Application of Kalman Filter to Support Decision- Making in the Maintenance of Heat Exchangers in Slurry Polymerization Processes

Fouling is one of the main problems in the operation of heat exchangers since it reduces the heat transfer efficiency. In industrial practice therefore these equipment have to be periodically removed for cleaning. The availability of fouling monitoring methods supports decision making concerning the periodic cleaning and therefore can reduce operational costs. This paper presents a model to estimate the heat transfer coefficient for the slurry polymerization process based on the Extended Kalman Filter (EKF). Some advantages of this proposed method are that neither special sensors nor steady state operating conditions are needed. Results indicate that the EKF can predict the parameter reasonably well with deviations up to 5% at the end of the campaign. The model allows identifying the fouling of the heat exchangers, one of the main drivers of production costs in industry, therefore avoiding unnecessary shut down for maintenance.