NDLI: Incipient machine degradation assessment by MF-MTS system

Content Provider	IEEE Xplore Digital Library
Author	Jinqiu Hu Laibin Zhang Wei Liang
Copyright Year	2012
Description	Author affiliation: College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing, China (Jinqiu Hu; Laibin Zhang; Wei Liang)
Abstract	This paper presents an incipient machine degradation assessment method based on multifractal theory and Mahalanobis-Taguchi system (MTS), which help to differentiate the incipient fault stage and assess the degradation degree as well. According to different machine degradation states, the feature parameters from multifractal aspects are first calculated and further optimized by a MTS statistical method, based on which incipient faults can be subsequently identified and diagnosed accurately. A comparative application study of the effectiveness of the proposed method is carried out through case study of bearings. It is also proved to be a powerful and comprehensive tool for machine's elaborate condition monitoring management which combines a unified representation in both current and predictive perspectives of the fault degradation behavior.
Starting Page	635
Ending Page	640
File Size	1844172
Page Count	6
File Format	PDF
ISBN	9781467307864
e-ISBN	9781467307888
DOI	10.1109/ICQR2MSE.2012.6246313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Degradation Vibrations Fault diagnosis Incipient fault Mahalanobis-Taguchi system Feature extraction Fractals Entropy Signal to noise ratio Degradation assessment Multifractal
Content Type	Text
Resource Type	Article

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