节点文献
机车牵引特性综合测试系统的研究
Study on Locomotive Traction Characteristic Test System
【作者】 张俊燕；
【导师】 郭世明；
【作者基本信息】 西南交通大学 ， 电工理论与新技术， 2008， 硕士
【摘要】 机车牵引特性测试是在新建线路投入运营、客运列车提速、货运列车增加牵引吨位、司乘制度改革及机车交路变化等情况下所进行的一项基础性技术工作,为铁路部门经营决策、指定运输方案、挖潜增效提供科学依据。它的核心是能够实时计算得到机车运行过程中的牵引力和制动力。针对传统的牵引特性测试方法得到的牵引力与制动力误差较大的不足,提出了采用人工神经网络实时计算机车运行过程中牵引力与制动力的方法。本文分析探讨了现有测试方法的不足,同时,通过人工神经网络技术的原理和特性的研究,以及其非线性逼近能力的分析,论证了神经网络技术应用于机车牵引特性测试上的可行性。本文采用了误差反向传播网络(BP网络)建立了牵引力与制动力的计算模型,详细阐述了该网络的结构设计,讨论了BP网络隐含层节点数目的选择、数据的预处理等问题;并针对BP算法易陷入局部极小、收敛速度慢等不足,提出了改进措施。最后,采用由成都铁路局提供的实验数据在MATLAB6.5环境下进行了仿真,实验结果表明,采用B P网络计算机车的牵引力和制动力,计算结果精度更高。
【Abstract】 Under the circumstances of putting new railway lines into use or improving passenger train speed or increasing freight train tonnage or reforming driving system, locomotive tractive characteristic test has become a foundational technical job. It provides scientific data for railway administration to make management decision and transportations plan, to dig potential and increase profit. The real time calculation of tractive force and braking force is the core of the system. Aiming at the disadvantages of traditional calculations of locomotive tractive and braking force,the method of Artificial Neural Network model is proposed. The structure design of the neural network iselaborated.The paper finds out the disadvantages of traditional method. At the meantime,by researching theory and characteristic of the Artificial Neural Network and analyzing its nonlinear approaching capacity,the writer probes into the feasibility of the application of Artificial Neural Network applying to the locomotive tractive characteristic test.A calculation of tractive force and braking force model using Error Back-Propagation Training neural network(BP netwok) is proposed. The structure design of the neural network iselaborated.the problems such as choice about the node number of hidden layer,data pretreatment ,and so on are dicussed;in allusion to the shortages of BP arithmetic such as easy to fall into local smallness and slow constringency speed,the paper brought forward the amelioratin measures.In the end, the simulation is carried out with Matlab 6.5 using the data provided by Chengdu Railway Bureau and these results are presented. It was shown that the accuracy of the result is increased.