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首页> 外文期刊>IFAC PapersOnLine >Adaptive Soft Sensing and On-line Estimation of the Critical Minimum Velocity with Application to an Oil Sand Primary Separation Vessel ?
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Adaptive Soft Sensing and On-line Estimation of the Critical Minimum Velocity with Application to an Oil Sand Primary Separation Vessel ?

机译:临界最小速度的自适应软传感和在线估计及其在油砂初级分离容器中的应用

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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.
机译:先前大多数关于在浆液管道内移动固体床所需的临界最小速度的研究都与设计步骤有关,在该步骤中,并未充分考虑过程的动力学。在本文中,提出了一种用于在线估计临界最小速度的通用框架,并将其应用于油砂行业中重要的主分离船(PSV)的底流。适当的统计和概率模型用于改善在线测量和估计。所提出的方法在检测PSV操作的不同条件下表现出令人满意的性能。

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