摘要
通过分析实际磨矿过程的生产状况和基本生产数据,建立在磨矿过程中结合比值调节控制前水和给矿量,运用专家 系统对给矿量进行优化控制和基于神经网络质量模型的智能控制方法。实际仿真研究表明,该方法能够提高生产效率,解决磨矿 过程中有一定难度的溢流浓度和分级粒度控制问题。
The intelligent control system with the expert system and the neural network quality model as well as PID feeding adjustment of ore and water is established on the basis of the analysis of the practical production situation and the basic production data in the grinding process for milling shop of Jinchuan Nonferrous Metals Corporation. Practical simulation and research show that the production efficiency of the milling system is increased, and the overflowing concentration and size grading control are satisfied by use of this system.
出处
《有色金属》
CAS
CSCD
2004年第1期86-89,共4页
Nonferrous Metals
关键词
选矿
磨矿
质量模型
神经网络
专家系统
智能控制
mineral processing
grinding process
quality model
neural network
expert system
intelligent control
