摘要
A new fault diagnosis method is proposed to effectively extract the fault features of the sound signal of typical faults of ZDJ9 railway point machines.A multi-entropy feature extraction method is proposed by combing multi-scale permutation entropy and wavelet packet entropy.Firstly,empirical mode decomposition is performed on sound signals to obtain modal components with different time scales.Then,multi-scale permutation entropy is extracted from these components.Meanwhile,the wavelet packet entropy of the sound signals of these sensitive nodes is obtained by analysing the reconstructed signals of the last layer nodes.Since the multi-scale permutation entropy and the wavelet packet entropy can distinguish the subtle features of the signal,the subtle features of the information among the high-dimensional features,ReliefF is utilized.Finally,a support vector machine(SVM)is used to judge the original sismal can be obtained as the feature vector of the 2DJ9 iway point mnchine in ditterent states,To reduce the redundant fault type of a ZDJ9 rilway point machine.
基金
supported by the Natural Science Foundation Guide Project of Liaoning Province(Grant No.2021-Ms-298)
Scientific Research Project Department of Education in Liaoning Pr ovince(Grant No.JDL2020006)
Liaoning Provincial Department of Education Higher Education Innovative Talent Support Program in 2020,National Natural Science Foundation of China(Grants No.U1934219,52202392 and 52022010)
Talent Fund of Beijing Jiaotong University(Grant No.2021RC276).
作者简介
Corresponding author:Shaohua Chen,E-mail:dl_chenshaohua@163.com。
