A PROBABILISTIC APPROACH TO FAULT-DIAGNOSIS IN LINEAR LIGHTWAVE NETWORKS

被引：31

作者：

DENG, RH ^{[1
]}

LAZAR, AA ^{[1
]}

WANG, WG ^{[1
]}

机构：

[1] COLUMBIA UNIV,DEPT ELECT ENGN,NEW YORK,NY 10027

来源：

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS | 1993年 / 11卷 / 09期

关键词：

Bayesian network - Linear lightwave networks - Network fault diagnosis - Probabilistic reasoning - Updating algorithms;

D O I：

10.1109/49.257935

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The application of probabilistic reasoning to fault diagnosis in Linear Lightwave Networks (LLN's) is investigated. The LLN inference model is represented by a Bayesian network (or causal network). An inference algorithm is proposed that is capable of conducting fault diagnosis (inference) with incomplete evidence and on an interactive basis. Two belief updating algorithms are presented which are used by the inference algorithm for performing fault diagnosis. The first belief updating algorithm is a simplified version of the one proposed by Pearl for singly connected inference models. The second belief updating algorithm applies to multiply connected inference models and is more general than the first. We also introduce a t-fault diagnosis system and an adaptive diagnosis system to further reduce the computational complexity of the fault diagnosis process.

引用

页码：1438 / 1448

页数：11