Research on Geometric Parameters Optimization of Fixed Frog Based on Particle Swarm Optimization Algorithm
Source abstract
Abstract
In this paper, to improve the wheel/rail dynamic performance of the vehicle passing through the fixed frog area and improve the service life of the fixed frog, a geometric parameter optimization design method of the fixed frog area is proposed using particle swarm optimization (PSO). Based on the variable section rail profile interpolation algorithm and wheel/rail contact solution algorithm, the wheel/rail contact characteristics of the fixed frog area are analyzed. Then, the vehicle-fixed frog dynamic model is built using a MATLAB/Simulink platform to complete the dynamic calculation and analysis of the rail vehicle passing through the fixed frog area. Finally, based on the wheel/rail contact characteristics of the fixed frog area, and take wheel/rail forces as the optimization goal, the optimization design method for the wing rail lifting value and the nose rail height of the fixed frog area is proposed. The comparative analysis shows that the wheel/rail dynamic performance in the fixed frog area has been greatly improved after optimization, which verifies the feasibility of the optimization strategy.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Railway Engineering and Dynamics · Railway Systems and Energy Efficiency · Transportation Planning and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Rail Transit, Tongji University, Shanghai 201804, China
Funding
Science and Technology Research and Development Plan of China Railway Corporation
References (24)
Show source-provided references
1. Wang, P. (2011). High Speed Railway Turnout Design Theory and Practice, Southwest Jiaotong University Press. [1st ed.].
2. Dynamic and static contact performance analysis of wagon and fixed frog in heavy haul railway
3. Chen, D. (2019). Research on Optimization Design of Rail Grinding Profile in Turnout Switch Area, Tongji University.
4. Vertical dynamic simulation calculation of railway vehicle passing frog
5. Study on vertical interaction between speed increasing train and turnout
6. Spatial coupling vibration model of wheel rail system in turnout area and its application
7. Discussion on the longitudinal distribution law of turnout vertical stiffness along the line
8. Rail vehicle passing through a turnout: Analysis of different turnout designs and wheel profiles10.1177/0954409712445114 ↗
9. Markine, V.L., and Shevitsov, I.Y. (2013, January 3–6). An Experimental study on crossing nose damage of railway turnouts in the Netherlands. Proceedings of the Fourteenth International Conference on Civil, Structural and Environmental Engineering Computing, Stirlingshire, UK.
10. Combatting RCF on switch points by tuning elastic track properties10.1016/j.wear.2010.10.031 ↗
11. Optimisation of support stiffness at railway crossings10.1080/00423114.2017.1404617 ↗
12. Wheel/rail impacts at a railway turnout crossing10.1243/0954409981530733 ↗
13. Anderson, C. (2003). Modelling and Simulation of Train-Track Interaction Including Wear Prediction, Chalmers University of Technology.
14. Study of the dynamic vehicle-track interaction in a railway turnout10.1007/s11044-017-9579-2 ↗
15. Optimisation of railway crossing geometry considering a representative set of wheel profiles10.1080/00423114.2014.998242 ↗
16. Improvement of vehicle-turnout interaction by optimizing the shape of crossing nose10.1080/00423114.2014.944870 ↗
17. Design method for rigid frog based on wheel/rail contact parameters
18. Optimization of nose depth for rigid frog
19. Optimization design method for rigid frog based on wheel/rail profile type
20. Influence of wing rail lifting value on dynamic characteristics of high-speed train crossing the turnout
21. Shen, G. (2014). Railway Vehicle System Dynamics, China Railway Press. [1st ed.].
22. Multi-objective optimization control strategy of traction inverter based on particle swarm algorithm
23. Compilation Group of the Public Works Bureau of the Ministry of Railways (2012). Railway Public Works Technical Manual Turnout, China Railway Press.
24. Wang, W. (2012). Research on Particle Swarm Optimization Algorithm and Its Application, Southwest Jiaotong University.