基于人工神经网络不锈钢套珩磨加工油石特性参数的智能选择

Intelligent Property Parameters Setting of Fine-grained Oilstone in Honing Stainless Steel Jacket Based on Artificial Neural Network

在综合分析工件材料、材料状态、表面硬度和要求达到的加工表面质量与油石各参数之间关系的基础上,采用改进的GCAQBP人工神经网络算法,通过对输入输出参数进行编码优化,构建了不锈钢材料珩磨加工油石特性参数智能选择模型。通过实验研究,证明了该智能选择模型与传统经验选择相比,具有选择速度快、可靠性高等优点。课题研究为珩磨加工油石特性参数的选择提供了一种新的智能方法。

The article studies the relationship between the status of materials, hardness of its surface, processing quality and the setting of property parameter, and develops an intelligent mode of setting property parameters with improved GCAQBP artificial neural network calculation and coding of input and output. It was improved by series of experiments that the intelligent choosing mode will improve the speed and accuracy comparing with the old ways. The research develops a new way of intelligently setting of property parameter.