公开(公告)号：WO2015079192A1

公开(公告)日：2015-06-04

申请号：PCT/GB2013/053157

申请日：2013-11-29

Applicant: GE AVIATION SYSTEMS LIMITED

Inventor： CALLAN, Robert Edward ,  HARDWICK, David Stephen

IPC: G06K9/62

CPC classification number: G06K9/66 ,  G06K9/6215 ,  G06K9/6257 ,  G06K9/6259 ,  G06K9/6284 ,  G06K9/6296

Abstract: A method (100) of constructing a probabilistic graphical model (10) of a system from data that includes both normal and anomalous data includes the step of learning parameters of a structure for the probabilistic graphical model (10). The structure includes at least one latent variable (26) on which other variables (12, 14, 16, 18, 20, 22, 24) are conditional, and has a plurality of components. The method further includes the steps of: iteratively associating one or more of the plurality of components of the latent variable (26) with normal data;constructing a matrix of the associations;detecting abnormal components of the latent variable (26) based on one of a low association with the normal data or the matrix of associations; and deleting the abnormal components of the latent variable (26) from the probabilistic graphical model (10).

Abstract translation: 从包括正常数据和异常数据的数据构建系统的概率图形模型（10）的方法（100）包括学习用于概率图形模型（10）的结构的参数的步骤。 该结构包括至少一个潜在变量（26​​），其上的其他变量（12,14,16,18,20,22,24）是有条件的并且具有多个分量。 该方法还包括以下步骤：将潜在变量（26​​）的多个分量中的一个或多个与正常数据进行迭代关联;构建关联矩阵;基于以下之一来检测潜在变量（26​​）的异常分量： 与正常数据或关联矩阵的低关联度; 以及从所述概率图形模型（10）中删除所述潜在变量（26​​）的异常分量。