021

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“…Yu et al [13] took the time-varying effect caused by the distributed and localized faults into consideration and found that the faults not only influenced the system on the dynamic behaviors but also on the geometric topographies. It is generally accepted that the surface defects affect the interactions between bearing components by changing the contact forces, and the defect frequencies are obtained through the relative motions between rings and balls [14][15][16]. However, for full-ceramic ball bearings, the fit clearance between the outer ring and the pedestal changes greatly in wide temperature ranges.…”

Section: Introductionmentioning

confidence: 99%

Raceway Defect Frequency Deviation of Full‐Ceramic Ball Bearing Induced by Fit Clearance in Wide Temperature Ranges

Bai

Zheng

Wang

et al. 2021

Shock and Vibration

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Full-ceramic ball bearings are widely applied in wide temperature ranges due to their excellent thermal shock resistance, and the condition monitoring and fault diagnosis are mainly conducted through the spectrum analysis based on the defect frequencies. However, the outer ring has a spinning motion in the temperature-related fit clearance, which leads to the deviation of raceway defect frequencies, and is not conducive to the fault diagnosis. In this paper, the temperature-related fit clearance is considered in the dynamic model, and defects are added on the inner raceway and outer raceway. The motions of the rings are calculated and analyzed in the frequency domain, and the trends of peak frequencies with temperature are investigated. Simulation and experimental results show that the spinning speed of the outer ring increases with temperature, and the defect frequencies exhibit obvious deviation in wide temperature ranges. In a temperature range of 500 K, the defect frequencies exhibit deviations of over 3%, which is obvious in the defect frequency identification. The results provide insights on the full-ceramic ball bearing dynamics and help with the fault diagnosis and status monitoring of the relevant devices.

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“…Although the above-mentioned methods have already achieved gratifying results in the application, if used improperly, there are also some negative impacts such as the pre-added Gauss white noise can't be eliminated entirely, which will affect the decomposition accuracy. Besides, as an improvement of EMD, some variational mode decomposition (VMD) based strategies are also widely applied in fault diagnosis of rotating machinery [22]- [24]. Meanwhile, many researchers believe that a major and fundamental reason of mode mixing in conventional EMD is the over and undershoot problem caused by the cubic spline-curve [25], [26], so they still continue to optimize and improve the sifting process of EMD.…”

Section: Introductionmentioning

confidence: 99%

An Improved Empirical Mode Decomposition Based on Adaptive Weighted Rational Quartic Spline for Rolling Bearing Fault Diagnosis

Shen

et al. 2020

IEEE Access

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As a powerful time-frequency signal analysis technique, empirical mode decomposition (EMD) has been commonly applied in fault diagnosis. However, the cubic spline-curve often causes outstanding over and undershoot problem, which significantly limits the performance of conventional EMD. To address this problem, an improved EMD (I-EMD) based on adaptive weighted rational quartic spline is proposed. Firstly, the original cubic spline interpolation in conventional EMD is replaced with the weighted rational quartic spline interpolation (WRQSI) which has two adjustable shape control parameters. Secondly, a novel parameter selection criterion termed envelope characteristic frequency ratio (ECFR) is designed to guide the construction of the optimal local envelope. And simulation analysis proved that ECFR is not only sensitive to the characteristic information but also robust to the weak noise and sudden impulses. Subsequently, the optimal shape control parameter can be searched by grasshopper optimization algorithm (GOA) using the maximum ECFR as the objective function. Then the sensitive modes selected via weighted Kurtosis index are employed for further Hilbert envelope spectrum analysis. Finally, two case studies on rolling bearing fault diagnosis are constructed to verify the rationality and effectiveness of the I-EMD method. The results show that I-EMD method can evidently solve the over and undershoot problem and restrain the mode mixing phenomenon. Moreover, I-EMD also performs better fault feature extraction ability under the same conditions compared with EMD, VMD and CEEMDAN. So it is expected that I-EMD will serve as a potential improvement for signal processing, fault feature extraction and fault diagnosis.

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Variational mode decomposition based symmetric single valued neutrosophic cross entropy measure for the identification of bearing defects in a centrifugal pump

Cited by 63 publications

References 43 publications

Short-Time/-Angle Spectral Analysis for Vibration Monitoring of Bearing Failures under Variable Speed

Short-Time/-Angle Spectral Analysis for Vibration Monitoring of Bearing Failures under Variable Speed

Raceway Defect Frequency Deviation of Full‐Ceramic Ball Bearing Induced by Fit Clearance in Wide Temperature Ranges

An Improved Empirical Mode Decomposition Based on Adaptive Weighted Rational Quartic Spline for Rolling Bearing Fault Diagnosis

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