气-固流化床压力脉动信号的多尺度排列熵分析

Multi-scale Permutation Entropy Analysis of Pressure Fluctuation Signals of Gas-Solid Fluidized Bed

采用多尺度排列熵算法对气-固流化床内4种流型的压力脉动信号进行研究,结果表明:不同流型由于其动力学特性不同,导致压力脉动信号的多尺度排列熵值存在差异——4种流花形态的排列熵值都是随着尺度的增加而增大,其中固定床在大尺度上熵值最大,气力输送床在小尺度上熵值最大,鼓泡流化床在所有尺度上熵值最小;此外,多尺度排列熵值变化速率特征是流型辨识的新指示器。

The multi-scale permutation entropy analysis was applied to investigate the pressure fluctuation sig- nals of four flow patterns in the gas-solids recycled fluidized bed. The result shows that different flow patterns with various dynamic characteristics can bring the difference to multi-scale permutation entropy of pressure fluctuation signals. The permutation entropy values of four flow patterns rise with the increasing of scales, and the fixed bed on large scale and the pneumatic conveying bed on small scale have maximum permutation entro- py value and the bubbling fluidized bed on all scale has minimum permutation entropy value. The change rate of multi-scale permutation entropy becomes a new indicator for flow pattern identification.