吉林大学学报(工学版) ›› 2022, Vol. 52 ›› Issue (2): 466-473.doi: 10.13229/j.cnki.jdxbgxb20211134

• 车辆工程·机械工程 • 上一篇    

基于混合不确定性的螺旋锥齿轮结构可靠性分析

邱继伟(),罗海胜()   

  1. 中国兵器工业标准化研究所,北京 100089
  • 收稿日期:2021-10-29 出版日期:2022-02-01 发布日期:2022-02-17
  • 通讯作者: 罗海胜 E-mail:qiujiwei235@126.com;43365843@qq.com
  • 作者简介:邱继伟(1986-),男,副研究员,博士.研究方向:装备通用质量特性.E-mail:qiujiwei235@126.com
  • 基金资助:
    中央军委装备发展部技术基础项目(JZX7J201912ZL005400)

Structure reliability analysis of spiral bevel gear based on hybrid uncertainties

Ji-wei QIU(),Hai-sheng LUO()   

  1. China Ordnance Industrial Standardization Research Institute,Beijing 100089,China
  • Received:2021-10-29 Online:2022-02-01 Published:2022-02-17
  • Contact: Hai-sheng LUO E-mail:qiujiwei235@126.com;43365843@qq.com

摘要:

螺旋锥齿轮结构中各设计参数和边界条件往往存在随机类和区间类参数混杂的情况,由于两类不确定参数的测度空间和测度性质不同,基于概率论的传统可靠性建模分析方法将不再适用,为此提出了一种基于随机-区间混合不确定性的二阶可靠性分析方法。利用二阶泰勒级数展开法在最可能失效点(MPP)近似展开极限状态方程,在此基础上引入极坐标,将n维极限状态函数的近似转化为一个新的极坐标二维函数;利用函数梯度向量代替直角坐标系中的失效域质心向量思想,在极坐标空间中推导随机变量和区间变量的极坐标概率密度函数;以二次二阶矩可靠性分析方法为基础,利用积分法推导出失效概率区间。最后,通过某装备综合传动装置的螺旋锥齿轮结构可靠性分析案例验证了本文方法的有效性。

关键词: 系统工程, 混合可靠性分析, 二阶可靠性方法, 极坐标, 螺旋锥齿轮

Abstract:

There is often a mix of random and interval parameters in the design parameters and boundary conditions of spiral bevel gears. Because the measurement space and properties of the two types of uncertain variables are different, the traditional reliability modeling and analysis methods based on probability theory will no longer be applicable. Therefore, a second-order reliability analysis method for hybrid structural analysis with random and interval variables was presented. The limit state function is approximated at the most probable point(MPP) by using the second-order Taylor series expansion method. On this basis, the polar coordinates are introduced and the n-dimensional limit state function is approximately transformed into a new polar coordinate two-dimensional function. By using the gradient vector of the function instead of the failure domain centroid vector, the polar probability density functions of the random variables and the interval variables are derived in polar space. Based on the second-order moment reliability analysis method, the failure probability interval is deduced by the integration method. Finally, the validity of the proposed method is verified by a structural reliability analysis case for spiral bevel gears of a weapon's comprehensive transmission.

Key words: systems engineering, hybrid reliability analysis, second-order reliability method, harmonic reducer, spiral bevel gear

中图分类号: 

  • TB114.3

表1

弧齿锥齿轮基本参数"

参数名称参数值
齿数比31/26
大端模数/mm8.654
螺旋角/(°)35
压力角/(°)20
轴交角/(°)90
齿高/mm16.746
齿顶高/mm6.44
锥距/mm175.07
传递功率/kW836

表2

弧齿锥齿轮材料参数"

参数名称参数值
密度/104(kg·m-37.83
杨氏模量/1011Pa2.07
泊松比0.29
抗拉强度/MPa1175
屈服强度/MPa1080

表3

不确定性变量参数分布"

变量分布参数变量类型
齿宽b/mmu=52.521,σ=0.03正态分布
转矩T/(N?m)[3580,3660]区间分布
转速n/(r/min-1[2140,2260]区间分布

表4

计算结果"

方法失效概率波动范围
下边界上边界中值偏差耗时/s
本文0.18740.38270.28510.09772.3
MC0.00310.57760.29040.28734.2
SORM0.00510.57180.29040.28343.2
1 于繁华, 刘仁云, 张义民, 等. 机械零部件动态可靠性稳健优化设计的群智能算法[J]. 吉林大学学报: 工学版, 2017, 47(6): 1093-1098.
Yu Fan-hua, Liu Ren-yun, Zhang Yi-min, et al. Swarm intelligence algorithm of dynamic reliability-based robust optimization design of mechanic components[J]. Journal of Jilin University(Engineering and Technology Edition), 2017, 47(6): 1093-1098.
2 李国发, 陈泽权, 何佳龙. 新型结构可靠性分析自适应加点策略[J]. 吉林大学学报: 工学版, 2021: 51(6): 1975-1981.
Li Guo-fa, Chen Ze-quan, He Jia-long. New adaptive sampling strategy for structural reliability analysis[J]. Journal of Jilin University(Engineering and Technology Edition), 2021: 51(6): 1975-1981.
3 Yang X F, Liu Y S, Zhang Y S, et al. Hybrid reliability analysis with both random and probability-box variables[J]. Acta Mechanica, 2015, 226(5): 1341-1357.
4 Hurtado J E, Alvarez D A. The encounter of interval and probabilistic approaches to structural reliability at the design point[J]. Computer Methods in Applied Mechanics and Engineering, 2012, 225: 74-94.
5 Du X P, Sudjianto A, Huang B Q. Reliability-based design with the mixture of random and interval variables[J]. Journal of Mechanical Design, 2005, 127(6): 1068-1076.
6 Guo J, Du X P. Reliability sensitivity analysis with random and interval variables[J]. International Journal for Numerical Methods in Engineering, 2010, 78(13): 1585-1617.
7 Zhang J H, Xiao M, Gao L. A new method for reliability analysis of structures with mixed random and convex variables[J]. Applied Mathematical Modelling, 2019, 70: 206-220.
8 Zhan K, Luo Y. Reliability-based structural optimization with probability and convex set hybrid models[J]. Structural & Multidisciplinary Optimization, 2010, 42(1): 89-102.
9 Yoo D, Lee I. Sampling-based approach for design optimization in the presence of interval variables[J]. Structural & Multidisciplinary Optimization, 2014, 49(2): 253-266.
10 Xie S J, Pan B S, Du X P. A single-loop optimization method for reliability analysis with second order uncertainty[J]. Engineering Optimization, 2015, 47(8): 1125-1139.
11 Wang W, Xue H, Kong T. An efficient hybrid reliability analysis method for structures involving random and interval variables[J]. S tructural and Multidisciplinary Optimization, 2020, 62(1/2): 159-173.
12 Qiu J W, Zhang J G, Ma Y P. Reliability analysis based on the principle of maximum entropy and dempster-shafer evidence theory[J]. Journal of Mechanical Science and Technology, 2018, 32(2): 605-613.
13 Wei G, Di W, Song C, et al. Hybrid probabilistic interval analysis of bar structures with uncertainty using a mixed perturbation Monte-Carlo method[J]. Finite Elements in Analysis & Design,2011,47(7):643-652.
14 Wang X, Lei W, Elishakoff I, et al. Probability and convexity concepts are not antagonistic[J]. Acta Mechanica, 2011, 219: 45-64.
15 Sankararaman S, Mahadevan S. Separating the contributions of variability and parameter uncertainty in probability distributions[J]. Reliability Engineering & System Safety, 2013, 112: 187-199.
16 Yang H J, Li G F, He J L, et al. Accelerated life reliability evaluation of grating ruler for CNC machine tools based on competing risk model and incomplete data[J]. The International Journal of Advanced Manufacturing Technology.DOI: 1007/s00170-021-07627-w.
doi: 1007/s00170-021-07627-w
17 Hurtado J E. Dimensionality reduction and visualization of structural reliability problems using polar features[J]. Probabilistic Engineering Mechanics, 2012, 29(7): 16-31.
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