Agglomeration Detection Based on Attractor Comparison in Horizontal Stirred Bed Reactors by Acoustic Emission Sensors

摘要

In industrial propylene polymerization technology of Innovene and Chisso, agglomeration of polymer particles in horizontal stirred bed reactors (HSBR) has significant negative impacts on the reactor efficiency. If the hydrodynamic change could be detected early enough, then large chunks may not be formed nor cause an unscheduled shutdown of the plant. A novel non-invasive acoustic emission (AE) technique combined with an attractor comparison method is presented. It is based on the comparison of the time series of AE signals acquired from a normal state with the time series measured during operation of the bed. The nature of the method is to determine whether or not two time series are generated by the same mechanism. A statistical characteristic S is used to test the null hypothesis that the two multidimensional probability distributions are identical. Experiments were carried out at room temperature in a 475 mm i.d. laboratory HSBR. The results demonstrated that the method is sensitive to small changes in the particle size distribution. It is, therefore, indicated that the proposed method not only can offer "early and accurate warning," but also has the potential to locate the agglomeration in HSBR with multiple AE sensors.