Multi-Scale and Multi-Fractal Analysis of Electrostatic Potential Signal in a Gas-Solid Fluidized Bed and Recognition of Fluidization Pattern

The criterion of dividing the electrostatic potential signal in three characteristic scales is established by Hurst analysis of the wavelet decomposed signals. For bubbling fluidization, energy percent of meso-scale component is highest, which confirms that the electrostatic signals mainly reflect the action of bubbles. Furthermore, energy profiles of three components vary with the radial distance of the bed. It is also found that micro-scale and meso-scale components are sensitive to the flow regime transition.