Abstract:

In industrial polymerization processes of Innovene and Chisso for polypropylene, agglomeration of polymer particles in horizontal stirred bed reactors (HSBR) has negative impacts on the reactor operation efficiency. A method for agglomeration detection based on attractor comparison by using acoustic emission (AE) sensors is presented. The method, which belongs to time domain analysis, is based on the comparison of time series of AE signals acquired form a normal state with time series measured during operation of the reactor. The nature of the method is whether two time series are generated by the same mechanism. A statistical characteristic S is used to test the null hypothesis that two multidimensional probability distributions are identical. When S <3, it means that the operation state now is normal, if S >3, it indicates with more than 95% confidence that agglomeration in the reactor has taken place. The results from lab-scale experiments showed that the method was sensitive to small changes in the particle-size distribution when the AE sensors were located at the optimal position and the original signals had been pre-processed, for examples, de-noising and normalization, etc . Thus, the agglomeration in HSBR could be quickly and exactly detected online by the acoustic emission technique.