基于关联维数的鼓泡流化床风帽压力波动特性研究  

Characteristic Study on Pressure Fluctuation of Wind Caps in a Bubbling Fluidized-bed Based on Correlation Dimension

作　　者：高建强[1] 唐树芳[1] 姜华伟[1] 刘宪岭[1] 陈鸿伟[1] 

机构地区：[1]华北电力大学能源动力与机械工程学院,保定071003

出　　处：《动力工程学报》2012年第4期268-272,共5页Journal of Chinese Society of Power Engineering

基　　金：教育部高等学校博士学科点专项科研基金资助项目(20090036110008);华北电力大学"211工程"三期面上项目(94021001)

摘　　要：通过采集鼓泡流化床风帽入口的压力信号,利用小波方法对信号进行消噪处理后,对流化床风帽入口压力信号的时间序列进行了相空间重构,利用G-P算法计算了重构相空间的关联维数,并对冷态实验台采集的风帽压力数据进行了分析处理.结果表明:鼓泡流化床风帽压力波动信号具有混沌特性;自相关函数为0.1时,对应的延迟时间较为合适;典型冷态试验工况下,当表观气速增大时,关联维数呈上升趋势;当静床高增大时,关联维数随之减小.Pressure data of wind caps in a cold-state bubbling fluidized-bed test rig were analyzed by means of collecting pressure signals at entrance of the wind caps,performing pressure signal denoising with the help of wavelet method,reconstructing phase space of relevant time series data and calculating correlation dimension of the reconstructed phase space using G-P algorithm.Results show that the pressure fluctuation signals of wind caps in bubbling fluidized bed have chaos characteristics.The time delay,coinciding with the point where the autocorrelation function reaches a value of 0.1,is found to be more appropriate.Under typical experimental conditions,the correlation dimension rises with increasing superficial gas velocity and reducing static bed height.

关 键 词：流化床 压力信号 关联维数 G-P算法 自相关函数 

分 类 号：TK229.6[动力工程及工程热物理—动力机械及工程]