基于神经网络的汽车板簧自组织配置设计方法

A Method of Self-Organizing Configuration Design of Vehicle Leaf-Spring Based on Neural Network

针对产品配置设计的效率以及配置过程的智能性等问题,以汽车板簧为对象,提出一种基于神经网络(NN)的产品自组织配置设计方法。在规划从客户需求到设计结果的自组织配置设计过程的基础上,结合汽车板簧自组织配置设计的过程和特点,分别采用BP和RBF网络构建汽车板簧结构特征与参数配置的神经网络模型;并运用一定数量的实例样本在Matlab7.1中对所建立的结构和参数配置模型进行了训练与仿真,以验证所提出方法的有效性。

Considering the problems in product configuration design such as configuration efficiency, intelligence of configuration process and so on, a method of self-organizing product configuration designing is presented for vehicle leaf spring based on Neural Network. On the basis of the lay out and description of the whole design from customer requirement to design result, combined with the characteristics of vehicle leaf-spring design, BP and RBF network models are constructed respectively for structure and parameter configuration. Furthermore, the built models are trained and simulated with samples in Matlab7.1 to testify the effectiveness of the method.