Abstract
A novel method, based on acoustic emission (AE) techniques, for detecting agglomeration in fluidized beds is presented. Particle size characteristics are determined based on the principle that AE signals with different frequency band energies are emitted when particles of different sizes impact an internal wall. By applying chaotic analysis to the AE signals, the malfunction coefficients are well defined. Agglomeration in the fluidized bed can then be detected by the sudden variation of malfunction coefficients. AE signals were investigated in a laboratory scale heated fluidized bed and an industrial polyethylene fluidized bed. Experimental data showed that the malfunction coefficients increased with the growth of agglomeration. The results indicated that agglomeration in fluidized beds can be predicted and diagnosed effectively and precisely using AE techniques based on chaotic analysis.
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