Fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis and Mahalanobis distance criterion

Mechanical Systems and Signal Processing

Volumn 38, Issue 2, 2013, Pages 515-533

  Lin, Jinshan ^a,b   Chen, Qian ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b WEIFANG UNIVERSITY   (China)

Author keywords

Fault diagnosis; Mahalanobis distance; Multifractal detrended fluctuation analysis (MF DFA); Rolling bearing

Indexed keywords

CHARACTERISTIC PARAMETER; DYNAMICAL CHARACTERISTICS; EMPIRICAL MODE DECOMPOSITION; GENERALIZED HURST EXPONENT; MAHALANOBIS DISTANCES; MULTIFRACTAL DETRENDED FLUCTUATION ANALYSIS; NON-STATIONARY TIME SERIES; ROLLING BEARINGS;

BEARINGS (MACHINE PARTS); FAILURE ANALYSIS; FEATURE EXTRACTION; ROLLER BEARINGS; SIGNAL PROCESSING; SPECTRUM ANALYSIS; STATISTICAL METHODS; TIME DOMAIN ANALYSIS; TIME SERIES;

FRACTALS;

EID: 84878285626     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2012.12.014     Document Type: Article

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