Research On Optimization Method Of Rail Profile Based On Evolution Law Of Rail Profile For Heavy Haul Railway

With the development of railway transportation toward high-speed passenger transportation and heavy-duty freight transportation,wheel-rail force increases and rail wear becomes more prominent.The worsening of rail wear in heavy haul railways will lead to the change of rail profile,reduce the service life of rails,thus increase the cost of railway transportation;if the rail profile changes greatly,it will also affect the safety of driving.Therefore,it is of great significance to study the law of rail profile evolution and explore the corresponding measures to reduce wear and tear,to increase the service life of rail and its components,to ensure driving safety and to increase economic benefits.Based on the evolution law of rail profile of heavy haul railway,the paper proposes that the adjustment of rail contact position can be realized by changing rail parameters,and the optimization of rail profile can be achieved by using wheel-rail natural wear instead of grinding,and the goal of prolonging rail service life can be achieved.In this paper,the following work has been done:The evolution law of rail profile of heavy haul railway under single track parameters and combined track parameters is studied.Based on the theory of Track-Vehicle coupling dynamics,the rail wear prediction model is established and simulated based on Archard wear calculation model and multi-point contact KP algorithm.The selection range of rail parameters in curve section of heavy haul railway is analyzed,and the evolution law of rail profile with different rail parameters is studied.Solve the most matched orbit parameters in each design cycle.By dividing the design period of adjusting track parameters according to the total weight as the standard,taking the minimum metal loss rate of rail as the optimization objective,the non-linear mathematical model of track parameters and metal loss rate in each design cycle is established by using neural network,and the optimal combination of track parameters in each design cycle is solved by using genetic algorithm,so as to achieve the minimum rail wear in the whole design cycle.Compared with the optimal profile proposed by relevant scholars,the two optimized profiles are similar,and the optimized region is close.Compared with the standard profile,the optimized profile formed by adjusting parameters reduces wear by 24.6%,which is higher than the optimized profile formed by grinding method by 17.3%.And the operation mode of the method proposed in this paper does not depend on large grinding equipment and is easy to implement.