Time–frequency manifold sparse reconstruction: A novel method for bearing fault feature extraction

Ding, Xiaoxi; He, Qingbo

doi:10.1016/j.ymssp.2016.04.024

Cited by 66 publications

(20 citation statements)

References 36 publications

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“…Therefore, weak impact feature identification in rolling element bearings is significant to reduce downtime and safety hazards during the running period. Nowadays, a large number of modern approaches have been proposed, such as kurtograms [11,12], improved kurtograms and spectral kurtosis [13][14][15], cyclostationary analysis [16,17], empirical mode decomposition [18], synchronous averaging technology [19,20], sparse models [21,22], stochastic resonance [23], wavelet spectra [24], etc. When the impact characteristics of a signal are relatively weak or submerged in fault-independent interference components, they require further analysis [13].…”

Section: Introductionmentioning

confidence: 99%

Investigation on Planetary Bearing Weak Fault Diagnosis Based on a Fault Model and Improved Wavelet Ridge

Yang

Wang

et al. 2018

Energies

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Abstract:Rolling element bearings are of great importance in planetary gearboxes. Monitoring their operation state is the key to keep the whole machine running normally. It is not enough to just apply traditional fault diagnosis methods to detect the running condition of rotating machinery when weak faults occur. It is because of the complexity of the planetary gearbox structure. In addition, its running state is unstable due to the effects of the wind speed and external disturbances. In this paper, a signal model is established to simulate the vibration data collected by sensors in the event of a failure occurred in the planetary bearings, which is very useful for fault mechanism research. Furthermore, an improved wavelet scalogram method is proposed to identify weak impact features of planetary bearings. The proposed method is based on time-frequency distribution reassignment and synchronous averaging. The synchronous averaging is performed for reassignment of the wavelet scale spectrum to improve its time-frequency resolution. After that, wavelet ridge extraction is carried out to reveal the relationship between this time-frequency distribution and characteristic information, which is helpful to extract characteristic frequencies after the improved wavelet scalogram highlights the impact features of rolling element bearing weak fault detection. The effectiveness of the proposed method for weak fault recognition is validated by using simulation signals and test signals.

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Section: Introductionmentioning

confidence: 99%

Investigation on Planetary Bearing Weak Fault Diagnosis Based on a Fault Model and Improved Wavelet Ridge

Yang

Wang

et al. 2018

Energies

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“…Recently, manifold learning has been successfully applied in fault diagnosis. The manifolds based on different spaces, such as scale space of WT and WPT [46,47], IMF space of EMD [48], and timefrequency space [49], are used to extract impulses. These manifold methods have successfully discovered the intrinsic structures of impulses embedded in the measured vibration signals.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold

Zhuang

Ding

Tan

et al. 2017

Shock and Vibration

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A novel fault detection method employing the impulse-envelope manifold is proposed in this paper which is based on the combination of convolution sparse representation (CSR) and Hilbert transform manifold learning. The impulses with different sparse characteristics are extracted by the CSR with different penalty parameters. The impulse-envelope space is constructed through Hilbert transform on the extracted impulses. The manifold based on impulse-envelope space (impulse-envelope manifold) is executed to learn the low-dimensionality intrinsic envelope of vibration signals for fault detection. The analyzed results based on simulations, experimental tests, and practical applications show that (1) the impulse-envelope manifold with both isometric mapping (Isomap) and locally linear coordination (LLC) can be successfully used to extract the intrinsic envelope of the impulses where local tangent space analysis (LTSA) fails to perform and (2) the impulse-envelope manifold with Isomap outperforms those with LLC in terms of strengthening envelopes and the number of extracted harmonics. The proposed impulse-envelope manifold with Isomap is superior in extracting the intrinsic envelope, strengthening the amplitude of intrinsic envelope spectra, and enlarging the harmonic number of fault-characteristic frequency. The proposed technique is highly suitable for extracting intrinsic envelopes for bearing fault detection.

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“…According to research, over 40% failures are due to bearing defects among failures of motors [1]. Bearing faults may cause unstable vibration of rotor system which leads to serious economic and increase the downtime [2,3]. Therefore, it is essential to understand the dynamic and intrinsic transient characteristics of vibration caused by bearing faults.…”

Section: Introductionmentioning

confidence: 99%

“…According to the recent research, the vibration signals are nonstationary and time-varying with the effect of speed changing and the nonlinear characteristics of the rotor system caused by faults. To well extract the transient characteristics from signal data, many signal denoising methods have been developed [9], such as time-domain method, band-pass filtering, frequency-domain threshold, empirical mode decomposition (EMD), wavelet transform (WT), time-frequency analysis (TFA), manifold learning, and matching pursuit. However, there are still some issues that remained to be studied among these denoising methods.…”

Section: Introductionmentioning

confidence: 99%

“…In these methods, time-frequency analysis can reflect the change of signal characteristics with time and is widely used in faults diagnosis [10]. Ding and He [9] proposed a novel transient signal reconstruction method for bearing fault features extraction and find this method is effective to verify faults characteristics of bearing fault. Liu et al [11] used a novel fault detection method to study the impact time-frequency dictionary and faulty features of roller bearing defects.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Analysis of a Rotor-Bearing-SFD System with the Bearing Inner Race Defect

Zhang

Lin

et al. 2017

Shock and Vibration

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In this paper, the dynamic behavior of a rotor-bearing-SFD system with the inner race defect of bearing is investigated. The contact force between the rolling element and the race is calculated in Hertzian contact and elastohydrodynamic lubrication condition. The supporting force of the SFD is simulated by integrating the pressure distribution derived from Reynolds's equation. The equations of motion of the rotor-bearing-SFD system are derived and solved using the fourth-order Runge-Kutta method. The dynamic behavior and the fault characteristics are analyzed with two configurations of the SFD: (1) mounted on the unfaulted bearing and (2) mounted on the faulty bearing. According to the analysis of time-frequency diagram, waterfall plot, and spectral diagram, the results show that the characteristics of inner race defects on bearing frequencies are related to the characteristic multiple frequency of the inner race defect and the fundamental frequency. The speed and defect width have different influence on the distribution and amplitude of frequency. The SFD can enhance the system stability under the bearing fault but the enhancement decreases with the increasing speed. Meanwhile, the beneficial effect of the SFD varies according to the mounted position in the rotor system.

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Time–frequency manifold sparse reconstruction: A novel method for bearing fault feature extraction

Cited by 66 publications

References 36 publications

Investigation on Planetary Bearing Weak Fault Diagnosis Based on a Fault Model and Improved Wavelet Ridge

Investigation on Planetary Bearing Weak Fault Diagnosis Based on a Fault Model and Improved Wavelet Ridge

Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold

Dynamic Analysis of a Rotor-Bearing-SFD System with the Bearing Inner Race Defect

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