Radio block center(RBC)system is the core equipment of China train control system-3(CTCS-3).Now,the fault analysis of RBC system mainly depends on manual work,and the diagnostic results are inaccurate and inefficient....Radio block center(RBC)system is the core equipment of China train control system-3(CTCS-3).Now,the fault analysis of RBC system mainly depends on manual work,and the diagnostic results are inaccurate and inefficient.Therefore,the intelligent fault diagnosis method of RBC system based on one-hot model,kernel principal component analysis(KPCA)and self-organizing map(SOM)network was proposed.Firstly,the fault document matrix based on one-hot model was constructed by the fault feature lexicon selected manually and fault tracking record table.Secondly,the KPCA method was used to reduce the dimension and noise of the fault document matrix to avoid information redundancy.Finally,the processed data were input into the SOM network to train the KPCA-SOM fault classification model.Compared with back propagation(BP)neural network algorithm and SOM network algorithm,common fault patterns of train control RBC system can be effectively distinguished by KPCA-SOM intelligent diagnosis model,and the accuracy and processing efficiency are further improved.展开更多
随着高铁运营速度达到了350km/h,我国铁路发展进入了新时期。为满足高铁需要,我国铁路部门研发了中国列车运行控制系统(Chinese Train Control System,CTCS)。CTCS-3级列控系统的实时性能指标是列车得以安全高效运行的关键因素,而RBC(Ra...随着高铁运营速度达到了350km/h,我国铁路发展进入了新时期。为满足高铁需要,我国铁路部门研发了中国列车运行控制系统(Chinese Train Control System,CTCS)。CTCS-3级列控系统的实时性能指标是列车得以安全高效运行的关键因素,而RBC(Radio Block Center,无线闭塞中心)是CTCS-3级列控系统的关键设备。RBC通过GSM-R网络与列控车载设备进行双向信息交互,实现对运行列车的控制。本文对LKDR-S型RBC接收列车信息时,超过50秒未收到列车发送的信息这一情况进行了分析。展开更多
基金Natural Science Foundation of Gansu Province(No.1310RJZA061)。
文摘Radio block center(RBC)system is the core equipment of China train control system-3(CTCS-3).Now,the fault analysis of RBC system mainly depends on manual work,and the diagnostic results are inaccurate and inefficient.Therefore,the intelligent fault diagnosis method of RBC system based on one-hot model,kernel principal component analysis(KPCA)and self-organizing map(SOM)network was proposed.Firstly,the fault document matrix based on one-hot model was constructed by the fault feature lexicon selected manually and fault tracking record table.Secondly,the KPCA method was used to reduce the dimension and noise of the fault document matrix to avoid information redundancy.Finally,the processed data were input into the SOM network to train the KPCA-SOM fault classification model.Compared with back propagation(BP)neural network algorithm and SOM network algorithm,common fault patterns of train control RBC system can be effectively distinguished by KPCA-SOM intelligent diagnosis model,and the accuracy and processing efficiency are further improved.
