Defect classification in pipes by neural networks using multiple guided ultrasonic wave features extracted after wavelet processing

Journal of Pressure Vessel Technology, Transactions of the ASME

Volumn 127, Issue 3, 2005, Pages 294-303

  Rizzo, Piervincenzo ^a   Bartoli, Ivan ^a   Marzani, Alessandro ^b   Lanza Di Scalea, Francesco ^a  

^a UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^b UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Feature extraction; Guided waves; Neural networks; Pipe inspection; Wavelet transform

Indexed keywords

DEFECT CLASSIFICATION; PIPE INSPECTION; REFLECTION MEASUREMENT; ULTRASONIC GUIDED WAVES;

CLASSIFICATION (OF INFORMATION); DEFECTS; FEATURE EXTRACTION; FOURIER TRANSFORMS; GUIDED ELECTROMAGNETIC WAVE PROPAGATION; NEURAL NETWORKS; ROBUSTNESS (CONTROL SYSTEMS); ULTRASONIC WAVES; WAVELET TRANSFORMS;

STEEL PIPE;

EID: 24944513857     PISSN: 00949930     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.1990213     Document Type: Article

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