Bayesian network framework for rotor fault diagnosis

Bingang Xu; Liangsheng Qu; Xiaoming Tao

Bayesian network framework for rotor fault diagnosis

Bingang Xu
, Liangsheng Qu
, Xiaoming Tao

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

15 Citations (Scopus)

Abstract

Bayasian network (BN) is applied to the field of rotor fault diagnosis for increasing the ability to handle uncertainty and inference quality. A general framework of BN for rotor fault diagnosis is proposed, which concerns more information both from the machine performance layer and the symptom layer. The network accords with the general diagnosis thinking of experts. The rotor synchronous fault diagnosis examples demonstrate its good recognition results.

Original language	English
Pages (from-to)	66-72
Number of pages	7
Journal	Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering
Volume	40
Issue number	1
Publication status	Published - 1 Jan 2004

Keywords

Bayesian network
Fault diagnosis
Rotor

ASJC Scopus subject areas

Mechanical Engineering

Cite this

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title = "Bayesian network framework for rotor fault diagnosis",

abstract = "Bayasian network (BN) is applied to the field of rotor fault diagnosis for increasing the ability to handle uncertainty and inference quality. A general framework of BN for rotor fault diagnosis is proposed, which concerns more information both from the machine performance layer and the symptom layer. The network accords with the general diagnosis thinking of experts. The rotor synchronous fault diagnosis examples demonstrate its good recognition results.",

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author = "Bingang Xu and Liangsheng Qu and Xiaoming Tao",

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TY - JOUR

T1 - Bayesian network framework for rotor fault diagnosis

AU - Xu, Bingang

AU - Qu, Liangsheng

AU - Tao, Xiaoming

PY - 2004/1/1

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N2 - Bayasian network (BN) is applied to the field of rotor fault diagnosis for increasing the ability to handle uncertainty and inference quality. A general framework of BN for rotor fault diagnosis is proposed, which concerns more information both from the machine performance layer and the symptom layer. The network accords with the general diagnosis thinking of experts. The rotor synchronous fault diagnosis examples demonstrate its good recognition results.

AB - Bayasian network (BN) is applied to the field of rotor fault diagnosis for increasing the ability to handle uncertainty and inference quality. A general framework of BN for rotor fault diagnosis is proposed, which concerns more information both from the machine performance layer and the symptom layer. The network accords with the general diagnosis thinking of experts. The rotor synchronous fault diagnosis examples demonstrate its good recognition results.

KW - Bayesian network

KW - Fault diagnosis

KW - Rotor

UR - https://www.scopus.com/pages/publications/2342526628

M3 - Journal article

SN - 0577-6686

VL - 40

SP - 66

EP - 72

JO - Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering

JF - Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering

IS - 1

ER -

Bayesian network framework for rotor fault diagnosis

Abstract

Keywords

ASJC Scopus subject areas

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