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Chinese Journal of Engineering Design  2026, Vol. 33 Issue (3): 377-389    DOI: 10.3785/j.issn.1006-754X.2026.05.203
Reliability and Quality Design     
Reliability analysis of aviation equipment MFOP considering probability-interval hybrid uncertainty
Ruping WANG1(),Tenghao BI2,3,Lihua MENG1,Fawu XIANG1,Chongshuai WANG2,3()
1.China Aero-Polytechnology Establishment, Beijing 100028, China
2.School of Electrical Engineering, Hebei University of Technology, Tianjin 300401, China
3.National Key Laboratory of Smart Power Distribution and Utilization Equipment and Systems, Tianjin 300401, China
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Abstract  

Based on the reliability analysis of aviation equipment with maintenance-free operating period (MFOP), the fault-free operation ability and task completion rate of the equipment can be improved by rationally planning the maintenance intervals. At present, the calculation of MFOP reliability indicators only considers the random uncertain factors based on specific distributions. However, for complex aviation equipment systems, it is difficult to obtain sample data of some uncertain factors, making it impossible to accurately establish probability distributions. Moreover, the reliability results obtained based on the ideally assumed probability distributions entail substantial deviations. Therefore, the probability-interval hybrid uncertainty was introduced into the MFOP reliability analysis framework. For the uncertain factors with sufficient sample sizes, they were characterized in a probabilistic way; for the uncertain factors with scarce sample sizes, they were characterized in an interval way. At the same time, taking into account the correlations among uncertain factors, a reliability analysis method for aviation equipment systems considering multi-source uncertainty was proposed. Finally, through an analytical example with four uncertain parameters and an engineering example of the water-landing airbag buffer system for aviation equipment involving six uncertain parameters, the effectiveness of the proposed method was verified. The research results provide a theoretical basis for maintenance decisions of aviation equipment.



Key wordshybrid uncertainty      reliability      maintenance-free operating period      aviation equipment     
Received: 24 September 2025      Published: 27 June 2026
CLC:  V 267  
Corresponding Authors: Chongshuai WANG     E-mail: Wangruping724@163.com;wangchongshuai@hebut.edu.cn
Cite this article:

Ruping WANG,Tenghao BI,Lihua MENG,Fawu XIANG,Chongshuai WANG. Reliability analysis of aviation equipment MFOP considering probability-interval hybrid uncertainty. Chinese Journal of Engineering Design, 2026, 33(3): 377-389.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2026.05.203     OR     https://www.zjujournals.com/gcsjxb/Y2026/V33/I3/377


考虑概率-区间混合不确定性的航空装备MFOP可靠性分析

基于无维修工作期(maintenance-free operating period, MFOP)的航空装备可靠性分析,可通过合理规划维修间隔时间实现装备无故障运行能力及任务完成率的提升。目前,MFOP可靠性指标的计算仅考虑基于特定分布的随机不确定因素。然而,对于复杂的航空装备系统,部分不确定因素的样本数据获取困难,无法准确构建概率分布,而基于理想设定的概率分布得到的可靠性结果偏差较大。为此,将概率-区间混合不确定性引入MFOP可靠性分析框架。针对样本充足的不确定因素,以概率方式表征;针对小样本量的不确定因素,以区间方式表征。同时,考虑不确定因素之间的相关性,提出了一种考虑多源不确定性的航空装备系统可靠性分析方法。最后,通过包含4个不确定参量的解析算例和包含6个不确定参量的航空装备水上降落气囊缓冲系统工程算例,验证了所提出方法的有效性。研究结果为航空装备的维修决策提供了理论依据。


关键词: 混合不确定性,  可靠性,  无维修工作期,  航空装备 
参量名称分布类型工程意义
材料抗拉强度正态分布制造工艺偏差和材料批次波动导致抗拉强度随机变化
充气速率对数正态分布阀门精度和流体特性引起的非线性随机波动
环境温度区间分布极端气候或任务区域温度变化,缺乏精确统计分布
工作压力区间分布传感器测量误差或工况波动导致的压力范围不确定性
Table 1 Common uncertain parameters of airbag buffer system
Fig.1 Process for formulating MFOP maintenance plans of aviation equipment considering probability-interval hybrid uncertainty
变量参数1参数2分布类型
X101正态分布
X201正态分布
Y1-11区间分布
Y2-11区间分布
Table 2 Distribution parameters and distribution types of uncertain parameters in analytical example
Fig.2 Distribution of sample points for uncertain parameters in analytical example
Fig.3 Distribution of target values in analytical example
Fig.4 Variation trend of failure probability with correlation coefficient of probability variables in analytical example
Fig.5 Variation trend of failure probability with correlation coefficient of interval variables in analytical example
Fig.6 Variation trend of MFOP with correlation coefficient of probability variables in analytical example (exponential distribution)
Fig.7 Variation trend of MFOP with correlation coefficient of interval variables in analytical example (exponential distribution)
Fig.8 Variation trend of MFOP with correlation coefficient of probability variables in analytical example (Weibull distribution)
Fig.9 Variation trend of MFOP with correlation coefficient of interval variables in analytical example (Weibull distribution)
分析方法失效概率MFOP/年
本文方法[0.089, 0.188][0.319, 1.087]
纯概率法0.1410.712
独立变量法[0.075, 0.210][0.280, 1.150]
椭球模型法[0.087, 0.186][0.314, 1.082]
Table 3 Comparison of calculation results of various methods in analytical example
Fig.10 Schematic diagram of airbag buffer system
Fig.11 Buffer airbag model
变量单位参数1参数2分布类型
XrMPa1206正态分布
Xvm3·s-140.1对数正态分布
YTK253298区间分布
YPMPa0.81.2区间分布
ZVm32.5
ZL0.75
Table 4 Distribution parameters and distribution types of uncertain parameters in airbag buffer system
参量组合相关性类型相关性影响
XrXv概率变量-概率变量充气速率升高会引发气囊内部动态载荷增大,材料抗拉强度须匹配高速充气下的瞬时应力峰值,以避免撕裂
YTYP区间变量-区间变量在气囊体积和充气量受限的条件下,温度升高会导致气体压力升高,同时高温可能会触发安全泄压机制,以限制压力失控风险
Table 5 Correlation between uncertain parameters in airbag buffer system
Fig.12 Distribution of sample points for uncertain parameters in airbag buffer system
Fig.13 Distribution of airbag deployment time
Fig.14 Variation trend of airbag failure probability with correlation coefficient of probability variables
Fig.15 Variation trend of airbag failure probability with correlation coefficient of interval variables
Fig.16 Variation trend of airbag MFOP with correlation coefficient of probability variables (exponential distribution)
Fig.17 Variation trend of airbag MFOP with correlation coefficient of interval variables (exponential distribution)
分析方法失效概率MFOP/年计算时间/s
本文方法[0.029 7, 0.115 2][0.227, 0.011]4.765
纯概率法0.068 40.5494.346
独立变量法[0.024 3, 0.126 8][0.195, 1.134]2.431
椭球模型法[0.035 8, 0.108 5][0.261, 0.972]3.783
Table 6 Comparison of calculation results of various methods in engineering example
 
 
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