工业过程控制中的数据协调研究

论文编号:ZD1093    论文字数:10179,页数:30

 摘要
 测量数据是实现过程设计、模拟、优化及控制等很多工程技术工作的基础和出发点,然而在实际工作过程中,测量数据不可避免地含有各种误差,包括随机误差和显著误差。数据校正的目的就是综合应用统计、辨识和优化技术，对实测数据进行调整，消除数据中包含的随机误差和显著误差，去掉明显错误的或不可靠的测量数据，从而提高测量数据的质量，同时对化工过程中的未测变量进行估计。
 通过对以往数据协调的分析研究，同时将理论研究同生产过程中的实际情况相结合，本文以前的一些数据校正技术在实际情况中碰到的若干具体问题进行了剖析，并提出相应的解决方案。具体包括以下几个方面：
 1． 通过大量的中外文献阅读，对数据协调技术的发展和研究方向做了一个较为系统完整的阐述。
 2． 针对传统数据协调模型的缺陷，通过添加一组基于测量值比例关系上下线的约束条件，并利用罚函数的概念将物料平衡的约束软约束的形式表示，并由此建立了一种新的数据协调模型。    改进后的数据协调模型只会对含有显著误差的测量值给予较大的协调量，而使得显著误差对 其他测量协调结果的影响脚下，具有较高的鲁棒性。仿真实验证明：基于该改进模型的协调 结果，可直接利用测量残差法进行显著误差检测，具有较高的误差检出率，且“虚警”的错    误率低。
 3． 详细叙述可上述改进数据协调模型在炼油厂连续催化重装装置中的实际应用情况。实际结果表明：本文所提出的数据协调检测技术具有显著的应用价值。
 
关键词：数据协调 罚函数 连续催化重整
                                

Abstract
 Measurement data to achieve the process of design, simulation, optimization and control, and many other engineering and technical work of the foundation and starting point. However, the actual chemical process, the measurement data will inevitably contain a variety of errors,Measurement errors can be mainly divided into two types: random error and gross error. Data rectification is a modern technique to improve the quality of Measurement data, and its main purpose is to eliminate the random errors and gross errors included in original data by making use of applied statistics, identification, optimization and other techniques.
      Base on the existing techniques of data reconciliation and gross errors detection,this
 thesis presented some new problems from real industrial processes and proposed the corresponding schemes.The main contributions include.
     1.  Review the development and the state-of-the-are of the techniques ni data reconciliation and gross errors detection   
 2.  In order to avoid the drawback of the traditional data reconciliation model,an
improved model is proposed in this thesis .Some new constraints for the ratio of measurement data are added to the new model,and the constraints of mass balance are transformed into soft constraints by using the method of penalty function.The data reconciliation procedur based on the improved model tends to make the measurements having gross errors get more modification than the others.Therefore,the new data reconciliation model is much more robust than the traditional.Besides,the results of the new model can  be used to detect gross errors directly.Simulation results show that the gross errors detection based on the new model is very sensitive to the presence of gross errors.
 3.  The above improved has been applied to practical data reconciliation for a continuous catalytic reforming unit nian oil refinery.Application results show that the improved data reconciliation model is very effective and can be widely used in industrial processes.
 
Keywords :data reconciliation；penalty function；ontinuous catalytic reformer.
         

 目录
摘要 Ⅰ
AbstractⅡ
目录.Ⅲ
1前言...1
2基于罚函数的数据协调模型...2
 2.1 数据协调模型  2
 2.2罚函数的构造..2
 2.3对数据协调模型的改进 3
3 基于罚函数的数据协调模型的工业应用.7
 3.1工业背景说明..7
 3.2 数据协调的应用.10
 3.2.1数据协调.11
 仿真图..12
 3.2.2 结论17
4  结论与展望.18
 4.1 研究工作总结.18
 4.2 数据协调技术研究展望18
5总结20
致谢22
参考文献23