Detection and characterization of buried macroscopic cracks inside dielectric materials by microwave techniques and artificial neural networks

IEEE Transactions on Instrumentation and Measurement

Volumn 57, Issue 12, 2008, Pages 2819-2826

  Maazi, M ^a   Benzaim, O ^a   Glay, D ^a   Lasri, T ^a  

^a UNIV LILLE   (France)

Author keywords

Artificial neural network (ANN); Cracks; Microwave; Millimeter wave; Nondestructive characterization

Indexed keywords

BACKPROPAGATION; CRACKS; ELECTROMAGNETIC WAVES; KNOWLEDGE ENGINEERING; MICROWAVES; NEURAL NETWORKS; REFLECTION; SIGNAL PROCESSING; VEGETATION;

ARTIFICIAL NEURAL NETWORK (ANN); ARTIFICIAL NEURAL NETWORKS; CHARACTERIZATION METHODS; CRACK PROFILES; FATIGUE CRACKS; GEOMETRICAL CONFIGURATIONS; KEY FACTORS; MACROSCOPIC CRACKS; MICROWAVE METHODS; MICROWAVE TECHNIQUES; NEAR FIELDS; NONCONTACT TECHNIQUES; NONDESTRUCTIVE; NONDESTRUCTIVE CHARACTERIZATION; PERCEPTRON; PRACTICAL ISSUES; REFLECTION COEFFICIENTS; SIX PORTS;

DIELECTRIC MATERIALS;

EID: 57049119081     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2008.926396     Document Type: Article

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