基于鲁棒目标函数的数据协调技术研究
关键词 数据校正 鲁棒性 目标函数 显著误差 Title Data reconciliation–based on robust objective function
Abstract
Reliable process data is the foundation of process monitoring, control
performance evaluation, process control, optimization and statistical
quality control. However, due to various sources such as measurement
irreproducibility, instrument degradation and malfunction, human error,
process-related errors, and other unmeasured errors，measurements can be
contaminated with errors. Rational use of the large volume of data generated
by chemical plants requires the application of suitable techniques to
improve their accuracy. Data reconciliation is a procedure of optimally
adjusting measured data so that the adjusted values obey the conservation
laws and other constraints.
In this paper the mechanism and research progress of traditional
robust data reconciliation methods were studied. And introduced a new data
reconciliation method-a robust data reconciliation method base on
objective function. This method is used for data reconciliation and gross
error detection under the steady state and analyze the Variable correlation
we encountered in the project . The examples show that this method with good
results for both linear and nonlinear problems.
Keywords data reconciliation robustness gross error Detection objective function
目 次
1 引言 . 1
1.1 数据校正技术概述 .. 1
1.2 数据分类技术 2
1.3 数据协调 . 4
1.4 显著误差检测 6
1.5 其他数据校正方法 .. 9
1.6 数据校正技术的运用 .. 10
1.7 论文研究内容 .. 12
2 数据分类、数据协调及显著误差检测方法简介 13
2.1 数据分类 13
2.2 显著误差检测的方法 .. 14
2.3 本章小结 17
3 鲁棒估计方法的基本原理 17
3.1 鲁棒估计基本概念 . 17
3.2 极大似然估计法 18
3.3 加权最小二乘估计法 .. 18
3.4 改进的最小二乘估计法 19
3.5 本章小结 22
4 基于鲁棒目标函数的数据协调技术研究 22
4.1 目标函数分析 .. 22
4.2 本章小结 24
5 数据校正实例 . 24
5.1 线性实例 24
5.2 非线性实例 . 27
5.3 本章小结 29
结 论 .. 30
致 谢 .. 31
参 考 文 献 .. 32
1 引言
通常在实际的化工生产过程中，我们需要在线或者离线采集大量的过程测量数据，
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