Prediction of progressive damage state at the hot spots using statistical estimation

Journal of Intelligent Material Systems and Structures

Volumn 21, Issue 6, 2010, Pages 595-605

  Banerjee, Sourav ^a   Qing, Xinlin P ^a   Beard, Shawn ^a   Chang, Fu Kuo ^b  

^a Acellent Technologies Inc   (United States)

^b 496 Lomita Mall   (United States)

Author keywords

Damage estimation; Gaussian mixture model; Hot spot monitoring; Local joint monitoring; Structural health monitoring

Indexed keywords

APRIORI; CALIBRATION PROCEDURE; CURRENT DATA; DAMAGE ESTIMATION; DAMAGE EXTENT; DAMAGE GROWTH; DATA SETS; DISCRETE TIME; FATIGUE CRACK GROWTH; GAUSSIAN MIXTURE MODEL; HOT SPOT; MAHALANOBIS DISTANCES; MODELING TECHNIQUE; OUTPUT PARAMETERS; PATTERN RECOGNITION AND CLASSIFICATION; POWER CONSUMPTION; PROGRESSIVE DAMAGE; REAL TIME; SIGNAL FEATURES; STATISTICAL APPROACH; STATISTICAL ESTIMATION; STEP ANALYSIS; WAVE SIGNAL;

ALARM SYSTEMS; ALGORITHMS; CRACKS; ELECTRIC POWER SUPPLIES TO APPARATUS; ESTIMATION; FATIGUE CRACK PROPAGATION; FORECASTING; GAUSSIAN DISTRIBUTION; MOBILE TELECOMMUNICATION SYSTEMS; MONITORING; PATTERN RECOGNITION; STRUCTURAL HEALTH MONITORING; STRUCTURES (BUILT OBJECTS); WELDS;

DAMAGE DETECTION;

EID: 77953174847     PISSN: 1045389X     EISSN: 15308138     Source Type: Journal    
DOI: 10.1177/1045389X10361632     Document Type: Article

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