工业生产过程中测量数据应该满足物料平衡等规律,但是在实际中不可避免的带有误差,导致了测量数据的不准确。测量数据的误差可分为随机误差和显著误差两大类。随机误差是受随机因素的影响而产生,服从一定的统计规律。而显著误差是由于测量仪器失灵等原因造成的。通过本课题掌握显著误差检测的相关知识,主要了解显著误差检测的三个方法,即节点残差检验法(NT)、测量残差检验法(MT)及MT-NT 联合改进检验法,并利用 MATLAB 编写程序实现 MT-NT联合改进检验法,并且通过仿真实例来检验 MT-NT 联合改进检验法检验显著误差的效果。10041
关键词 显著误差检测 MT 算法 NT 算法 MATLAB 编程 仿真 数据校正
Title An improved MT-NT method for gross error detection and data reconciliation
Abstract
The measurement data of industrial production process should satisfy the
material balance , but, in practice, the inevitable error will lead to
the inaccurate measurement data. The error of measurement data can be
pided into two types:random error and gross error. Influenced by the
random factors, random error is subjected to certain statistical rule.
However, the gross error is due to several reason ,such as measuring
instrument dysfunction. Through this graduation project , we can know well
about the gross error detection. Moreover, we can understand three methods
of the main gross error detection , namely the Node test, Measurement
test and an improved MT-NT method. And by using MATLAB to compile the
improved MT-NT method for gross error detection and data reconciliation ,
also with the simulation examples , the improved MT-NT method can be
tested.
Keywords gross error detection Mesurement test Node test MATLAB
programming simulation Data reconciliation
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