Train Based On Empirical Mode Decomposition Algorithm And Unbalanced Load Detection

Railway is the main way of domestic bulk freight, and its safety is paid more and more national attention, because the unbalance load and bias load of the train brings more and more accidents in recent years.Nowadays, the main methods of train load examining are mostly based on examining the track deformation or installing the weighing track, and the measurement's advantages are relatively little interference to measurement data, and ensuring the accurate result. Besides, it is easily to install and replacement the equipment. But that limits the measuring place and can not achieve the examining in time. The running train's bogie often load dramatically changes comparing with its usual situation, which always brings deviation to the examining system, for the unbalance of rail track. In the paper, it brings a new way to detect the overload and unbalance load, that examining the train's load by installing sensor to bearing springs, and it can examine the situation of the train in time. Then it brings effective way to avoid the vibration in physical and digital form by analysis of vibration of the model, which ensure the accuracy of examining result. At the same time, CAN bus transmission is applied to the object which obtain a fast and accurate data transmission. Also empirical mode decomposition algorithm is applied model of signal analysis, and it improves the way of interpolation about the algorithm, which processing the input curve has a better softness and reduce the analytical error. At the same time it test the simulation model, comparing with other testing methods, and showing the advantages of the improved algorithm.This topic from the State Plan 2008 863 issues of modern transport technologies, it improves the train Unbalanced Load Detection System on the point of real-time and accuracy, and have some meaning to examining danger situation about running train.