Abstract:Abstract:A ball mill is one of the most often used milling equipments in power plants. The efficiency of ball mill operation is an important aspect to improve economization of the plants. Factors those effect the mill fill level and their relationships are analyzed. Mill fill level grading theory is proposed which classifies the coal amount into three areas: uneconomical area, optimal area and dangerous area. The difficulty to obtain plenty of fill level samples is solved so that the data fusion method can be properly used to measure the fill level. A soft-sensing method of mill fill level based on BP neural network is proposed and is validity by analyzing the data from the operation field. This method gives the optimal operation range for ball mill and forms the basis for the optimum operation and automatic control of the ball mill system.
陈蔚;贾民平;王恒. 基于信息融合的球磨机料位分级与检测研究 [J]. , 2010, 29(6): 142-143.
Chen Wei Jia Minping Wang Heng. A study on the mill fill level grading theory and soft-sensing of mill fill level based on information fusion. , 2010, 29(6): 142-143.