A study of diagnostic signatures of a deep groove ball bearing based on a nonlinear dynamic model

Rehab, Ibrahim; Tian, Xinshou; Gu, Fengshou; Ball, Andrew

doi:10.1109/iconac.2015.7313944

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…A series of models was developed to simulate the vibration responses of bearings with localised defects. [38][39][40][41][42] The fault-related vibration responses from a rolling element bearing are induced by the periodic impulses when the rolling elements pass the localised fault. The system resonance modulates the periodic impulses, generating modulation vibration signals.…”

Section: Simulation Of Bearing Signalsmentioning

confidence: 99%

A phase linearisation–based modulation signal bispectrum for analysing cyclostationary bearing signals

et al. 2020

Structural Health Monitoring

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Bearings are used as the most important load-carrying transmission components in various machines, thus subjecting to a number of faults including wear, fatigue pitting, cracks and so on. Fault detection and diagnosis of bearings can effectively prevent the machine from such typical failures and subsequent consequences. The faults in bearings can lead to the vibration signals that exhibit cyclostationary characteristics due to the inevitably random phase noise (or slippage between bearing components). In this article, a phase linearisation–based modulation signal bispectrum is proposed to tune up the cyclostationary bearing signal into a periodic waveform by linearizing the instantaneous phase of the narrow frequency band signals. In this way, the signal becomes more deterministic and modulation signal bispectrum can be effectively applied to suppression noise and obtain accurate and robust diagnosis results. As a result, this fault detector can achieve high performance in characterising the nonstationary bearing vibration signals and hence diagnose the bearing faults even in the case of extremely low signal-to-noise ratio (<−20 dB), which is benchmarked by the method of conventional modulation signal bispectrum in both simulation and experiment studies.

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Section: Simulation Of Bearing Signalsmentioning

confidence: 99%

A phase linearisation–based modulation signal bispectrum for analysing cyclostationary bearing signals

et al. 2020

Structural Health Monitoring

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“…To evaluate the performance of the MSB detector, both no-slippage and slippage signals were produced using a linearised bearing model derived from the nonlinear model presented in [23], and this was validated with different bearing fault cases and different internal clearances. Table 1 and denoted A through F; collectively these allowed a range of representative detection circumstances to be assessed.…”

Section: Simulation Studymentioning

confidence: 99%

A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram

Tian

Rehab

et al. 2018

Mechanical Systems and Signal Processing

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Envelope analysis is a widely used method for rolling element bearing fault detection. To obtain high detection accuracy, it is critical to determine an optimal frequency narrowband for the envelope demodulation. However, many of the schemes which are used for the narrowband selection, such as the Kurtogram, can produce poor detection results because they are sensitive to random noise and aperiodic impulses which normally occur in practical applications. To achieve the purposes of denoising and frequency band optimisation, this paper proposes a novel modulation signal bispectrum (MSB) based robust detector for bearing fault detection. Because of its inherent noise suppression capability, the MSB allows effective suppression of both stationary random noise and discrete aperiodic noise. The high magnitude features that result from the use of the MSB also enhance the modulation effects of a bearing fault and can be used to provide optimal frequency bands for fault detection. The Kurtogram is generally accepted as a powerful means of selecting the most appropriate frequency band for envelope analysis, and as such it has been used as the benchmark comparator for performance evaluation in this paper. Both simulated and experimental data analysis results show that the proposed method produces more accurate and robust detection 2 results than Kurtogram based approaches for common bearing faults under a range of representative scenarios.

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Autocorrelated Envelopes for early fault detection of rolling bearings

Zhen

et al. 2021

Mechanical Systems and Signal Processing

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A study of diagnostic signatures of a deep groove ball bearing based on a nonlinear dynamic model

Cited by 5 publications

References 12 publications

A phase linearisation–based modulation signal bispectrum for analysing cyclostationary bearing signals

A phase linearisation–based modulation signal bispectrum for analysing cyclostationary bearing signals

A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram

Autocorrelated Envelopes for early fault detection of rolling bearings

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