Prognosis of bearing failures using hidden markov models and the adaptive neuro-fuzzy inference system

IEEE Transactions on Industrial Electronics

Volumn 61, Issue 6, 2014, Pages 2864-2874

  Soualhi, Abdenour ^a,b   Razik, Hubert ^a,b   Clerc, Guy ^a,b   Doan, Dinh Dong ^c  

^a UNIVERSITÉ DE LYON   (France)

^b Univ Claude Bernard Lyon1   (France)

^c FEMTO ST INSTITUTE   (France)

Author keywords

Artificial intelligence; feature extraction; fuzzy neural networks; hidden Markov models (HMMs); pattern recognition; prognosis; time domain analysis; vibration analysis

Indexed keywords

ARTIFICIAL INTELLIGENCE; FEATURE EXTRACTION; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; PATTERN RECOGNITION; ROLLER BEARINGS; TIME DOMAIN ANALYSIS; TRACKING (POSITION); VIBRATION ANALYSIS;

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; HIDDEN MARKOV MODELS (HMMS); PROGNOSIS; PROGNOSTICS AND HEALTH MANAGEMENTS; RELIABILITY AND SAFETIES; TIME DOMAIN FEATURES; TIME SERIES PREDICTION; UNSUPERVISED CLASSIFICATION;

HIDDEN MARKOV MODELS;

EID: 84891769069     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2013.2274415     Document Type: Article

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