This paper presents the results from a pilot study of a 'smart system ', used for defect detection in railroad rails. The experimental data used to train the pattern recognition 'smart system', were extracted from experiments conducted during a previous long range ultrasonic guided wave study. Reflection coefficient plots corresponding to a variety of transverse and oblique defects were shown to provide features that were successfully used to train a 'smart System'to identify those defects automatically. This paper presents a brief introduction to support vector machines, followed by a description of the procedure used to determine the best training data to be used to train the 'smart System',, and concluding with lessons learned during this study.
Smart system for long range ultrasonic defect detection of railroad rails
Intelligentes System zum weit reichenden Fehlernachweis von Eisenbahnschienen mit Ultraschall
Structural Materials Technology, 6 ; 186-192
2004
7 Seiten, 5 Bilder, 2 Tabellen, 5 Quellen
Conference paper
Storage medium
English
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