Automatic real-time SVM-based ultrasonic rail flaw detection and classification system
Revised date: 2009-04-13
Online published: 2009-07-15
郝炜 , 李成桐 . 基于SVM的实时自动超声钢轨伤损检测分类系统[J]. 中国科学院大学学报, 2009 , 26(4) : 517 -521 . DOI: 10.7523/j.issn.2095-6134.2009.4.013
This paper describes a more efficient real time SVM(support vector machine)-based ultrasonic rail defect detection and classification system. Feature extraction is achieved based on the attribute of ultrasonic rail defect and then SVM classification prediction algorithm and statistical processing are used to realize classification and calculating the size of the rail defect. This machine learning algorithm is tested in DSP and the type, grade and location of the defects are displayed in real-time.
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