Urban rail track condition monitoring based on in-service vehicle acceleration measurements

Abstract

Condition monitoring of railway tracks is essential in ensuring the safety of railway systems. Traditional track recording vehicles (TRV) can only carry out the track inspection in the midnight after all the service vehicles are off duty. One track line can be inspected only once or less in a month. The severe track condition degradation cannot be detected timely and there is potential safety hazard for the railway system. Therefore, the track condition monitoring based on in-service vehicle has been paid more attention in the recent years. In this paper, the track condition monitoring based on the bogie and car body acceleration measurements is presented. The track alignment information which can be derived from the bogie and car body sensor is investigated by using a mathematical model and the frequency response analysis. The track irregularities can be estimated by using the bogie and the car body acceleration sensors. The acceleration signals are preprocessing with a DC filter and a low pass filter. After that, the track alignments are obtained by double integrating the signals. Field tests are carried out in Shang Hai metro Line 1 for demonstrating the effectiveness of the proposed track inspection system.