期刊文献+

核电厂智能诊断方法研究的进展 被引量:12

Advance in Study of Intelligent Diagnostic Method for Nuclear Power Plant
下载PDF
导出
摘要 文章评述神经网络、模糊逻辑和专家系统3种典型的智能方法在核电厂(NPP)运行状态监测和故障诊断中的应用研究进展。分析了基于神经网络(ANN)、模糊逻辑和专家系统的核电厂运行状态监测和故障诊断方法的研究状况及其特点。探索了核电厂智能诊断方法应用研究的发展趋势。分析表明:基于模糊逻辑和专家系统的核电厂智能诊断方法的研究成果相对较少;核电厂智能诊断方法研究主要集中在基于神经网络的状态监测与故障诊断方面;多种智能诊断方法的结合、神经网络与其它方法的结合,以及基于多神经网络的核电厂运行状态监测和故障诊断方法研究是核电厂智能诊断方法研究的重要发展趋势。 The advance of research on the application of three types of intell diagnostic approach based on neural network (ANN), fuzzy logic and expert syste the operation status monitoring and fault diagnosis of nuclear power plant (NPP) reviewed. The research status and characters on status monitoring and fault diag approaches based on neural network, fuzzy logic and expert system for nuclear p plant were analyzed. The development trend of applied research on intelligent diagn approaches for nuclear power plant was explored. The analysis results show that the search achievements on intelligent diagnostic approaches based on fuzzy logic and exsystem for nuclear power plant are not much relatively. The research of intelligent nostic approaches for nuclear power plant concentrate on the aspect of operation monitoring and fault diagnosis based on neural networks for nuclear power plant, advancing tendency of intelligent diagnostic approaches for nuclear power plant combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple n network diagnostic approaches.
作者 周刚 杨立
出处 《原子能科学技术》 EI CAS CSCD 北大核心 2008年第B09期92-99,共8页 Atomic Energy Science and Technology
关键词 核电厂 神经网络 模糊逻辑 专家系统 故障诊断 nuclear power plant neural network fuzzy logic expert system fault diagnosis
  • 相关文献

参考文献37

  • 1NABESHIMA K, SUZUDO T, SUZUKI K. Real-time nuclear plant monitoring with neural network[J]. Journal of Nuclear Science and Technology, 1998, 35(2): 93-100.
  • 2RUAN D. Fuzzy logic in the nuclear world[J]. Fuzzy Sets and System, 1995, 74: 5-13.
  • 3MARSEGUERRA M, ZIO E, BARALDI P. Fuzzy logic for signal prediction in nuclear system [J]. Progress in Nuclear Energy, 2003, 43 (1 4) : 373 380.
  • 4MARSEGUERRA M, ZIO E, OLDRINI A, et al. Fuzzy identification of transients in nuclear power plants [J]. Nuclear Engineering and De sign, 2003, 225: 285-294.
  • 5MARSEGUERRA M, ZIO E, BARALDI P. A fuzzy modeling approach to the identification of transients in nuclear components[J]. Annals of Nuclear Energy, 2004, 31: 2 093-2 112.
  • 6ZIO E, BARALDI P. Identification of nuclear transients via optimized fuzzy clustering[J]. Annals of Nuclear Energy, 2005, 32:1 068-1 080.
  • 7ZIO E, GOLA G. Neuro-fuzzy pattern classifica tion for fault diagnosis in nuclear components [J]. Annals of Nuclear Energy, 2006, 33: 415- 426.
  • 8GUIMARAES A C F, LAPA C M F. Fuzzy inference to risk assessment on nuclear engineering systems[J]. Applied Soft Computing, 2007, 7: 17-28.
  • 9GUIMARAES A C F, LAPA C M F. Adaptive fuzzy system for fuel rod cladding failure in nuclear power plant[J]. Annals of Nuclear Energy, 2007, 34: 233-240.
  • 10杨叔子,郑晓军.人工智能与专家系统[M].1版.西安:西安交通大学出版社,1990:111-120.

二级参考文献15

共引文献25

同被引文献85

引证文献12

二级引证文献64

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