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所属单位：自动化学院
发表刊物：MEASUREMENT
关键字：Rail crack recognition Magnetic Flux Leakage (MFL) Support Vector Machine (SVM) Adaptive weighting Multi-classifier Fusion Decision
摘要：In order to make the full use of three-dimensional information of Magnetic Flux Leakage (MFL) signals, an Adaptive Weighting Mull-classifier Fusion Decision Algorithm is adopted for rail crack recognition. Support Vector Machine (SVM) is used to classify MFL signals from single-channel and single-direction, and then adaptive weightings of different SVMs are assigned according to entropy calculated by posterior probabilities of different SVMs. Finally, weighted majority vote strategy is used to make a comprehensive decision by fusing classification results of different channels and different directions. Effectiveness of the proposed method is testified by experiments based on measured MFL signals.
ISSN号：0263-2241
是否译文：否
发表时间：2018-07-01
合写作者：Chen, Wangcai,李开宇,王平,Zhu, Haixia,F70206529
通讯作者：刘文波