Canonical variate analysis, probability approach and support vector regression for fault identification and failure time prediction

Journal of Intelligent and Fuzzy Systems

Volumn 34, Issue 6, 2018, Pages 3771-3783

  Li, Xiaochuan ^a   Duan, Fang ^b   Bennett, Ian ^c   Mba, David ^a  

^a DE MONTFORT UNIVERSITY   (United Kingdom)

^b LONDON SOUTH BANK UNIVERSITY   (United Kingdom)

^c SHELL GLOBAL SOLUTIONS INTERNATIONAL B V   (United States)

Author keywords

canonical variate analysis; Condition monitoring; cox proportional hazard model; support vector regression

Indexed keywords

COMPRESSIBILITY OF GASES; CONDITION MONITORING; DEGRADATION; FAILURE (MECHANICAL); FAILURE ANALYSIS; FAULT DETECTION; GAS INDUSTRY; HAZARDS; MAINTENANCE; REGRESSION ANALYSIS; SENSORY ANALYSIS; VECTORS;

CANONICAL VARIATE ANALYSIS; COX PROPORTIONAL HAZARD MODEL; DIAGNOSIS AND PROGNOSIS; FAILURE TIME PREDICTION; FAULT IDENTIFICATIONS; MAINTENANCE IMPROVEMENTS; REMAINING USEFUL LIVES; SUPPORT VECTOR REGRESSION (SVR);

RECIPROCATING COMPRESSORS;

EID: 85049400265     PISSN: 10641246     EISSN: 18758967     Source Type: Journal    
DOI: 10.3233/JIFS-169550     Document Type: Conference Paper

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