An adaptive and tacholess order analysis method based on enhanced empirical wavelet transform for fault detection of bearings with varying speeds

Hu, Yue; Tu, Xiaotong; Li, Hongguang; Meng, Guang

doi:10.1016/j.jsv.2017.08.003

Cited by 95 publications

(46 citation statements)

References 30 publications

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“…Many functions may satisfy the characteristics of Equation , and the most used function β ( x ) in literature is

β ((), x) = x^{4} ((), 35 - 84 x + 70 x^{2} - 20 x^{3}) \forall x \in ([],, 0, 1) .

…”

Section: Theoretical Background and Developmentmentioning

confidence: 99%

“…Many functions may satisfy the characteristics of Equation 5, and the most used function β(x) in literature [28][29][30][31][32] is…”

Section: The Traditional Ewtmentioning

confidence: 99%

“…To overcome this shortcoming, a novel adaptive filter method named Empirical Wavelet Transform (EWT) was proposed, which can be used to extract the different modes of a vibration response signal by designing an appropriate wavelet filter bank in the Fourier spectrum. EWT has been applied to detect the defects of rolling bearings with good results . Analysis of the noisy and nonstationary signals based on Fourier spectrum would be less effective.…”

Section: Introductionmentioning

confidence: 99%

“…EWT has been applied to detect the defects of rolling bearings with good results. [29][30][31] Analysis of the noisy and nonstationary signals based on Fourier spectrum would be less effective. It will be difficult for EWT to detect the proper boundaries in the Fourier spectrum for extracting the modes, since false modes may be observed leading to an improper segmentation in the frequency domain.…”

mentioning

confidence: 99%

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Operational modal identification of structures based on improved empirical wavelet transform

Hao

2019

Struct Control Health Monit

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Summary This paper proposes an improved Empirical Wavelet Transform (EWT) approach for structural operational modal identification based on measured dynamic responses of structures under ambient vibrations. Two steps are involved in the improved EWT approach. In the first step, the standardized autoregressive power spectrum of the measured response is calculated to define the boundaries of frequency components for the subsequent EWT analysis. The second step is to decompose the measured response into a number of Intrinsic Mode Functions (IMFs) by using EWT. When the Intrinsic Mode Functions are obtained, structural modal information such as natural frequencies, mode shapes, and damping ratios can be identified by using Hilbert transform and Random Decrement Technique. In numerical studies, a simulated signal is used to investigate the effectiveness of the proposed approach. Operational modal identification based on the proposed approach and procedure is conducted to identify the modal parameters of a simulated spatial frame structure under the ambient excitations. The proposed approach is further used for operational modal identification of a seven‐storey shear type steel frame structure in the laboratory and a real footbridge under ambient vibrations to verify the accuracy and performance. The modal identification results from both numerical simulations and experimental validations demonstrate that the proposed approach can effectively and accurately decompose the vibration responses and identify the structural modal parameters under operational conditions.

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“…Many functions may satisfy the characteristics of Equation , and the most used function β ( x ) in literature is

β ((), x) = x^{4} ((), 35 - 84 x + 70 x^{2} - 20 x^{3}) \forall x \in ([],, 0, 1) .

…”

Section: Theoretical Background and Developmentmentioning

confidence: 99%

“…Many functions may satisfy the characteristics of Equation 5, and the most used function β(x) in literature [28][29][30][31][32] is…”

Section: The Traditional Ewtmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Operational modal identification of structures based on improved empirical wavelet transform

Hao

2019

Struct Control Health Monit

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“…Hu et al [40] used the envelope approach based on the order statistics filter to pick useful peaks from the spectrum before segmentation and the method was applied to noisy and non-stationary signals. In another recent study, Hu et al [41] developed an adaptive and tacholess order analysis technique using the enhanced EWT to detect bearing faults in variable speed applications. Pan et al [42] introduced a modified EWT (MEWT) method via data-driven adaptive Fourier spectrum segmentation that is suitable for mechanical fault diagnosis and applied it successfully to bearing fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Feature Extraction Enhancement Based on Parameterless Empirical Wavelet Transform: Application to Bearing Fault Diagnosis

El-Mongy

2018

The International Conference on Applied Mechanics and Mechanica

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Rolling-element bearings are usually subject to faults that need prompt detection in order to prevent sudden failures. Many time-frequency analysis techniques have been used for the purpose of bearing fault detection and diagnosis.From these techniques, wavelets and empirical mode decomposition (EMD) stand out as the most widely applied methods in bearing fault diagnosis. Recently, a novel method named the parameterless empirical wavelet transform (PEWT) has been proposed to combine the wavelet formulation with the adaptability of the empirical mode decomposition. In this paper, the parameterless empirical wavelet transform (PEWT) is combined with envelope detection (ED) to present a new scheme named PEWT-ED for non-stationary signal analysis. The capabilities and limitations of the new method in bearing fault diagnosis are investigated using simulation and experiment. The results show that the new approach can effectively extract the bearing fault characteristics. The PEWT-ED is found to be a powerful tool in signal de-noising and enhancement for fault diagnosis purposes.

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Development and stability analysis of a high‐speed train bearing system under variable speed conditions

Wang

Liu

Zhang

et al. 2022

Int Journal of Mech Sys Dyn

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During a high‐speed train operation, the train speed changes frequently, resulting in motion change as a function of time. A dynamic model of a double‐row tapered roller bearing system of a high‐speed train under variable speed conditions is developed. The model takes into consideration the structural characteristics of one outer ring and two inner rings of the train bearing. The angle iteration method is used to determine the rotation angle of the roller within any time period, solving the difficult problem of determining the location of the roller. The outer ring and inner ring faults are captured by the model, and the model response is obtained under variable speed conditions. Experiments are carried out under two fault conditions to validate the model results. The simulation results are found to be in good agreement with the results of the formula, and the errors between the simulation results and the experimental results when the bearing has outer and inner ring faults are found to be, respectively, 5.97% and 2.59%, which demonstrates the effectiveness of the model. The influence of outer ring and inner ring faults on system stability is analyzed quantitatively using the Lempel–Ziv complexity. The results show that for low train acceleration, the inner ring fault has a more significant effect on the system stability, while for high acceleration, the outer ring fault has a more significant effect. However, when the train acceleration changes, the outer ring has a greater influence. In practice, train acceleration is usually small and does not frequently change in one operation cycle. Therefore, the inner ring fault of the bearing deserves more attention.

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An adaptive and tacholess order analysis method based on enhanced empirical wavelet transform for fault detection of bearings with varying speeds

Cited by 95 publications

References 30 publications

Operational modal identification of structures based on improved empirical wavelet transform

Operational modal identification of structures based on improved empirical wavelet transform

Feature Extraction Enhancement Based on Parameterless Empirical Wavelet Transform: Application to Bearing Fault Diagnosis

Development and stability analysis of a high‐speed train bearing system under variable speed conditions

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