Ultrasonic signal recognition with multi-feature SVM-Bayes fusion method
Hongkun Che, Xiang Zhan-qin · Zhendong yu chongji · 2011
Problems in ultrasonic signal recognition were analyzed.A new fusion recognition method base on multi-features extraction was studied,it was combined with support vector machine(SVM) theory and Bayes reasoning.The principles of SVM method and Bayes reasoning were introduced.The fusion recognition method based on maximum a posteriori(MAP) was designed to identify signals of different defects with features extracted in different ways.Four feature extraction methods were presented for fusion recognition.Experiments with both SVM method and SVM-Bayes one were carried out to identify defect signals of oil casing pipe.The result showed that defects can be identified effectively with SVM-Bayes method,and its recognition rate and generality are better than those of a single feature SVM method.