A sliding-window based signal processing method for characterizing particle clusters in gas-solids high-density CFB reactor

Particle clusters in CFB risers were identified from the instantaneous solids holdup signals by a new sliding -window based signal processing method. By shifting the time window and calculating the mean and the stan-dard deviation within it, a non-linear threshold curve for identifying the clusters was derived instead of the conventional constant threshold. The optimal sliding window size was determined as Wb = 1024 data points by the bisection method on the entire piece of signals. Using the proposed method, a more realistic characterization of the particle clusters in both HDCFB and LDCFB was obtained by considering the bulk fluctuation of the gas -solids flow. The clusters in HDCFB have higher solids holdup and lower velocity than that in the LDCFB. The HDCFB is also found to have a greater number of loose clusters for better gas-solids contacting and exchanges in the center of the riser.

Automated summary

This study proposes a new signal processing method to identify particle clusters in CFB risers using a sliding window and a non-linear threshold curve. By considering the fluctuation of the gas-solids flow, a more realistic characterization of the clusters in HDCFB and LDCFB is obtained.