模糊C均值聚类算法在高炉料面分类中的应用

通过对多雷达扫描得到的高炉料面进行数据处理,根据数据的特征,分别采用模糊C均值聚类和特征加权模糊C均值聚类算法对料面数据进行分类,建立标准料面模型库.再通过模糊模式识别中贴近度的方法把待分类的目标料面与模型库相匹配,为后续的布料控制提供依据.该算法在某2500 m³高炉上进行了实验,取得良好的效果.仿真结果表明了其有效性.

Application of the fuzzy C-means clustering algorithm in blast furnace burden surface identification

Blast furnace burden surface data derived from multi radars were processed. Fuzzy C-means and feature weighted fuzzy C-means clustering were applied to identify the burden surface data according to the data information, and a standard burden surface model database was set up. Each target burden surface was matched with the model database by using the method of nearness in fuzzy pattern recognition, and this provides a basis for the next burden surface control. The algorithm was carried out into a 2 500 m3 blast furnace, and the control effect has been improved. The simulation results show the effectiveness of the proposed method.