中国机械工程2012，Vol.23Issue(9)：1070-1074,5.
基于改进自适应模糊推理系统的YG3硬质合金精密外圆磨削表面质量预测
Surface Quality Prediction in Precision Cylindrical Grinding of YG3 Cemented Carbide Based on Improved ANFIS
摘要
Abstract
For improving the surface integrity and processing quality in the precision cylindrical grinding of cemented carbides,and investigating the prediction technique of the surface quality,a prediction model of the surface roughness in the precision cylindrical grinding of YG3 cemented carbide based on the adaptive network-based fuzzy inference system（ANFIS） was proposed.Then,it was improved by the hybrid Taguchi genetic algorithm（HTGA）.At last,the grinding parameters and corresponding surface roughness in the experiments was used as the training and testing samples.Trough the comparative analysis of the prediction results in the BP neural network model,traditional ANFIS model and improved ANFIS model,the effectiveness and prediction accuracy of three models were verified.The results show that the prediction accuracy of the improved ANFIS model was better than that of an other two in the distribution of the relative error Er and the size of mean square error EMSRE,and it is an effective prediction method of the surface quality.关键词
硬质合金/表面质量预测/自适应模糊推理系统/混合田口遗传算法Key words
cemented carbide/surface quality prediction/adaptive network-based fuzzy inference system(ANFIS)/hybrid Taguchi genetic algorithm(HTGA)分类
矿业与冶金引用本文复制引用
刘茂福..基于改进自适应模糊推理系统的YG3硬质合金精密外圆磨削表面质量预测[J].中国机械工程,2012,23(9):1070-1074,5.
