On middle and low speed maglev track irregularity detection based on threshold filtering algorithm

Maglev train is a new urban transportation tool. Track is considered as a component of maglev transportation system and it would directly affect the safety of train operation. An algorithm based on triple threshold filtering is put forward to conduct detection of maglev track, which can be used to filter abnormal points to judge the vertical suspected irregularity of track. In the scheme, the threshold settings for gap difference, current change rate and acceleration differences on suspended controller are set according to characteristics of low sampling rate, high data repeatability and large data volume of automobile data recorder, it can extract information of track irregularity. In order to improve the reliability of the algorithm, 20 sets of data from 5 independent bogies of two trains are clustered for analysis, and get the suspected area of vertical irregularity. The data of maglev train of Changsha operating railway was tested finally.