In order to reveal multiscale dynamic distribution characteristics of dust collectors in a wet scrubber, a method for scale decomposition of dust collectors based on Wigner–Ville distribution (WVD), empirical mode decomposition (EMD) and Hurst analysis of grayscale signals is reported. The WVD features of grayscale signals were used to observe the energy distribution details of dust collectors at different frequency bands and time periods. Then, the scale decomposition of dust collectors based on EMD and Hurst analysis of the grayscale signals was carried out. These analysis results showed that the motion behaviors of micro-, meso- and macro-scale subsets of dust collectors were determined: specifically, the single fractal features of micro-scale subsets conform to the motion characteristics of individual dust collectors. The dual fractal characteristics of meso-scale subsets denote the interactions among dust collector aggregations. Additionally, the fractal features of the macro-scale subsets reflect persistent liquid surface fluctuation behavior in wet scrubbers. Finally, the relative contribution of dust collectors at different scales to the effectiveness of dust removal was represented. This is not only an important innovation in the study of micro mechanism of wet dust removal but provides powerful theoretical support for technological innovations in wet scrubbers.

Implications: The multiscale dynamic distribution characteristics of dust collectors in wet dust scrubber were explored, using a method for scale decomposition of dust collectors based on Wigner–Ville distribution, empirical mode decomposition and Hurst analysis of grayscale signals. The fractal characteristics of different scales of dust collectors are determined. Besides, the contribution of different scales of dust collectors to the effect of dust removal is quantized. Therefore, this research is very meaningful, which not only has important innovation in the study of micro mechanism of wet dust collectors but provides a powerful theoretical support for technological innovation of wet dust scrubbers.

为了揭示湿式除尘器中集尘器的多尺度动态分布特性，报道了一种基于Wigner-Ville分布（WVD），经验模式分解（EMD）和灰度信号的Hurst分析的集尘器尺度分解方法。灰度信号的WVD功能用于观察不同频段和时间段内集尘器的能量分布细节。然后，基于EMD和灰度信号的Hurst分析，对除尘器的水垢进行了分解。这些分析结果表明，确定了集尘器的微观，中观和宏观子集的运动行为：具体而言，微观子集的单个分形特征符合各个集尘器的运动特征。中尺度子集的双重分形特征表示集尘器聚集之间的相互作用。另外，宏观子集的分形特征反映了湿式洗涤器中持续的液体表面波动行为。最后，代表了不同规模的集尘器对除尘效率的相对贡献。这不仅是研究湿法除尘微观机理的一项重要创新，而且为湿法洗涤塔的技术创新提供了有力的理论支持。代表了不同规模的集尘器对除尘效率的相对贡献。这不仅是研究湿法除尘微观机理的一项重要创新，而且为湿法洗涤塔的技术创新提供了有力的理论支持。代表了不同规模的集尘器对除尘效率的相对贡献。这不仅是研究湿法除尘微观机理的一项重要创新，而且为湿法洗涤塔的技术创新提供了有力的理论支持。

启示：利用湿式除尘器中的除尘器的多尺度动态分布特性，采用基于Wigner-Ville分布，经验模态分解和灰度信号的Hurst分析的除尘器规模分解方法。确定了不同规模的集尘器的分形特征。此外，量化了不同规模的集尘器对除尘效果的贡献。因此，这项研究意义重大，不仅在研究湿式除尘器的微观机理方面具有重要的创新意义，而且为湿式除尘器的技术创新提供了有力的理论支持。