Power spectrums of acoustic emission (AE) on the walls of fluidized beds were calculated, to investigate the
particle movement in the bed. It is determined that the main frequency of the AE power spectrum can be
related to the average Landau−Lifshitz collision time of particles impacting on the walls of the bed. A frequency model was proposed to examine the effect of superficial velocity, the size and density of particles,
and the elastic modulus of the materials. The influence of chunk formation on the structure of AE power
spectrum was shown to be significant. A very good agreement of frequency was observed between the AE
measurement and the model prediction in a fluidized bed both for cold mode in laboratory scale and hot
mode in plant scale. The AE spectrum can be used to monitor the particle average size and chunk formation
successfully.
The occurrence of agglomeration in fluidized-bed production of polyolefin can have negative impacts on the efficiency of the reactor operation and may lead to defluidization and unscheduled shutdown of the plant. A novel method by using acoustic emission (AE) sensors was developed to detect different types of agglomeration in fluidized bed. Chaos analysis was discussed, and coefficients of malfunction were defined to recognize agglomeration. AE signals we divided into micro-, meso-, and macroscales by wavelet transform, and on the basis of the energy of mesoscale fraction analysis of AE signals, a prediction model was developed to predict the size of moving chunks in the bed. The application effect of AE method was illustrated with experiments carried out both in laboratory and the plant.
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