Use of a genetic algorithm to improve the rail profile on Stockholm underground
Use of a genetic algorithm to improve the rail profile on Stockholm underground
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DOI：
10.1080/00423111003668245
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发表时间：
2010-11
影响因子：
3.6
通讯作者：
I. Persson;R. Nilsson;Ulf Bik;M. Lundgren;S. Iwnicki
中科院分区：
文献类型：
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作者：
I. Persson;R. Nilsson;Ulf Bik;M. Lundgren;S. Iwnicki
在本文中，遗传算法优化方法已被用于为地下斯德哥尔摩开发改进的轨道轮廓。基于多个关键性能参数的倒罚指数被生成，作为健身函数，并使用多体模拟包装套件进行了车辆动力学模拟。使用轮盘旋轮法评估了由遗传算法产生的每个轮廓的有效性。该方法已应用于斯德哥尔摩地下的铁路剖面，在那里，车轮和轨道上的滚动接触疲劳问题目前是通过研磨来管理的。从原始BV50的起点和UIC60轨道剖面的起点，已经产生了一些具有一些肩部浮雕的轨道轮廓。优化的配置文件似乎类似于斯德哥尔摩地下网络上的轨道剖面，尽管需要初步磨削，但对轮廓的维护可能不需要进一步的磨削。
In this paper, a genetic algorithm optimisation method has been used to develop an improved rail profile for Stockholm underground. An inverted penalty index based on a number of key performance parameters was generated as a fitness function and vehicle dynamics simulations were carried out with the multibody simulation package Gensys. The effectiveness of each profile produced by the genetic algorithm was assessed using the roulette wheel method. The method has been applied to the rail profile on the Stockholm underground, where problems with rolling contact fatigue on wheels and rails are currently managed by grinding. From a starting point of the original BV50 and the UIC60 rail profiles, an optimised rail profile with some shoulder relief has been produced. The optimised profile seems similar to measured rail profiles on the Stockholm underground network and although initial grinding is required, maintenance of the profile will probably not require further grinding.