The Simulation Analysis of the Signals Collection Model for Railway Locomotive Remote Communication
Xin Hui Wu · Applied Mechanics and Materials · 2014
The locomotive frequency shift signals carry important operation information. In order to achieve reliable detection of the locomotive signals, this paper analyzes the signal characteristics of the locomotive and proposes a railway remote communication signals collection model. The model uses the data mining methods to extract the locomotive frequency shift signals by analyzing the locomotive frequency shift with signal classification technology. The separated signals can obtain the low frequency signals with low-pass filtering and shaping. The algorithm is simulated by MATLAB software. The results illustrate the proposed method can effectively separate and collect the shifted frequency signals with some application value.