| 基于RBF神经网络的涡轮盘疲劳可靠性分析 |
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| 引用本文： | 高阳,白广忱,于霖冲.基于RBF神经网络的涡轮盘疲劳可靠性分析[J].机械设计,2009,26(5). |
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| 作者姓名： | 高阳 白广忱 于霖冲 |
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| 作者单位： | 北京航空航天大学能源与动力工程学院,北京,100083 |
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| 摘 要： | 涡轮盘是发动机的关键部件,在高温、高转速的条件下工作,因此对其进行疲劳可靠性分析具有重要意义.由于涡轮盘结构热一机械耦合分析的复杂性,对其进行可靠性分析时,直接用Monte-Carlo方法计算量太大,常规的多项式响应面方法在精度上又难以满足要求.径向基函数(radial basis function,RBF)神经网络具有很强的非线性函数逼近能力,在涡轮盘低循环疲劳可靠性分析中采用RBF神经网络结合Monte-Carlo的方法得到了疲劳寿命的概率分布,并与直接用Monte-Carlo模拟和响应面方法进行了对比.RBF神经网络结合Monte-Carlo的方法具有高精度、高效率的优点,在涡轮盘等复杂结构可靠性分析中具有很好的应用前景.
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| 关 键 词： | 涡轮盘 热-机械耦合 径向基函数 低循环疲劳 可靠性 |
Fatigue reliability analysis of turbine-disk based on RBF neural network |
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| GAO Yang,BAI Guang-chen,YU Lin-chong.Fatigue reliability analysis of turbine-disk based on RBF neural network[J].Journal of Machine Design,2009,26(5). |
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| Authors: | GAO Yang BAI Guang-chen YU Lin-chong |
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| Affiliation: | School of Jet Propulsion;Beijing University of Aeronautics & Astronautics Beijing;Beijing 100083;China |
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| Abstract: | Turbine-disk is the key component of aero-engine,it works under the conditions of high temperature and high speed,thus to carrying out analysis on its fatigue reliability possesses important significance.On account of the complexity of the analysis on the thermo-mechanical coupling of turbine-disk,while carrying out its reliability analysis the amount of calculation is too large by using the directly Monte-Carlo method and the conventional multinomial response surface method is also difficult to satisfy the... |
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