Track profile estimation using inverse analysis from multibody simulation approach
The condition monitoring of the track irregularity is extremely significant for the safe passage of railway vehicle.Poor maintenance of track geometry can effect in unwanted vehicle dynamic responses leading to poor ride quality,distorted flange contact and deterioration during climb.For maintenance purpose,Track Recording Vehicle(TRV)is utilized,which is expensive and cannot be frequently used.Thus,it is very beneficial to be able to use the in-service train vehicle to monitor the condition of the track daily.However,the potential applicability of such measurement for track profile estimation is not clarified yet.Multi-Body Simulation(MBS)approach by SIMPACK is expected to investigate the influence from different factors under various scenarios on simulated track excitations.In this paper,a fundamental study to identify track profile from acceleration and angular velocity measurements on train car body and bogie mass by means of MBS is being carried out.These vehicle measurement responses are utilized to estimate the vertical and lateral track profile using the 6 DOF train model for the proposed estimation algorithm,based on an extended Augmented State Kalman filter(ASKF),which is frequently utilized to determine an unknown input signal(track geometry)from a known output signal(in-service vehicle measurements),is validated for different train running scenarios.It shows a good agreement with true waveform for vertical track profile while it can estimate only above 7 m wavelength irregularity for lateral track profile.Hence,this study proposes the effective track profile estimation techniques from car-body and bogie mass motions using MBS approach.
track geometry Multi-Body Simulation Augmented State Kalman Filter train model statistical metrics
T.Jothi Saravanan Di Su Hirofumi Tanaka Tomonori Nagayama
Bridge and Structure Laboratory,Department of Civil Engineering,The University of Tokyo,Japan Track Technology Division,Railway Technical Research Institute,Japan
国际会议
The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)
青岛
英文
1305-1315
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）