神经网络多源数据融合磨机料位检测

Mill Material Level Detection of Milling Machine Based on the Neural Network Multi-Source Data Fusion

针对火电厂磨煤机储煤量难与直接精准测量,造成磨机长期处于保守工况运行,制粉系统能耗损失巨大,效率低下的现实问题,,提出了基于神经网络多传感器信息融合的磨机料位智能软测量方法,仿真实验的数据融合结果表明了该方法的可行性和有效性,为进一步开展制粉系统的优化控制奠定了基础.

In view of the difficult to obtain coal storage volume and precision measurement directly, caused mill for power plant works in conservative operation for a long time, coal pulverizing system with huge losses of energy consumption, low efficiency etc. an intelligent soft measurement method based on neural network multi-sensor information fusion is put forward. The simulation experiment of data fusion results show the feasibility and validity of the method, and Lays a further carry out the basis for the control of the optimization of the coal pulverizing system.