基于深度学习的浮选加药控制系统

赵楼煤矿选煤中心根据浮选泡沫的特点将深度学习技术融入到浮选加药系统的研发之中,设计了基于卷积神经网络的识别与分类网络,提高了系统的泡沫识别准确率及抗干扰能力。通过将西门子PLC、WinCC、高清摄像机与智能算法的深度接合,使浮选加药控制系统实现了"人工智能"。

Flotation Dosing Control System Based on Deep Learning

According to the characteristics of flotation foam,the coal preparation center of Zhaolou Coal Mine integrates deep learning technology into the research and development of flotation dosing system.The identification and classification network based on convolution neural network is designed,which improves the foam recognition accuracy and anti-interference ability of the system.Through the deep engagement of Siemens PLC,WinCC,HD camera and intelligent algorithm,the flotation dosing control system is realized"artificial intelligence".