A study of two unsupervised data driven statistical methodologies for detecting and classifying damages in structural health monitoring

Mechanical Systems and Signal Processing

Volumn 41, Issue 1-2, 2013, Pages 467-484

  Tibaduiza, D A ^a   Torres Arredondo, M A ^b   Mujica, L E ^a   Rodellar, J ^a   Fritzen, C P ^b  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^b UNIVERSITY OF SIEGEN   (Germany)

Author keywords

Active ultrasonic guided wave testing; Discrete wavelet transform; Principal component analysis; Self organizing maps; Structural health monitoring

Indexed keywords

CARBON FIBER REINFORCED PLASTICS (CFRP); MECHANICAL STRUCTURES; MULTIWAY PRINCIPAL COMPONENT ANALYSIS; PIEZOELECTRIC ACTIVE SENSORS; PRINCIPAL COMPONENT MODELS; SQUARED PREDICTION ERRORS; STATISTICAL METHODOLOGIES; WAVELET COEFFICIENTS;

CARBON FIBER REINFORCED PLASTICS; CONFORMAL MAPPING; DISCRETE WAVELET TRANSFORMS; DYNAMIC RESPONSE; FUSELAGES; PRINCIPAL COMPONENT ANALYSIS; SELF ORGANIZING MAPS; SENSOR NETWORKS; STRUCTURAL DYNAMICS; STRUCTURAL HEALTH MONITORING; ULTRASONIC APPLICATIONS;

DAMAGE DETECTION;

EID: 84885616556     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2013.05.020     Document Type: Article

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