基于模糊理论和BN的燃气轮机健康状态评估方法
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TK478 TP182

基金项目:

海军工程大学自然科学基金


A Gas Turbine Health Evaluation Method Based on Fuzzy Theory and Bayesian Network
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对小样本条件下燃气轮机的健康状态评估问题,提出了基于模糊理论和近等式约束的贝叶斯网络的燃气轮机健康状态评估方法。用模糊理论整合专家先验知识,以近等式约束的形式将其融合到贝叶斯网络参数学习中,再通过贝叶斯网络模型得到燃气轮机健康状态。以某型燃气轮机为例进行仿真,结果表明,该型燃气轮机处于正常状态,与实际运行状态相符,验证了方法的可行性,具有一定的工程应用价值。

    Abstract:

    To evaluate the health status of gas turbine under small sample conditions, this paper proposes a Bayesian network health status evaluation method based on fuzzy theory and near-equality constraints. The expert priori knowledge was integrated with the fuzzy theory, which was fused into the Bayesian network parameter learning in the form of nearly equality constraint, and then the gas turbine health state was obtained through the Bayesian network model. Taking a certain type of gas turbine as an example, the simulation results show that this type of gas turbine is in normal state and consistent with the actual operation state, which verifies the feasibility of the method and has certain engineering application value.

    参考文献
    相似文献
    引证文献
引用本文

曾强,黄政,魏曙寰. 基于模糊理论和BN的燃气轮机健康状态评估方法[J]. 科学技术与工程, 2020, 20(11): 4363-4369.
Zeng Qiang, Huang Zheng, Wei Shuhuan. A Gas Turbine Health Evaluation Method Based on Fuzzy Theory and Bayesian Network[J]. Science Technology and Engineering,2020,20(11):4363-4369.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2019-07-29
  • 最后修改日期:2020-01-02
  • 录用日期:2019-09-27
  • 在线发布日期: 2020-05-29
  • 出版日期:
×
律回春渐,新元肇启|《科学技术与工程》编辑部恭祝新岁!
亟待确认版面费归属稿件,敬请作者关注