期刊文献+

燃气轮机性能评价的模糊综合评判方法 被引量:43

FUZZY COMPREHENSIVE METHOD FOR GAS TURBIINE EVALUATION
下载PDF
导出
摘要 针对目前燃气轮机性能评价研究一般仅局限于某一方面,不能全面反应燃气轮机系统性能问题,该文提出了利用模糊数学理论,从技术经济、功能设置、可靠性及维修性4个方面来综合评判燃气轮机系统性能的新方法。文中分析过程给出的为二阶模糊综合评判,具体应用时,阶数可根据实际情况有所增减,同时权重系数及模糊评判矩阵的确定应综合各方面意见。模糊综合评判方法不仅适用于系统性能多因素评判,而且适用于组成系统的单体设备的多因素或单因素性能评判。 Currently to analyses the performance of a gas turbine is limited in a certain aspect, but not the unit a whole. Based on the theory of fuzzy mathematics, the paper puts forward a method for evaluating the gas turbine performance comprehensively from four aspects, namely from technical economy, function capability, reliability and maintainability. The analysis gives a second order fuzzy comprehensive evaluation. The order of fuzziness can be changed according to the specific cases. Meanwhile, the weight and fuzzy evaluating matrices should also be determined by a consideration of every aspect. This new method is applicable not only for multi-factor evaluation of system performance, but also for a mono-or multi- factor evaluation of unit performance for system.
出处 《中国电机工程学报》 EI CSCD 北大核心 2003年第9期218-220,共3页 Proceedings of the CSEE
关键词 燃气轮机 性能评价 模糊综合评判方法 可靠性 模糊数学理论 Gas turbine Fuzzy theory Comprehensive evaluation method Performance analysis
  • 相关文献

参考文献9

二级参考文献22

  • 1匿名著者,1989年
  • 2汪健(Wang Jian).基于热力参数的大型机组热力循环的集成故障诊断系统(Integrated fault diagnosis system baded on parameters for thermal cycle of large power generation units)[D].北京:清华大学(Beijing:Tsinghua University),1996.
  • 3Munoz A,Sanz-Bobi M A.An incipient fault detection system based on the probabilistic radial basis function network:Application to the diagnosis of the condenser of a coal power plant[J].Neurocomput-ing,1998,(23):177-194.
  • 4Alefeld G,Herzberger J.Introduction to interval computations [M].New York:Academic Press.1983.
  • 5Ishibuchi H,Miyazaki A,Kwon K,et al.Learning from incomplete training data with missing values and medical application [A].Proceedings of the international joint conference on neural networks (IJCNN'93)[C].1993,1871-1874.
  • 6Hernandez C A,Espi J,Nakayama K A.Generalization of backp-ropagation to interval arithmetic[A].Proceedings of the world cong-ress on neural networks (WCNN'93)[C].1993,131-134.
  • 7Takagi T, Sugeno M. Fuzzy identification of systems and its applications to modeling and control [J]. IEEE Trans Syst.,Man, Cybern., 1985,15(1): 116-130.
  • 8Nie J H, Lee T.H..Rule-based modeling: fast construction and optimal manipulation [J]. Part A, IEEE Trans. Syst.,Man, Cybem., 1996,26(6):728-738.
  • 9Xu L, Krzyzay A, Oja E. Rival penalized competitive learning for clustering analysis, RBF net, and curve detection [J], IEEE Trans.Neural Networks, 1993, 4(4): 636-649.
  • 10Shimoji S.,Lee S. Data clustering with entropical scheduling [C].Proceeding of IEEE Conference on Fuzzy Sytems, 1994,2423-2428.

共引文献161

同被引文献419

引证文献43

二级引证文献680

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部