摘要
在以球磨机为主要生产设备的工业过程中,球磨机负荷是与生产效率和能源消耗密切相关的重要指标。针对难以采用常规方法控制球磨机负荷的难题,将多传感器数据融合和案例推理方法相结合,提出了氧化铝生料浆配料过程的球磨机负荷优化控制方法。利用球磨机的振动和电流信号,采用多传感器数据融合方法在线估计出球磨机的负荷状态,在此基础上,采用案例推理方法自动调整进入球磨机的干料总量,从而使球磨机在"最佳负荷状态"下运行。将所提出的优化控制方法进行工业实验,结果表明,球磨机的台时产能得到了较大提高,同时降低了能源消耗并减少了"堵磨"故障次数,取得了良好的经济效益。所提出的方法为化工、冶金和电力等其他行业的球磨机负荷控制提供了重要的参考价值。
Ball mill is used widely in various productions, such as chemical industry, metallurgical industry and power industry. Ball mill is high energy consumption equipment, whose load is the key index that affects the production efficiency and energy consumption. In the blending process of sintering alumina production, raw materials are fed into the ball mill and blended to form the raw slurry. In order to make ball mill work at the optimal load state, a control strategy of the ball mill load in the blending process was proposed with data fusion and case-based reasoning. Current and vibration were used to estimate the state of ball mill load with data fusion technology, and ball mill load was controlled to achieve the optimal state with case-based reasoning. Industrial experiment in an alumina factory showed the validity of the proposed control strategy.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2009年第7期1746-1752,共7页
CIESC Journal
基金
国家重点基础研究发展计划项目(2002CB312201)
国家自然科学基金项目(60674056)
辽宁省教育厅重点实验室项目(2009S054)~~
