...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computers & Chemical Engineering >Predictive analytics in the petrochemical industry: Research Octane Number (RON) forecasting and analysis in an industrial catalytic reforming unit
【24h】

Predictive analytics in the petrochemical industry: Research Octane Number (RON) forecasting and analysis in an industrial catalytic reforming unit

机译：石油化工行业预测分析：工业催化改革单位研究辛烷值（RON）预测分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The Research Octane Number (RON) is a key parameter for specifying gasoline quality. It assesses the ability to resist engine knocking as the fuel burns in the combustion chamber. In this work we address the critical but complex problem of predicting RON using real process data in the context of a catalytic reforming process from a petrochemical refinery. We considered data collected from the process over an extended period of time (21 months). RON measurements are obtained offline, by laboratory analysis, with a significant delay and at much lower rates when compared to process measurements. The proposed workflow covers all the way from data collection, cleaning and pre-processing to data-driven modelling, analysis and validation for a real industrial refinery located in Portugal. The accuracy achieved with the best soft sensors open up perspectives for industrial applications and the results obtained also provide relevant information about the main RON variability sources.
机译：研究辛烷值（RON）是指定汽油质量的关键参数。它评估了抵抗发动机敲击的能力，因为燃料燃烧在燃烧室中。在这项工作中，我们解决了从石油化工炼油厂的催化重整过程的背景下使用真实过程数据预测RON的关键但复杂的问题。我们考虑了在延长的时间内从过程中收集的数据（21个月）。与工艺测量相比，通过实验室分析，通过实验室分析获得ron测量，通过实验室分析，延迟显着延迟，并且速率低得多。所提出的工作流程从数据收集，清洁和预处理到数据驱动的建模，分析和验证，以获得位于葡萄牙的真正工业炼油厂的数据驱动的建模，分析和验证。使用最佳软传感器实现的准确性为工业应用开辟了透视，并获得了结果的结果还提供了有关主要RON可变性来源的相关信息。

著录项

  • 来源
    《Computers & Chemical Engineering》 |2020年第4期|106912.1-106912.15|共15页
  • 作者

    Tiago Dias; Rodolfo Oliveira; Pedro Saraiva; Marco S. Reis;

  • 作者单位

    Univ Coimbra CIEPQPF Department of Chemical Engineering Rua Silvio Lima Polo Ⅱ - Pinhal de Marrocos 3030-790 Coimbra Portugal Petrogal SA Rua Belchior Robles 4451-852 Leca da Palmeiro Portugal;

    Petrogal SA Rua Belchior Robles 4451-852 Leca da Palmeiro Portugal;

    Univ Coimbra CIEPQPF Department of Chemical Engineering Rua Silvio Lima Polo Ⅱ - Pinhal de Marrocos 3030-790 Coimbra Portugal Dean of NOVA IMS Campus de Campolide 1070-312 Lisboa Portugal;

    Univ Coimbra CIEPQPF Department of Chemical Engineering Rua Silvio Lima Polo Ⅱ - Pinhal de Marrocos 3030-790 Coimbra Portugal;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Predictive data analytics; Soft sensors; Research Octane Number; Catalytic reforming; Big Data;

    机译：预测数据分析;软传感器;研究辛烷值;催化重整;大数据;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号