摘要
提出运用神经网络的非线性建模原理和自学习能力 ,建立影响磨削参数选择的各种因素与磨削参数之间的函数映射关系。据此可以实现初始磨削用量智能化选择目的。将磨削过程智能监测模块检测到的砂轮状态特征信号反馈到神经网络的输入端 ,根据砂轮钝化程度实现磨削参数的在线智能调整 ,以减少砂轮钝化对磨削质量的影响 。
In this paper, it is proposed to utilize the nonlinear modeling theory and self-learning capability of neural network to setup mapping relations between the grinding conditions and their affecting factors, and between AE signals and grinding wheel states. Based on these,intelligent selection of starting parameters for grinding process can be realized. On-line intelligent adjustment of grinding conditions also can be realized based on dull degree of grinding wheel through feeding back the characteristic signals of grinding wheel states given by intelligent monitoring module into input extremity of this neural network.So that the influence of grinding wheel dull on grinding quality is reduced, and stability of processing quality is ensured.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2003年第15期1268-1271,共4页
China Mechanical Engineering
基金
教育部科学技术研究重点资助项目 ( 2 0 0 0 3 2)
关键词
磨削
加工参数
神经网络
在线调整
智能化方法
grinding processing parameter neural network on-line adjustment intelligent method
