Statistical pattern recognition for Structural Health Monitoring using time series modeling: Theory and experimental verifications

Mechanical Systems and Signal Processing

Volumn 23, Issue 7, 2009, Pages 2192-2204

  Gul, Mustafa ^a   Necati Catbas, F ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Damage detection; Dynamics; Outlier detection; Statistical pattern recognition; Structural Health Monitoring; Time series modeling

Indexed keywords

AMBIENT VIBRATIONS; AUTO REGRESSIVE MODELS; DAMAGE CONDITION; DAMAGE-SENSITIVE FEATURES; EXOGENOUS INPUT; EXPERIMENTAL VERIFICATION; LABORATORY CONDITIONS; MAHALANOBIS DISTANCES; OUTLIER ANALYSIS; OUTLIER DETECTION; OUTLIER DETECTION ALGORITHM; RESEARCH GROUPS; SIMPLY SUPPORTED; STATISTICAL PATTERN RECOGNITION; STEEL BEAMS; STEEL GRIDS; STRUCTURAL CHANGE; TEST SPECIMENS; TEST STRUCTURE; TIME SERIES MODELING;

DAMAGE DETECTION; DYNAMICS; HEALTH; PATTERN RECOGNITION; STEEL; STRUCTURES (BUILT OBJECTS); TESTING; TIME SERIES; TIME SERIES ANALYSIS;

STRUCTURAL HEALTH MONITORING;

EID: 67349128320     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2009.02.013     Document Type: Article

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