An unsupervised pattern recognition approach for AE data originating from fatigue tests on polymer-composite materials

Mechanical Systems and Signal Processing

Volumn 64-65, Issue , 2015, Pages 465-478

  Doan, D D ^a   Ramasso, E ^a   Placet, V ^a   Zhang, S ^a   Boubakar, L ^a   Zerhouni, N ^a  

^a FEMTO ST INSTITUTE   (France)

Author keywords

Acoustic emission clustering; Fatigue datasets; Noise reduction; Organic matrix composites; Sequential feature selection

Indexed keywords

ACOUSTIC NOISE; CARBON FIBER REINFORCED PLASTICS; CLASSIFICATION (OF INFORMATION); COMPOSITE MATERIALS; DATA HANDLING; FATIGUE DAMAGE; FATIGUE TESTING; FEATURE EXTRACTION; FIBER REINFORCED PLASTICS; NOISE ABATEMENT; PATTERN RECOGNITION;

AUTOMATIC SEPARATIONS; DAVIES-BOULDIN INDEX; DIMENSIONALITY REDUCTION; MAHALANOBIS DISTANCES; ORGANIC MATRIX COMPOSITES; POLYMER COMPOSITE MATERIALS; SEQUENTIAL FEATURE SELECTIONS; UNSUPERVISED PATTERNS;

ACOUSTIC EMISSION TESTING;

EID: 84937978179     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2015.04.011     Document Type: Article

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