Peak-Based Mode Decomposition for Weak Fault Feature Enhancement and Detection of Rolling Element Bearing
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-09
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Rolling element bearings are widely used in rotating machinery to support shafts, whose failures may affect the health of the whole system.
However, strong noise interferences often make the bearing fault features submerged and difficult to be identified.
Peak-based wavelet method is such a way to reduce certain noise and enhance the fault features by increasing the sparsity of monitored signals.
But peak-based wavelet parameters need to be optimized due to the determined basis function and constant resolution, which will affect the efficiency of vibration signal analysis.
To address these problems, a peak-based mode decomposition is proposed for weak bearing fault feature enhancement and detection.
Firstly, to enhance the differences between repetitive transients and high-frequency noise, a peak-based piecewise recombination is used to convert the middle frequency parts into low-frequency ones.
Then, the recombined signal is processed by empirical mode decomposition, combining with a criterion of cross-correlation coefficients and kurtosis.
Subsequently, a backward peak transformation is performed to obtain the enhanced signal.
Finally, the fault diagnosis is implemented by the squared envelope spectrum, whose normalized squared magnitude is used as a bearing fault indicator.
The analysis results of the simulated signals and the experimental signals show that the proposed method can enhance and identify the weak repetitive transient features.
The superiority of the proposed method for faint repetitive transient detection is also verified by comparing with the peak-based wavelet method.
American Psychological Association (APA)
Xu, Zhi& Tang, Gang& He, Mengfu. 2020. Peak-Based Mode Decomposition for Weak Fault Feature Enhancement and Detection of Rolling Element Bearing. Shock and Vibration،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1213651
Modern Language Association (MLA)
Xu, Zhi…[et al.]. Peak-Based Mode Decomposition for Weak Fault Feature Enhancement and Detection of Rolling Element Bearing. Shock and Vibration No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1213651
American Medical Association (AMA)
Xu, Zhi& Tang, Gang& He, Mengfu. Peak-Based Mode Decomposition for Weak Fault Feature Enhancement and Detection of Rolling Element Bearing. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1213651
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1213651