A sliding-window based signal processing method for characterizing
clusters in gas-solids high-density CFB reactor
Abstract
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 sliding time window and calculating the mean and
the standard 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 based on the bisection method on the entire piece of
signals. Using the proposed method, a more realistic characterization of
the clusters in both the HDCFB and LDCFB was obtained by considering the
bulk fluctuation of the gas-solids flow. The clusters in the 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.