A physically segmented hidden markov model approach for continuous tool condition monitoring: Diagnostics and prognostics

IEEE Transactions on Industrial Informatics

Volumn 8, Issue 4, 2012, Pages 964-973

  Geramifard, Omid ^a   Xu, Jian Xin ^a   Zhou, Jun Hong ^b   Li, Xiang ^b  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b SINGAPORE INSTITUTE OF MANUFACTURING TECHNOLOGY   (Singapore)

Author keywords

Diagnostics; feature selection; hidden Markov model (HMM); prognostics; tool condition monitoring (TCM)

Indexed keywords

COMPUTER NUMERICAL CONTROL; CROSS VALIDATION; DIAGNOSTICS AND PROGNOSTICS; ELMAN NETWORK; EXPERIMENTAL STUDIES; HIDDEN STATE; HYPER-PARAMETER; MACHINERY SYSTEMS; MARKOV MODEL; MULTI LAYER PERCEPTRON; PROBABILISTIC APPROACHES; PROGNOSIS ABILITY; PROGNOSTICS; TOOL CONDITION MONITORING; TOOL WEAR;

COMPUTER CONTROL SYSTEMS; FEATURE EXTRACTION; MACHINE TOOLS; PARAMETER ESTIMATION; PLASMA DIAGNOSTICS; SYSTEMS ENGINEERING;

HIDDEN MARKOV MODELS;

EID: 84867928825     PISSN: 15513203     EISSN: None     Source Type: Journal    
DOI: 10.1109/TII.2012.2205583     Document Type: Article

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