基于DSLPSO的中速磨煤机动态特性研究  

Research on Dynamic Characteristics of Medium Speed Mill Based on DSLPSO

作　　者：陈立志 董云山[1] 司风琪[1] Chen Lizhi;Dong Yunshan;Si Fengqi(Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education,Southeast University, Nanjing 210096, China)

机构地区：[1]东南大学能源热转换及其过程测控教育部重点实验室,南京210096

出　　处：《发电设备》2021年第3期194-200,共7页Power Equipment

摘　　要：以某火电厂MPS型中速磨煤机为研究对象,建立了具有动态特性的中速磨煤机灰箱模型,将动态自学习粒子群寻优(DSLPSO)算法应用于对模型中未知参数的高效辨识,并对模型进行验证。结果表明:建立模型的输出数据能够较好地跟随磨煤机的实际输出数据,采用该模型可以实现磨煤机出口参数的预测及煤粉水分含量的在线监测;通过控制一次风进口的流量和温度能够有效地调节煤粉水分含量和磨煤机出口温度。Taking a MPS-type medium speed mill in a thermal power plant as the research object,a gray box model was established for the medium speed mill with dynamic characteristics,and the dynamic self-learning particle swarm optimization(DSLPSO)algorithm was applied to the efficient identification of unknown parameters of the model,after which,the model was verified.Results show that the output data from the established model can better follow the actual output data of the mill,and through adopting the model,the outlet parameters of the mill can be predicted and the online monitoring can be realized for the water content of the pulverized coal.By controlling the flow rate and temperature of the inlet primary air,the water content of the pulverized coal and the outlet temperature of the mill can be effectively adjusted.

关 键 词：火电厂 中速磨煤机 DSLPSO 灰箱模型 

分 类 号：TK223.72[动力工程及工程热物理—动力机械及工程]