摘要
通过对Si3N4、Al2O3和ZrO2三种工程陶瓷材料进行磨削加工试验,获得磨削力的实验数据。利用人工神经网络和遗传算法建立工程陶瓷磨削力数学模型。在相同的加工条件下参照试验数据对这两种模型进行分析,得出人工神经网络建立的数学模型相对误差小些。
By doing experiments on Si3N4 ceramic material, Al2O3 ceramic material, and ZrO2 ceramic material, this paper obtains experimental data of grinding force. Utilizing self- study characteristic of artificial neural networks and genetic algorithm, it builds up the forecasting models of grinding force. On base of the same processing conditions and experimental data, it analyses the two models. The result shows that the errors by the model of artificial neural networks is less than the other one.
出处
《天津职业院校联合学报》
2008年第5期10-15,共6页
Journal of Tianjin Vocational Institutes
关键词
工程陶瓷
磨削力
遗传算法
人工神经网络
engineeringceramic
grinding force
genetic algorithms
artificial neural networks
