Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/71404
Title: Bayesian network framework for rotor fault diagnosis
Other Titles: 转子故障贝叶斯诊断网络的研究
Authors: Xu, BG 
Qui, LS
Tao, XM 
Keywords: Rotor fault diagnosis Bayesian network
Issue Date: 2004
Publisher: 機械工業出版社
Source: 機械工程學報 (Chinese journal of mechanical engineering), 2004, v. 40, no. 1, p. 66-72 How to cite?
Journal: 機械工程學報 (Chinese journal of mechanical engineering) 
Abstract: 将贝叶斯网络技术引入到转子故障诊断领域,旨在提高故障诊断中不确定信息的处理能力和推理质量;提出了用于转子故障诊断的一般网络框架,使诊断故障时既考虑了实际的运行工况,又考虑了现场的故障征兆,这符合专家的诊断思路;转子同频故障网络算例验证了其良好的识别效果。
Beyasian 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.
URI: http://hdl.handle.net/10397/71404
ISSN: 0577-6686
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