基于多色集合的贝叶斯诊断网络构造方法研究

李果; 高建民; 陈富民; 高智勇

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基于多色集合的贝叶斯诊断网络构造方法研究

专题研究 | 更新时间：2025-12-08

- 基于多色集合的贝叶斯诊断网络构造方法研究
- Construction of Bayesian Diagnostic Network Based on Polychromatic Sets
- 西安交通大学学报 2007年41卷第11期页码：1262-1266
- 作者机构：
  
  西安交通大学机械制造系统工程国家重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2007-03-02. 作者简介: 李果(1979～),男,博士生;高建民(联系人),男,教授,博士生导师. 基金项目: 国家高技术研究发展计划资助项目(2006AA04Z441)
- DOI：
  中图分类号： TH17;TP391
- 网络首发：2007-11-10，
  
  纸质出版：2007
- 稿件说明：
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李果, 高建民, 陈富民, 等. 基于多色集合的贝叶斯诊断网络构造方法研究[J]. 西安交通大学学报, 2007,41(11):1262-1266.

李果, 高建民, 陈富民, et al. Construction of Bayesian Diagnostic Network Based on Polychromatic Sets[J]. 2007, 41(11): 1262-1266.
李果, 高建民, 陈富民, 等. 基于多色集合的贝叶斯诊断网络构造方法研究[J]. 西安交通大学学报, 2007,41(11):1262-1266. DOI：

李果, 高建民, 陈富民, et al. Construction of Bayesian Diagnostic Network Based on Polychromatic Sets[J]. 2007, 41(11): 1262-1266. DOI：

摘要

针对贝叶斯诊断网络知识表达不一致的问题

提出了一种基于结构分解的层级式多重故障结构模型

并引入多色集合理论

对这种结构模型的底层框架进行形式化描述

使得模型便于计算机表达和操作.利用多色集合的推理矩阵来实现贝叶斯诊断网络(BDN)的自动生成

给出了具体的推理步骤.以汽轮机设备为例

对提出的方法进行了有效性验证

结果表明

该方法有助于BDN知识表达的规范化和构造过程自动化程度的提高.

Abstract

To solve the consistency problem of knowledge representation of the Bayesian diagnostic network

the mapping framework between the failure modes and the physical components are established

and a kind of hierarchical structural model of the multiple failures is proposed combined with the structural decomposition of the complex system. Following the polychromatic sets theory

the rock-bottom frame of this model is described formally

which facilitates constructing the computational expression and leading to a more convenient operation. Bayesian diagnostic network(BDN)is generated automatically via the iterative search process on the reasoning matrices of the polychromatic sets

and the specific procedure of the reasoning is presented. A case study for a steam turbine is reported to illustrate the validity of the proposed method

which is helpful to the standardization of the DBN knowledge representation and promotes the automation of the BDN construction process.

关键词

Keywords

references

Hu Zhaoyong. Bayesian diagnostic network: a powerful model for representation and reasoning of engineering diagnostic knowledge [J]. International Journal of Plant Engineering and Management, 2005, 10(1): 28-35.

Xiang Y, Olesen K G, Jensen F V. Practical issues in modeling large diagnostic systems with multiply sectioned Bayesian networks [J]. IJPRAI, 2000, 14(1): 59-72.

Koller D, Pfeffer A. Object-oriented Bayesian networks [C]∥ Proceedings of the 13th Annual Conference on Uncertainty in Artificial Intelligence. San Mateo, CA:Morgan Kaufmann, 1997: 302-313.

Przytula K W. An efficient framework for the conversion of fault trees to diagnostic Bayesian network models [C]∥ Proceedings of 2006 IEEE Aerospace Conference. Piscataway, USA:IEEE Press,2006: 1-14.

Li Zongbing, Xu Lida. Polychromatic sets and its application in simulating complex objects and systems [J]. Computers and Operations Research, 2003, 30(6): 851-860.

Xu Lida, Li Zongbing. A polychromatic sets approach to conceptual design of machine tools [J]. International Journal of Production Research, 2005, 43(12): 2397-2421.

Zhao Tingdi, Su Tiejun. Intelligent FMEA based on model FIORN [C]∥ Proceedings of Annual Reliability and Maintainability Symposium. New York:IEEE Press, 2004: 386-390.

Sun Yong, Ma Lin. An analytical model for interactive failures [J]. Reliability Engineering and System Safety, 2006, 91(5): 495-504.

李萨扬. 汽轮机及其辅助设备基于维修的FMEA [D]. 北京: 华北电力大学热能工程学院, 2002.

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