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Rolling bearing fault diagnosis based on adaptive smooth ITD and MF-DFA method

Content Provider	SAGE Publishing
Author	Yuan, Zhe Peng, Tingting An, Dong Cristea, Daniel Pop, Mihai Alin
Copyright Year	2019
Abstract	To effectively utilize a feature set to further improve fault diagnosis of a rolling bearing vibration signal, a method based on multi-fractal detrended fluctuation analysis (MF-DFA) and smooth intrinsic time-scale decomposition (SITD) was proposed. The vibration signal was decomposed into several proper rotation components by applying this new SITD method to overcome noise effects, preserve the effective signal, and improve the signal-to-noise ratio. Wavelet analysis was embedded in iteration procedures of intrinsic time-scale decomposition (ITD). For better results, an adaptive threshold function was used for signal recovery from noisy proper rotation components in the wavelet domain. Additionally, MF-DFA was used to reveal the multi-fractality present in the instantaneous amplitude of the proper rotation components. Finally, linear local tangent space alignment was applied for feature dimension reduction and to obtain fault characteristics of different types, further improving identification accuracy. The performance of the proposed method is determined to be superior to that of the ITD-MF-DFA method.
Related Links	https://journals.sagepub.com/doi/pdf/10.1177/1461348419867012?download=true
Starting Page	968
Ending Page	986
Page Count	19
ISSN	14613484
Issue Number	4
Volume Number	39
Journal	Journal of Low Frequency Noise, Vibration and Active Control (LFN)
e-ISSN	20484046
DOI	10.1177/1461348419867012
Language	English
Publisher	Sage Publications UK
Publisher Date	2019-08-01
Publisher Place	London
Access Restriction	Open
Rights Holder	© The Author(s) 2019
Subject Keyword	Smooth intrinsic time-scale decomposition multi-fractal detrended fluctuation analysis linear local tangent space alignment vibration signal bearing fault diagnosis
Content Type	Text
Resource Type	Article
Subject	Building and Construction Acoustics and Ultrasonics Mechanics of Materials Geophysics Mechanical Engineering Civil and Structural Engineering

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