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基于极值响应面法的叶盘应力可靠性分析

Reliability Analysis of Blisk Stress Based on Extremum Response Surface Method
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摘要 针对航空发动机叶盘动态可靠性问题,提出了一种极值响应面法。该方法首先综合考虑了温度载荷和离心载荷的影响作用,通过确定性分析找到叶盘最大应力点;然后以叶盘材料密度、转速和温度作为输入随机变量,随机小批量抽取随机变量样本,得到叶盘应力在分析时域内的动态输出响应,并取各组动态输出响应在分析时域内的最大值,建立极值响应面函数;最后,应用蒙特卡罗法对ERSF模型进行大批量抽样,获得叶盘动态可靠性指标。 To the problem of the dynamic reliability analysis of aero-engine blisk, a method of Extremum response surface method (ERSM) was proposed. Firstly, the maximum stress point of the blisk was found by the deterministic analysis considering the coupling influences of the temperature load and centrifugal load. Then, the density of blisk, rotor speed, temperature is taken as input random variables. The input random sample was small sampled and the output response of the blisk stress within in the time domain was obtained. The entire maximum values of the dynamic output response in the analysis time domain and its corresponding input random variable are regard as new sample points. The extremum response surface function (ERSF) was established. Finally, the dynamic reliability index of the blisk was obtained by using the Monte Carlo method (MCM) large amount linkage sampling of the ERSF.
作者 孙田 张春宜 SUN Tian;ZHANG Chunyi(Harbin Metro Group CO.LTD,Harbin 150080,China;School of Mechanical and Power Engineering,Harbin Universityof Science and Technology,Harbin 150080,China)
出处 《现代制造技术与装备》 2019年第2期27-29,共3页 Modern Manufacturing Technology and Equipment
关键词 叶盘应力 极值响应面 蒙特卡罗 动态可靠性 Blisk stress Extremum response surface Monte carlo Dynamic reliability
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  • 1郭运强,张克实,耿小亮,刘芹.镍基定向凝固高温合金力学性能的统计分析[J].中国有色金属学报,2005,15(1):49-54. 被引量:5
  • 2宗培,曾凡其,范名琦,张海宽.10Ni5CrMoV船体钢力学性能统计分析[J].造船技术,2006(4):13-14. 被引量:4
  • 3Georgilakis P S, Hatziargyriou N D. Optimal distributed generation placement in power distribution networks models, methods, and future research[J]. IEEE Transactions on Power Systems, 2013, 28(3): 3420-3428.
  • 4Keane A, Ochoa L F, Borges C L T, et al. State-of-the-Art techniques and challenges ahead for distributed generation planning and optimization[J]. IEEE Transactions on Power Systems, 2013, 28(2): 1493-1502.
  • 5Naderi E, Seifi H, Sepasian M S. A dynamic approach for distribution system planning considering distributed generation[J]. IEEE Transactions on Power Delivery, 2012, 27(3): 1313-1322.
  • 6Doagou-Mojarrad H, Gharehpetian G B, Rastegar H, et al. Optimal placement and sizing of DG(distributed generation) units in distribution networks by novel hybrid evolutionary algorithm[J]. Energy, 2013, 54: 129-138.
  • 7Shaaban M F, El-Saadany E F. Accommodating high penetrations of PEVs and renewable DG considering uncertainties in distribution systems[J]. IEEE Transactions on PowerSystems, 2014, 29(1): 259-270.
  • 8Evangelopoulos V A, Georgilakis P S. Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm[J]. IET Generation, Transmission and Distribution, 2014, 8(3): 389-400.
  • 9Usaola J. Probabilistic load flow with correlated wind power injections[J]. Electric Power Systems Research, 2010, 80(5): 528-536.
  • 10Chen Y, Wen J, Cheng S. Probabilistic load flow method based on Nataf transformation and Latin Hypercube sampling[J]. IEEE Transactions on Sustainable Energy, 2013, 4(2): 294-301.

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