Crack shape reconstruction in Eddy current testing using machine learning systems for regression

IEEE Transactions on Instrumentation and Measurement

Volumn 57, Issue 9, 2008, Pages 1958-1968

  Bernieri, Andrea ^a   Ferrigno, Luigi ^a   Laracca, Marco ^a   Molinara, Mario ^a  

^a UNIVERSITY OF CASSINO AND SOUTHERN LAZIO   (Italy)

Author keywords

Artificial neural network (ANN); Eddy current testing (ECT); Nondestructive testing (NDT); Signal processing; Support vector machine (SVM)

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CONDUCTIVE MATERIALS; CRACKS; DEFECTS; EDDY CURRENT TESTING; EDDY CURRENTS; EDUCATION; FOOD PROCESSING; MACHINE DESIGN; MATERIALS TESTING; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; ROBOT LEARNING; SUPPORT VECTOR MACHINES; TESTING;

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK (ANN); CRACK SHAPES; CURRENT PRINCIPLE; DEFECT CHARACTERIZATION; EDDY CURRENT TESTING (ECT); EXPERIMENTAL VALIDATIONS; MACHINE LEARNING SYSTEMS; MACHINE-LEARNING; NON-DESTRUCTIVE TESTING; NONDESTRUCTIVE TESTING (NDT); PERFOR MANCE COMPARISON; SIGNAL PROCESSING; SOLID MATERIALS; SUPPORT VECTOR MACHINE (SVM); SUPPORT-VECTOR MACHINE;

LEARNING SYSTEMS;

EID: 49649085874     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2008.919011     Document Type: Article

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