中国机械工程 ›› 2010, Vol. 21 ›› Issue (10): 1135-1139.

• 机械基础工程 •    下一篇

低周疲劳失效的涡轮盘可靠性灵敏度设计

张义民;王鹏;杨周;张飞
  

  1. 东北大学,沈阳,110004
  • 出版日期:2010-05-25 发布日期:2010-06-02
  • 基金资助:
    国家863高技术研究发展计划资助项目(2007AA04Z442);国家自然科学基金资助项目(50875039) 
    National High-tech R&D Program of China (863 Program) (No. 2007AA04Z442);
    National Natural Science Foundation of China(No. 50875039)

Reliability Sensitivity Design for a Turbine Disc with Low Cycle Fatigue Failure

Zhang Yimin;Wang Peng;Yang Zhou;Zhang Fei
  

  1. Northeastern University,Shenyang,11004
  • Online:2010-05-25 Published:2010-06-02
  • Supported by:
     
    National High-tech R&D Program of China (863 Program) (No. 2007AA04Z442);
    National Natural Science Foundation of China(No. 50875039)

摘要:

将有限元方法、低周疲劳模型、径向基函数神经网络技术与可靠性理论相结合,给出了涡轮盘低周疲劳可靠性灵敏度设计方法。应用径向基函数神经网络拟合得到随机设计变量与失效寿命之间的函数关系式,根据随机摄动法与可靠性灵敏度技术进行灵敏度设计。径向基函数神经网络技术的引入克服了工程实际无法给出极限状态函数显式的问题,而灵敏度技术使各变量对可靠度的影响得以定量表达,具有很好的指导意义。

关键词:

Abstract:

Based on the finite element method,a low cycle fatigue model,
RBF neural network technique and reliability theory, the reliability sensitivity design for one turbine disc with low cycle fatigue failure were studied in detail.First, the explicit relational expression among the design parameters and the failure life were given in term of RBF neural network. On the basis of the trained neural network,the MPPPM can be used to begin the sensitivity design. Hence,the introduction to RBF neural network solves the explicit expression of the limit state function which is difficult to obtain in engineering, and the method of sensitivity which expresses the influence the parameters posed on the reliability in quantity has a strong significance.

Key words: reliability, sensitivity, radial basis function(RBF) neural network, most probable point perturbation method(MPPPM), Monte Carlo method

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