稳态系统的过失误差识别

Gross Error Identification for Steady State System

数据校正包括数据协调和过失误差侦破与识别两部分,其中过失误差的侦破与识别一直是数据校正的重点和难点所在。针对系统偏差型的过失误差,研究了稳态系统中含有多个过失误差情况下的过失误差侦破与识别问题。提出了系统的过失误差可识别性的概念,分析了稳态系统的特性,指出了系统过失误差可识别的条件,并提出了过失误差的参数估计识别方法。计算实例表明,此方法可以准确地识别出系统所含的多个过失误差,具有很重要的理论意义。

Data rectification can be classified into two categories: data reconciliation, gross error detection and identification. Gross error detection and identification is the bottleneck of data rectification. For steady state system, the detection and identification of multiple gross errors of bias type was studied. The concept of identifiability of gross error for the process was defined. Based on the property analysis of the steady state system, identification conditions of gross errors for the process were pointed out and an identification method of the gross errors based on parameter estimation was proposed. The computation results show that the method can identify multiple gross errors existing in the measurements correctly and estimate their values accurately.