Abstract The wavelet transform and rescaled range analysis were employed to reveal the multi-scale interactions between particles and fluids in a gas-solid cyclone reactor. A wavelet-threshold criterion was subsequently specified to identify clusters. By the established threshold, cluster dynamics can be determined from the transient signal. Experimental results show that the micro-, meso-, and macro-scale characteristics can be described by different wavelet decomposed sub-signals. The normalized energy of original solid holdup signals is mainly distributed on mesoscale signals. Cluster dynamics is found to be rather complex near the outer wall. The relationship between time fraction of clusters and average cluster concentration near the outer wall was further analyzed, dividing the cyclone reactor into dilute cluster regions and dense cluster regions. Finally, the prediction model between average cluster concentration and local average solids holdup in the vicinity of the outer wall was established.

中文翻译：

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气固旋流反应器的多尺度分辨率和簇动力学分析

摘要 采用小波变换和重标度范围分析揭示气固旋流反应器中颗粒与流体之间的多尺度相互作用。随后指定了一个小波阈值标准来识别集群。通过建立的阈值，可以从瞬态信号确定集群动态。实验结果表明，不同的小波分解子信号可以描述微观、中观和宏观尺度的特征。原始固含量信号的归一化能量主要分布在中尺度信号上。发现外壁附近的集群动力学相当复杂。进一步分析了簇的时间分数与外壁附近平均簇浓度之间的关系，将旋风反应器分为稀簇区和密集簇区。最后，建立了外壁附近平均簇浓度与局部平均固含率之间的预测模型。