摘要
磨削过程中的声发射信号和砂轮状态及磨削状态有着很强的关联性,为了更好的实现磨削过程的智能监控,通过构建贝叶斯网络来分离及辨识声发射信号,搭建了贝叶斯网络的声发射磨削智能监控系统,并进行了磨削实验。结果表明:构建的贝叶斯网络可以有效的实现磨削过程中工件粗糙度预测、砂轮钝化和接触识别。
There is strong relationship between the acoustic emission and the states of the wheel and grinding. The Bayesian networks were used to separate and identify the acoustic emission signal for the better intelligent monito- ring of grinding. The grinder intelligent monitoring system based on Bayesian networks was established and grinding experiments were performed. The results show that thesyatem can predict the surface roughness of grinding work- pieces, blunt level and the contact states of grinding wheel.
出处
《机械科学与技术》
CSCD
北大核心
2012年第7期1166-1169,共4页
Mechanical Science and Technology for Aerospace Engineering
关键词
磨削监控
声发射
贝叶斯网络
acoustic emission
grinder intelligent monitoring
bayesian networks
