实况下机械零件的动态可靠性分析

doi:10.12068/j.issn.1005-3026.2019.11.012

东北大学学报:自然科学版 ›› 2019, Vol. 40 ›› Issue (11): 1584-1589.DOI: 10.12068/j.issn.1005-3026.2019.11.012

实况下机械零件的动态可靠性分析

杨周¹，姜红猛¹，张义民²，姜超¹

(1. 东北大学机械工程与自动化学院，辽宁沈阳110819; 2. 沈阳化工大学机械工程学院，辽宁沈阳110142)

收稿日期:2019-02-25 修回日期:2019-02-25 出版日期:2019-11-15 发布日期:2019-11-05
通讯作者: 杨周
作者简介:杨周(1979-)，女，辽宁鞍山人，东北大学副教授；张义民(1958-)，男，吉林长春人，沈阳化工大学教授，长江学者特聘教授，博士生导师.
基金资助:
国家自然科学基金资助项目(U1710119).

Dynamic Reliability Analysis of Mechanical Parts Under Actual Operation Conditions

YANG Zhou¹， JIANG Hong-meng¹， ZHANG Yi-min²， JIANG Chao¹

School of Mechanical Engineering & Automation， Northeastern University， Shenyang 110819， China.

Received:2019-02-25 Revised:2019-02-25 Online:2019-11-15 Published:2019-11-05
Contact: JIANG Hong-meng
About author:-
Supported by:
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摘要/Abstract

摘要： 考虑不同工况下载荷变化和强度退化对机械零件可靠性的影响，采用雨流计数法对工况载荷进行统计处理，运用Goodman直线修正法与线性积累损伤法则估计出零件的疲劳寿命.在此基础上，利用等时间段内最大载荷替代载荷变化，Gamma过程模拟强度随机退化的方法来建立渐变可靠性数学模型，最后由随机摄动理论和四阶矩法相结合推导出可靠性灵敏度的表达式.以采煤机扭矩轴为例，估算出扭矩轴在实际载荷下的疲劳寿命，给出各参数变量在疲劳寿命内动态可靠性灵敏度变化规律，分析了参数变量改变对扭矩轴可靠性的影响，并用Monte Carlo仿真进行了验证，结果表明所采用的动态可靠性分析过程符合实际工况，能够为实况下机械零件的动态可靠性分析提供一种方法.

关键词: 机械零件, 疲劳寿命, Gamma过程, 四阶矩, 可靠性灵敏度

Abstract: The fatigue life of the parts were estimated by using the Goodman linear correction method and the linear cumulative damage rule， and the working load was statistically analyzed by the rain flow count method， considering the impact of the load change and the strength degradation on the reliability of mechanical parts. Then， the gradient reliability mathematical model was set up with maximum load in equal time to replace the variable load by using Gamma random process simulating strength degradation. Finally， the expression of reliability sensitivity was derived by stochastic perturbation theory and four rank moment method. The torque shaft of coal mining machine was taken as an example， the fatigue life of the shaft under actual load was estimated and the each parameter variables′ variation rule of dynamic reliability sensitivity during the fatigue life was given. Furthermore， the influence of the parameter variables′ variation on torque shaft reliability was analyzed， and the Monte Carlo simulation method was used to verify the results. All analysis results show that the dynamic reliability analysis process adopted conforms actual working conditions， and can provide a method for dynamic reliability analysis of mechanical parts in real situations.

Key words: mechanical parts, fatigue life, Gamma process, fourth-order moment, reliability sensitivity

中图分类号:

TH133.2

杨周，姜红猛，张义民，姜超. 实况下机械零件的动态可靠性分析[J]. 东北大学学报:自然科学版, 2019, 40(11): 1584-1589.

YANG Zhou， JIANG Hong-meng， ZHANG Yi-min， JIANG Chao. Dynamic Reliability Analysis of Mechanical Parts Under Actual Operation Conditions[J]. Journal of Northeastern University Natural Science, 2019, 40(11): 1584-1589.

参考文献

[1]Ronold K O，Larsen G C.Reliability-based design of wind-turbine rotor blades against failure in ultimate loading［J］.Engineering Structures，1999，22(6):565-574.
[2]Roy D，Dasgupta T.Evaluation of reliability of complex systems by means of a discretizing approach:Weibull set-up［J］.International Journal of Quality & Reliability Management，2002，19(6):792-801.
[3]Wunderle B，Sinning R.Thermo-mechanical reliability during technology development of power chip-on-board assemblies with encapsulation［J］.Microsystem Technologies，2009，15(9):1467-1478.
[4]Tavner P J，Xiang J，Spinato F.Reliability analysis for wind turbines［J］.Wind Energy，2010，10(1):1-18.
[5]Andrieu-Renaud C，Sudret B，Lemaire M.The PHI2 method:a way to compute time-variant reliability［J］.Reliability Engineering & System Safety，2004，84(1):75-86.
[6]Wang Z，Xie L.Dynamic reliability model of components under random load［J］.IEEE Transactions on Reliability，2008，57(3):474-479.
[7]Fang Y，Chen J，Tee K F，et al.Analysis of structural reliability from time response using fully probabilistic［J］.Journal of the Brazilian Society of Mechanical Sciences and Engineering，2014，36(2):277-281.
[8]Huang W，Askin R G.A generalized SSI reliability model considering stochastic loading and strength aging degradation［J］.IEEE Transactions on Reliability，2004，53(1):77-82.
[9]Wang Z，Wei C.Time-variant reliability assessment through equivalent stochastic process transformation［J］. Reliability Engineering & System Safety，2016，152(3):474-479.
[10]Khosrovaneh A K，Dowling N E.Fatigue loading history reconstruction based on the rain flow technique［J］.International Journal of Fatigue，1990，12(2):99-106.
[11]赵少汴.抗疲劳设计［M］.北京:机械工业出版社，1994.(Zhao Shao-bian.Anti-fatigue design［M］.Bejing:China Machine Press，1994.)
[12]王新刚，张义民，王宝艳.机械零部件的动态可靠性灵敏度分析［J］.机械工程学报，2010，46(10):188-193.(Wang Xin-gang，Zhang Yi-min，Wang Bao-yan.Dynamic reliability sensitivity analysis of mechanical components［J］.Journal of Mechanical Engineering，2010，46(10):188-193.)
[13]Noortwijk J M V.A survey of the application of Gamma processes in maintenance［J］.Reliability Engineering & System Safety，2009，94(1):2-21.
[14]安宗文，高建雄，刘波.基于 P-S-N 曲线的强度退化随机模型［J］.计算力学学报，2015，32(1):118-122.(An Zong-wen，Gao Jian-xiong，Liu Bo.Stochastic model of strength degradation based on P-S-N curve ［J］.Chinese Journal of Computational Mechanics，2015，32(1):118-122.)
[15]Birnbaum Z W.On a use of the Mann-Whitney statistic［C］// Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability，1954—1955.Berkeley，1955:13-17.
[16]赵丽娟，李明昊，张品好.采煤机扭矩轴可靠性分析与优化设计［J］.机械强度，2017，39(3):585-591.(Zhao Li-juan，Li Ming-hao，Zhang Pin-hao.Reliability analysis and optimization design of the shearer′s torque shaft［J］.Journal of Mechanical Strength，2017，39(3):585-591.)

实况下机械零件的动态可靠性分析

Dynamic Reliability Analysis of Mechanical Parts Under Actual Operation Conditions

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