气-固流化床压力脉动信号的多尺度熵分析

摘要

Multi-scale entropy algorithm was employed to investigate the pressure fluctuation signals of four flow patterns in the gas-solid fluidized bed, including the analysis of their multi-scale dynamic characteristics. The results show that the flow patterns' different dynamic characteristics can lead to multi-scale entropy differ-ences of pressure fluctuation signals; and in the small scale, the multi-scale entropy values of four patterns show an approximate linear growth with the increase of scale and the entropy growth becomes slow at the large scales.It's regarded the new method of employing the characteristics of multi-scale entropy's changing rate to identify the flow patterns.%采用多尺度熵算法对气-固流化床内4种典型流型的压力脉动信号进行研究,分析了其内部多尺度动力学特性. 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. 在小尺度下4种流化型态的多尺度熵值都是随着尺度的增加近似呈线性增长,在大尺度下熵值的增长十分缓慢. 此外,利用多尺度熵值变化速率特征识别气-固流化床内的流型,是一种新的流型辨识方法.