Study on fault diagnosis and prognosis methods based on hidden semi-Markov model

Binggong Xuebao/Acta Armamentarii

Volumn 30, Issue 1, 2009, Pages 69-75

  Hu, Hai Feng ^a   An, Mao Chun ^b   Qin, Guo Jun ^a   Hu, Niao Qing ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^b Pre research Projects Management Center of General Armament Department   (China)

Author keywords

Artificial intelligence; Efficient recursive algorithm; Fault diagnosis; Fault prognosis; Hidden semi Markov model

Indexed keywords

ARTIFICIAL INTELLIGENCE; HIDDEN MARKOV MODELS; MOTION ESTIMATION; RECURSIVE FUNCTIONS;

COMPUTATION COMPLEXITY; EFFICIENT RECURSIVE ALGORITHM; EXPONENTIAL DISTRIBUTIONS; FAULT DIAGNOSIS; FAULT PROGNOSIS; GAAS; HELICOPTER GEARBOXES; HIDDEN SEMI-MARKOV MODEL; HIDDEN STATE; PATTERN CLASSIFICATIONS; REMAINING USEFUL LIFE PREDICTIONS; TIME DURATIONS; UNIFIED FRAMEWORKS;

DIAGNOSIS;

EID: 61949171720     PISSN: 10001093     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

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