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首页> 外文期刊>Journal of Chemical Engineering of Japan >Probabilistic Modeling and Prediction of Dynamic Discharge Process in Multiphase Pumps
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Probabilistic Modeling and Prediction of Dynamic Discharge Process in Multiphase Pumps

机译:多相泵动态排放过程的概率建模与预测

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摘要

To ensure the reliability of reciprocating multiphase pumps, it is necessary to predict the flow rate curve of the discharge process under different multiphase transportation conditions. Unfortunately, an accurate model describing the complicated characteristics is still not available. A modeling method of automatically selecting a probabilistic model is proposed for prediction of the discharge flow rate. A posterior probability index is proposed to evaluate the trained local Gaussian process regression (GPR) models. Additionally, to enhance the prediction reliability, the prediction variance-based index is explored to automatically choose a more suitable model from the selected local GPR and just-in-time GPR models for each new sample. Consequently, with limited samples, an efficient probabilistic modeling method is developed for online prediction of the discharge flow rate curve. The experimental results for a reciprocating multiphase pump validate its superiority.
机译:为了确保往复式多相泵的可靠性,有必要预测不同多相输送条件下排出过程的流量曲线。不幸的是,描述复杂特性的精确模型仍然不可用。提出了一种自动选择概率模型的建模方法,用于预测流量。提出了后验概率指数来评估训练的局部高斯过程回归(GPR)模型。另外,为了增强预测可靠性,探索了基于预测方差的索引,以针对每个新样本从选定的本地GPR模型和实时GPR模型中自动选择一个更合适的模型。因此,在样品有限的情况下,开发了一种有效的概率建模方法,用于在线预测排放流量曲线。往复式多相泵的实验结果证明了其优越性。

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