Probabilistic Transformer Fault Tree Analysis Using Bayesian Networks

被引：0

作者：

Cheim, Luiz ^{[1
]}

Lin, Lan ^{[2
]}

Dagnino, Aldo ^{[2
]}

机构：

[1] ABB Inc, TRES North Amer, Ann Arbor, MI USA

[2] ABB Corp Res, Ind Software Syst, Baden, Switzerland

来源：

2014 IEEE PES T&D CONFERENCE AND EXPOSITION | 2014年

关键词：

Asset management; power transformers; fault tree analysis; Bayesian networks;

D O I：

暂无

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：

This paper describes a novel application of probabilistic Bayesian networks for the identification of faulty conditions in power transformers, based on the well-known fault tree analysis procedure. The proposed technique emulates human judgment by the construction of a Bayesian net which closely resembles the structure of a typical expert-built power transformer fault tree. The proposed solution will be exemplified with test data from real cases.

引用

页数：5

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