基于“3σ法则”的显著误差检测  

Detecting and Identifying Gross Errors Based on "3σ Rule"

作　　者：李九龙[1] 周凌柯[1] 

机构地区：[1]南京理工大学自动化学院,江苏南京210094

出　　处：《计算机与现代化》2012年第1期10-13,共4页Computer and Modernization

摘　　要：由于测量或传感器等其他原因造成测量数据中可能存在显著误差,直接进行数据校正会导致显著误差的扩散,影响数据校正结果的可靠性和准确性,因此在数据校正前,需要侦破识别并剔除含有显著误差的测量数据。现有的显著误差检测方法并不能完全识别显著误差,而且只能对有限的显著误差(小于等于3个)具有一定的检测效果,本文提出基于概率统计(3σ法则)的检测方法,识别效果优异,对3个以上的误差具有良好的侦破效果,并且采用显著误差同步补偿的方法,有效避免奇异矩阵的出现。Measurements can be contaminated with gross errors due to various reasons such as measurement irreproducibility, sensor problem and other reasons. The direct data reconciliation will diffuse gross errors, which affect reliability and accuracy of data reconciliation results. As a result, before the data reconciliation, it needs to identify and remove the measurement data contaminated with gross errors. The existing methods of gross errors detection have not a good detection result for limited gross errors （less than or equal to 3 ）. This paper presents a new method of detecting and identifying gross errors based on ＂3σ rule＂, which not only has a good detection result for limited gross errors but also for more gross errors. By using the method of collective compensation for gross errors, this method can effectively prevent the emergence of the singular matrix.

关 键 词：显著误差 数据校正 概率统计 同步补偿 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]