基于模块化神经网络的汽车轮胎接触面压力模型  

Pressure Model of Contact Interface Between Vehicle Tires and Highway Pavement Based on Modular Neural Network

作　　者：王树威[1] 陈艳艳[1] 薄迎春[2] 

机构地区：[1]北京工业大学交通工程北京市重点实验室,北京100124 [2]北京工业大学电子信息与控制工程学院,北京100124

出　　处：《北京工业大学学报》2013年第2期245-250,共6页Journal of Beijing University of Technology

基　　金：十一五"国家科技支撑计划资助项目(2009BAG13A02);北京市交通委资助项目"(KY2009-19)

摘　　要：针对汽车轮胎与路面接触面压力测量问题,提出了一种基于模块化神经网络的轴载、胎压与接触面压力的关系模型.该模型首先将样本进行模糊聚类,针对不同的轴载、胎压信息,构造基于距离测度的隶属函数,通过模糊判别实现该信息子网络的在线选择,提高神经网络对信息处理的自适应性.对合肥市某公路的轴载检测样本的测试结果表明,基于模块化神经网络的接触面压力模型在精度上优于经验模型,环境适应性也有一定程度提高.In order to solve the problem of measurement between vehicle tires and highway pavement, this paper built a mathematical model among axle load, tire pressure and contact interface pressure based on modular neural network （MNN）. With the different axle load and tire pressure, the membership function based on distance measurement is constructed firstly, and on that basis, a fuzzy cluster method to sample data is adopted to realize on-line sub-nets selection to improve the self-adapting ability of MNN. The experiment on the sample data of Hefei city＇s highway demonstrates that this model is superior to others in accuracy and adaptability.

关 键 词：接触面压力 轴载 胎压 模块化神经网络 

分 类 号：U417[交通运输工程—道路与铁道工程]