Adaptive correlated Kurtogram and its applications in wheelset-bearing system fault diagnosis

Liu, Zechao; Yang, Shaopu; Liu, Yongqiang; Lin, Jianhui; Gu, Xiaohui

doi:10.1016/j.ymssp.2020.107511

Cited by 52 publications

(25 citation statements)

References 33 publications

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“…7 Journal of Sensors In this case, xðtÞ is a complex number whose real and imaginary parts are both nonzero and its squared envelope is calculated by equation (5).…”

Section: Definition Of Autocorrelationmentioning

confidence: 99%

“…In the aspects of the filter optimization design, the related research is aimed at designing a more accurate band-pass filter to suppress the limitations of the FIR filter. Liu et al [5] applied empirical wavelet transform to construct the filter to ensure the same signal length after filtering. The improved redundant second-generation wavelet packet transform proposed by Chen et al, can adaptively match the features of vibration signals to achieve fine separation of fault features and avoid frequency aliasing [6].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Based on the Log-Squared Envelope Harmonic Noise Ratio Fault Transient Feature Extraction Method

Zhu

2022

Journal of Sensors

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To counter the sensitivity of kurtosis for the random pulse, a novel periodic detection index based on the log-squared envelope harmonic noise ratio (LSEHNR) is constructed, and then, a novel LSEHNRgram feature extraction method is proposed by introducing the maximal overlap discrete wavelet packet transform (MODWPT). Firstly, MODWPT is used to decompose the frequency band of the signal and a series of subsignals are obtained from each stage of decomposition, which are called nodes. Secondly, autocorrelation of the log-squared envelope for each node at each level is computed; calculate the LSEHNR, simultaneously. Then, the LSEHNR values of all nodes are calculated and the node with the maximal of the LSEHNR value is selected for spectrum analysis. Finally, the square envelope spectrum (SES) analysis is performed on the in-band filtered signal to extract the transient characteristics of the rolling bearing fault. The experimental results indicate that the LSEHNRgram method can accurately detect the demodulation frequency band and enhance the fault features under the condition of the low noise-to-signal ratio (SNR). The effectiveness of the method is verified on numerical and experimental datasets by comparison with autogram, infogram, and fast kurtgram methods.

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“…7 Journal of Sensors In this case, xðtÞ is a complex number whose real and imaginary parts are both nonzero and its squared envelope is calculated by equation (5).…”

Section: Definition Of Autocorrelationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Based on the Log-Squared Envelope Harmonic Noise Ratio Fault Transient Feature Extraction Method

Zhu

2022

Journal of Sensors

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“…The targeted IFBI method focuses on the (quasi) periodicity of bearing fault features to extract the cyclic components in the signal to be analyzed, requiring knowledge of the impulse period (in the time domain) or the fault characteristic frequency (in the frequency domain) before identifying IFB. For example, the harmonic-to-noise ratio [30] and correlated kurtosis [31,32] using the impulse period have been employed to construct the IFBI methods for extracting periodic bearing fault features. In recent years, the cyclostationarity of bearing fault signals has received increasing attention, and the IFBI methods using fault characteristic frequency have been continuously proposed, such as the ratio of cyclic content [33], indicator of second-order cyclostationarity [34], frequency domain correlated kurtosis [35] and weighted cyclic harmonic-to-noise ratio [36].…”

Section: Introductionmentioning

confidence: 99%

IGIgram: An Improved Gini Index-Based Envelope Analysis for Rolling Bearing Fault Diagnosis

Chen

Dong-li

Cheng

et al. 2022

JDMD

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The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure. Informative frequency band identification is a crucial prerequisite for envelope analysis and thereby accurate fault diagnosis of rolling bearings. In this paper, based on the ratio of quasi-arithmetic means and Gini index, improved Gini indices (IGIs) are proposed to quantify the transient impulse features of a signal, and their effectiveness and advantages in sparse quantification are confirmed by simulation analysis and comparisons with traditional sparsity measures. Furthermore, an IGI-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings. In the new method, an IGI-based indicator is constructed to evaluate the impulsiveness and cyclostationarity of the narrow-band filtered signal simultaneously, and then a frequency band with abundant fault information is adaptively determined for extracting bearing fault features. The performance of the IGIgram method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelope analysis methods and log-cycligram. The results demonstrate that the proposed IGIs are efficient in quantifying bearing fault-induced transient features and the IGIgram method with appropriate power exponent can effectively achieve the diagnostics of different axle-box bearing faults.

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“…Liu et al. [ 13 ] proposed a novel method to find different proper frequency bands of repetitive transients for achieving the wheelset‐bearing systems’ diagnosis. Chen et al.…”

Section: Introductionmentioning

confidence: 99%

Axle Box Resonance Excitation Model Based on Wheelset Polygon and Its Resonance Characteristic Analysis in High‐Speed Train

Cai

Huo

Liao

et al. 2022

Advcd Theory and Sims

Self Cite

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By grasping the vibration characteristics of the wheelset, the service state of the wheel can be reversely deduced. In this paper, the dynamic model of a rigid–flexible coupling vehicle system, considering wheelset flexibility and axle box flexibility, is established, and a novel resonance excitation loading method for axle box is proposed. Through this method, the vertical force of the wheel‐rail and the resonance response of the axle box vibration under different rigid–flexible combinations of wheelset axle box are obtained. The resonance response characteristics of the axle box of the wheelset and the main factors affecting the resonance characteristics are analyzed. Results show that the bending mode of the wheelset considerably affects the vibration characteristics of the axle box. The mass, the moment of inertia around the x‐axis, and the position of the center of gravity of the axle box also greatly affect the resonance characteristics of the wheel‐to‐axle box.

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Adaptive correlated Kurtogram and its applications in wheelset-bearing system fault diagnosis

Cited by 52 publications

References 33 publications

A Novel Based on the Log-Squared Envelope Harmonic Noise Ratio Fault Transient Feature Extraction Method

A Novel Based on the Log-Squared Envelope Harmonic Noise Ratio Fault Transient Feature Extraction Method

IGIgram: An Improved Gini Index-Based Envelope Analysis for Rolling Bearing Fault Diagnosis

Axle Box Resonance Excitation Model Based on Wheelset Polygon and Its Resonance Characteristic Analysis in High‐Speed Train

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