Research On Load Identification Of Longitudinal Stop On Well-Hole Freight Train

This project is a study on the load identification of the longitudinal stop on well-hole car.Based on the analysis of the development of load identification technology at home and abroad and the development of load identification technology in railway transportation,this paper studies the load identification technology of the stop on well-hole car.In this paper,using modeling software and finite element analysis software,such as ABAQUS,a load inversion model of the longitudinal is established.Based on the model,the screws load of two trapezoidal can be identified according to the strain measured at any time in the real vehicle test.Railway freight transport has been an important role in delivering long and big freight cargos like transformers.Safety evaluation of key support components remains a challenge for freight trains because of the difficulties in direct and precise monitoring.In this work,the longitudinal stop on well-hole freight train,which prevents the cargo from sliding in anterior-posterior direction,is investigated.Load identification approach is proposed via strain perception at multiple locations,which are selected from the optimal positions sensitive to longitudinal and lateral loading in finite element analysis(FEA).Validation undergoes in random loading simulation.The identified loads deviate from the randomly sets within 4.07%.Longitudinal and lateral forces are recognized in attempt to calculate the signed von Mises stress of the longitudinal stop structure for fatigue evaluation.In application,vehicle test reveals that the maximum longitudinal force is up to 162.2 k N,when the train runs from 36.8km/h to 3.6 km/h within 31 seconds.The maximum lateral force hits 41.6 k N when the train runs on 300-m radius line curve at the speed of 10 km/h.The reconstructed structural stress climbs up to to 107.1 MPa for the right weld base.Employing the rain-flow counting and Miner’s damage rule,the recommendation for load spectra grade in convergence is 64 groups.The equivalent fatigue damage is 0.854 and it maximally drops to 30% in the statistical annual maximum mileage equivalency.Research outcome reveals that the proposed method enables the real-time monitoring of service loads and structural stress in railway freight transport,which provides scientific evidence for its maintenance planning and structural optimization.