Quantitative and Localization Diagnosis of a Defective Ball Bearing Based on Vertical–Horizontal Synchronization Signal Analysis

Cui, Lingli; Zhang, Feibin

doi:10.1109/tie.2017.2698359

Cited by 195 publications

(103 citation statements)

References 24 publications

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“…Zhu et al [109] cross-fuzzy entropy 8 Zair et al [110] fuzzy entropy of empirical mode decomposition + principal component analysis + self-organizing map neural network 9 Deng et al [111] integrating empirical wavelet transform + fuzzy entropy 10 Zhu et al [112] adaptive local iterative filtering + modified fuzzy entropy + support vector machine 11 Liu et al [113] composite interpolation-based multiscale fuzzy entropy+ Laplacian support vector machine 12 Zheng et al [114] sigmoid-based refined composite multiscale fuzzy entropy 13 Zhu et al [115] multiscale fuzzy entropy + Laplacian support vector machine…”

Section: Application Of Fuzzy Entropy On Bearingmentioning

confidence: 99%

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Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Liu

Zhi

Zhang

et al. 2019

Entropy

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Rotating machinery plays an important role in various kinds of industrial engineering. How to assess their conditions is a key problem for operating safety and condition-based maintenance. The potential anomaly, fault and failure information can be obtained by analyzing the collected condition monitoring data of the previously deployed sensors in rotating machinery. Among the available methods of analyzing sensors data, entropy and its variants can provide quantitative information contained in these sensing data. For implementing fault detection, diagnosis, and prognostics, this information can be utilized for feature extraction and selecting appropriate training data for machine learning methods. This article aims to review the related entropy theories which have been applied for condition monitoring of rotating machinery. This review consists of typical entropy theories presentation, application, summary, and discussion.

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Section: Application Of Fuzzy Entropy On Bearingmentioning

confidence: 99%

“…If the condition monitoring data are not enough, the accelerated degradation model can be utilized [10,11]. The localization diagnosis of the defectiveness is also worth studying [12]. Many methods have been proposed to achieve accurate and stable results of condition monitoring.…”

Section: Introductionmentioning

confidence: 99%

Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Liu

Zhi

Zhang

et al. 2019

Entropy

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“…When a rolling element bearing fails, the rolling body will impact periodically when it touches the fault position [53][54][55][56]. Antoni and Randall [57] indicated that the vibration induced by a single fault in the rolling element bearing can be simulated as follows:…”

Section: Model Of the Collected Vibrationmentioning

confidence: 99%

Fault Feature Extraction and Enhancement of Rolling Element Bearings Based on Maximum Correlated Kurtosis Deconvolution and Improved Empirical Wavelet Transform

Ming

Zhang

et al. 2019

Applied Sciences

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In order to extract and enhance the weak fault feature of rolling element bearings in strong noise conditions, the Empirical Wavelet Transform (EWT) is improved and a novel fault feature extraction and enhancement method is proposed by combining the Maximum Correlated Kurtosis Deconvolution (MCKD) and improved EWT method. At first, the MCKD method is conducted to de-noise the signal by eliminating the non-impact components. Then, the Fourier spectrum is segmented by local maxima or minima in the envelope of the amplitude spectrum with a pre-set threshold based on the noise level. By building up the wavelet filter banks based on the spectrum segmentation result, the signal is adaptively decomposed into several sub-signals. Finally, by choosing the most meaningful sub-signal with the maximum kurtosis, the fault feature can be extracted in the squared envelope spectrum and teager energy operator spectrum of the chosen component. Both simulations and experiments are performed to validate the effectiveness of the proposed method. It is shown that the spectrum segmentation result of improved EWT is more reasonable than the traditional EWT in strong noise conditions. Furthermore, compared with commonly used methods, such as the Fast Kurtogram (FK) and the Optimal Wavelet Packet Transform (OWPT) method, the proposed method is more effective in the fault feature extraction and enhancement of rolling element bearings.

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“…Gearbox is one of the most important components in mechanical industry and daily life. With constant development of modern industrial technology, fault monitoring of gearbox is more and more valued in research field [1][2][3][4][5][6][7][8][9][10]. As the key component of gearbox, the study of gear fault diagnosis method [11][12][13][14] is of great significance.…”

Section: Introductionmentioning

confidence: 99%

Improvement on Meshing Stiffness Algorithms of Gear with Peeling

et al. 2019

Self Cite

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This paper investigates the effect of a gear tooth peeling on meshing stiffness of involute gears. The tooth of the gear wheel is symmetric about the axis, and its symmetry will change after the gear spalling, and its meshing stiffness will also change during the meshing process. On this basis, an analytical model was developed, and based on the energy method a meshing stiffness algorithm for the complete meshing process of single gear teeth with peeling gears was proposed. According to the influence of the change of meshing point relative to the peeling position on the meshing stiffness, this algorithm calculates its stiffness separately. The influence of the peeling sizes on mesh stiffness is studied by simulation analysis. As a very important parameter, the study of gear mesh stiffness is of great significance to the monitoring of working conditions and the prevention of sudden failure of the gear box system.

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Quantitative and Localization Diagnosis of a Defective Ball Bearing Based on Vertical–Horizontal Synchronization Signal Analysis

Cited by 195 publications

References 24 publications

Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Fault Feature Extraction and Enhancement of Rolling Element Bearings Based on Maximum Correlated Kurtosis Deconvolution and Improved Empirical Wavelet Transform

Improvement on Meshing Stiffness Algorithms of Gear with Peeling

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