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首页> 外文期刊>International Journal of Innovative Computing Information and Control >EXTENDED SUPPORT VECTOR REGRESSION BASED DATA RECONCILIATION AND ITS APPLICATION TO PLANT-WIDE MASS BALANCE
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EXTENDED SUPPORT VECTOR REGRESSION BASED DATA RECONCILIATION AND ITS APPLICATION TO PLANT-WIDE MASS BALANCE

机译：基于扩展支持向量回归的数据协调及其在全厂质量平衡中的应用

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摘要

Process data measurements are important for process monitoring, control and optimization. However, process data may be deteriorated by gross errors in measurements. Therefore, it is significant to detect and estimate gross errors with data reconciliation. Meanwhile, in any modern petrochemical plant, the plant-wide mass data derived from process data rendering the real conditions of manufacturing are the key to the operation managements such as production planning, production scheduling and performance analysis. In this paper, an extended support vector regression approach for data reconciliation and gross error detection is proposed and applied to deal with the plant-wide mass balance problem. The proposed approach could simultaneously detect and estimate gross errors like measurement bias and process leaks. Then the proposed approach is applied to address the plant-wide mass balance problem with measurement bias and mass movement information lost, because of its superior characteristic for the issue. Both simulation and application results in this paper demonstrate that the proposed approach is accurate and effective to address plant-wide mass balance.
机译：过程数据测量对于过程监视，控制和优化很重要。但是，过程数据可能会因测量中的重大错误而恶化。因此，通过数据对账来检测和估计重大错误非常重要。同时，在任何现代石油化工厂中，从反映真实制造条件的过程数据中获得的整个工厂范围内的质量数据，是生产计划，生产计划和性能分析等运营管理的关键。本文提出了一种扩展的支持向量回归方法，用于数据对账和总误差检测，并用于解决工厂范围内的物料平衡问题。所提出的方法可以同时检测和估计总误差，例如测量偏差和过程泄漏。然后将所提出的方法应用于解决全厂范围内的质量平衡问题，因为该方法具有测量偏差和质量运动信息丢失的优点。本文的仿真结果和应用结果均表明，该方法准确有效地解决了全厂范围内的质量平衡问题。

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  • 作者

    HONGREN ZHAN; Yu MlAO; WEI WANG;

  • 作者单位

    School of Materials and Metallurgy Northeastern University Shenyang 110004, P. R. China,School of Mechanical Engineering Shenyang Institute of Chemical Technology No. 11 Street, Economic and Technological Development Zone, Shenyang 110142, P. R. China;

    College of Control Science and Engineering Dalian University of Technology No. 2, Linggong Road, Ganjingzi District, Dalian 116024, P. R. China;

    College of Control Science and Engineering Dalian University of Technology No. 2, Linggong Road, Ganjingzi District, Dalian 116024, P. R. China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    data reconciliation; support vector regression; parameter estimation; grosserror detection;

    机译：数据核对;支持向量回归参数估计;重大错误检测;

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