Prognosis of defect propagation based on recurrent neural networks

IEEE Transactions on Instrumentation and Measurement

Volumn 60, Issue 3, 2011, Pages 703-711

  Malhi, Arnaz ^a   Yan, Ruqiang ^b   Gao, Robert X ^c  

^a MEDTRONIC INC   (United States)

^b SOUTHEAST UNIVERSITY   (China)

^c UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

Competitive learning; continuous wavelet transform (CWT); long term prediction

Indexed keywords

BEARING DEFECT; COMPETITIVE LEARNING; CONTINUOUS WAVELET TRANSFORMS; DEFECT PROPAGATION; INCREMENTAL TRAINING; INPUT DATAS; LONG-TERM PREDICTION; MACHINE HEALTH; PRE-PROCESSED DATA; ROLLING BEARINGS; STATISTICAL PARAMETERS; TIME STEP; TRAINING TECHNIQUES; VIBRATION SIGNAL;

BEARINGS (MACHINE PARTS); BEARINGS (STRUCTURAL); DEFECTS; FORECASTING; WAVELET TRANSFORMS;

RECURRENT NEURAL NETWORKS;

EID: 79951660524     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2010.2078296     Document Type: Article

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