Adaptive Soft Sensing and On-line Estimation of the Critical Minimum Velocity with Application to an Oil Sand Primary Separation Vessel∗

Abstract Most of the previous studies on the required critical minimum velocity to move the solid bed inside the slurry pipelines are related to the design step where the dynamics of the process are not thoroughly considered. In this paper, a general framework for on-line estimation of the critical minimum velocity is proposed and applied to the underflow stream of an important Primary Separation Vessel (PSV) in an oil sand industry. Appropriate statistical and probabilistic models are used to improve the on-line measurements and estimations. The proposed method demonstrates a satisfactory performance in detection of different conditions of the PSV operations.