Turnout fault diagnosis based on DBSCAN/PSO-SOM

作     者：YANG Juhua LI Xutong XING Dongfeng CHEN Guangwu 杨菊花;李旭彤;邢东峰;陈光武

作者机构：School of Traf fic and TransportationLanzhou Jiaotong UniversityLanzhou 730070China Gansu Provincial Key Laboratory of Traffic Information Engineering and ControlLanzhou 730070China Automatic Control Research InstituteLanzhou Jiao tong UhiversityLanzhou 730070China 

出 版 物：《Journal of Measurement Science and Instrumentation》 (测试科学与仪器（英文版）)

年 卷 期：2022年第13卷第3期

页      面：371-378页

核心收录：

学科分类：08[工学] 0814[工学-土木工程] 082301[工学-道路与铁道工程] 0823[工学-交通运输工程] 

基　　金：High Education Research Project Funding(No.2018C-11) Natural Science Fund of Gansu Province(Nos.18JR3RA107,1610RJYA034) Key Research and Development Program of Gansu Province(No.17YF1WA 158) 

主　　题：turnout fault diagnosis density-based spatial clustering of applications with noise(DBSCAN) particle swarm optimization(PSO) self-organizing feature map(SOM) 

摘      要：In order to diagnose the common faults of railway switch control circuit,a fault diagnosis method based on density-based spatial clustering of applications with noise(DBSCAN)and self-organizing feature map(SOM)is ***,the three-phase current curve of the switch machine recorded by the micro-computer monitoring system is dealt with segmentally and then the feature parameters of the three-phase current are calculated according to the action principle of the switch *** to the high dimension of initial features,the DBSCAN algorithm is used to separate the sensitive features of fault diagnosis and construct the diagnostic sensitive feature ***,the particle swarm optimization(PSO)algorithm is used to adjust the weight of SOM network to modify the rules to avoid“dead neurons.Finally,the PSO-SOM network fault classifier is designed to complete the classification and diagnosis of the samples to be *** experimental results show that this method can judge the fault mode of switch control circuit with less training samples,and the accuracy of fault diagnosis is higher than that of traditional SOM network.