Affiliation of Author(s):自动化学院
Journal:MEASUREMENT
Key Words:Rail crack recognition Magnetic Flux Leakage (MFL) Support Vector Machine (SVM) Adaptive weighting Multi-classifier Fusion Decision
Abstract: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 No.:0263-2241
Translation or Not:no
Date of Publication:2018-07-01
Co-author:Chen, Wangcai,lky,Wang Ping,Zhu, Haixia,F70206529
Correspondence Author:lwb
Date of Publication:2018-07-01