曲文宇1,2 ,尚尔魁 1,2 ,刘洋1,2.服役条件下低压涡轮轴多参数载荷谱计算[J].航空发动机,2024,50(5):105-112
服役条件下低压涡轮轴多参数载荷谱计算
Calculation of Multi-Parameter Loading Spectrum of Low Pressure Turbine Shaft under Service Conditions
  
DOI:
中文关键词:  低压涡轮轴  气动载荷  机动载荷  Copula函数  联合概率分布函数  航空发动机
英文关键词:low pressure turbine shaft  aerodynamic load  maneuver load  Copula function  joint probability distribution function  aeroengine
基金项目:航空动力基础研究项目资助
作者单位
曲文宇1,2 ,尚尔魁 1,2 ,刘洋1,2 1.中国航发沈阳发动机研究所 2.辽宁省航空发动机冲击动力学重点实验室:沈阳110015 
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中文摘要:
      为了获得使用条件下航空发动机低压涡轮轴的多参数载荷谱及联合概率分布,基于发动机的气动相似准则,采用多元 非线性回归方法建立气动载荷模型,通过对转子及支撑结构的合理简化,采用结构力学理论建立机动载荷模型,结合服役发动机 的飞行测量参数,快速转换出低压涡轮轴的气动扭矩、气动轴向力和机动弯矩剖面。在此基础上,对载荷剖面进行峰谷检测和雨 流计数,形成载荷的峰谷循环矩阵。为了考虑载荷之间的相关性,采用核密度法估计各种载荷变量的边缘概率分布,采用Copula 函数构造低压涡轮轴载荷的联合概率分布函数,通过拟合优度检验确定了最优分布函数。结果表明:与统计数据结果相比,建立 的联合概率分布函数具有较好的计算精度,可以满足工程应用需要。
英文摘要:
      In order to obtain the multi-parameter loading spectrum and joint probability distribution of the low-pressure turbine shaft of an aeroengine under service conditions, based on the aerodynamic similarity criterion of the engine, the aerodynamic load model was established by using the multiple nonlinear regression method. Through the reasonable simplification of the rotor and support structure, the maneuver load model was established by using the structural mechanics theory. Combined with the in-flight measurement parameters of the engine in service, the aerodynamic torque, aerodynamic axial force, and dynamic bending moment profile of the low-pressure turbine shaft were rapidly converted. On this basis, the peak-valley detection and Rainflow counting were carried out on the load profile to form the peak-valley cycle matrix of the load. In order to consider the correlation between loads, the kernel density method was used to estimate the marginal probability distribution of various load variables, and the Copula function was used to construct the joint probability distribution function of the low pressure turbine shaft load, and the optimal distribution function was determined through the goodness of fit test. The results show that compared with the statistical data, the joint probability distribution function established has better calculation accuracy and can meet the needs of engineering applications.
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