无失效数据下计算装置贮存寿命评估方法

doi:10.3969/j.issn.1001-506X.2021.01.34

摘要/Abstract

摘要：

针对信息化弹药部组件贮存寿命难以评估的问题,提出了一种融合自然贮存试验数据与加速试验无失效数据的部组件贮存寿命评估方法。首先,根据部组件的自然贮存试验数据,通过保序回归解决数据中的倒挂问题,采用极小卡方估计法和拟合优度检验初步确定部组件的寿命分布函数。接着,通过最优置信限法,估计加速应力水平下的模型参数,并计算加速应力水平与常规应力水平间的加速因子,将加速试验中的无失效数据折算为常规应力水平下的定时截尾数据,单独依据该数据重新评估模型参数。而后,融合折算数据和原始自然贮存数据,再次评估部组件的贮存可靠性,综合对比评估结果确定其分布函数。最后,以某计算装置为例,综合对比分析自然贮存试验数据、加速试验无失效数据和融合贮存试验数据的评估结果,确定了该计算装置的寿命分布函数和给定可靠度下的贮存寿命,证明了该方法的有效性,可以做工程应用推广。

关键词: 计算装置, 无失效数据, 自然贮存试验, 贮存寿命, 最优置信限

Abstract:

Aiming at the problem that it is difficult to evaluate the storage life of informationized ammunition components, a component storage life evaluation method combining natural storage test data and accelerated test zero-failure data is proposed. Firstly, according to the natural storage test data of the component, the upside down problem in the data is solved by the isotonic regression, and the life distribution function of the component is initially determined by the minimum chi-square estimation method and the goodness of fit test. Then, through the optimal confidence limit method, the model parameters under the accelerated stress level are estimated, and the acceleration factor between the accelerated stress level and the conventional stress level is calculated, and the zero-failure data in the accelerated test is converted to the timing censored data under normal stress levels, and the model parameters are re-evaluated based on that data alone. Furthermore, the conversion data and the original natural storage data are combined, and the storage reliability of the components is evaluated again, and the evaluation results are comprehensively compared to determine the distribution function. Finally, taking a computing device as an example, comprehensively comparing and analyzing the evaluation results of natural storage test data, accelerated test no-failure data, and fusion storage test data, the life distribution function of the computing device and the storage life at a given reliability are determined. The effectiveness of this method is proved, which can be used to promote the engineering applications.

Key words: computing device, zero-failure data, natural storage test, storage life, optimal confidence limit

中图分类号:

TJ413.6

赵晓东, 穆希辉. 无失效数据下计算装置贮存寿命评估方法[J]. 系统工程与电子技术, 2021, 43(1): 272-278.

Xiaodong ZHAO, Xihui MU. Evaluation method for storage life of computing devices under zero-failure data[J]. Systems Engineering and Electronics, 2021, 43(1): 272-278.

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贮存时间/月	检测样本数	失效样本数	原始失效比率	倒挂处理
30	P₁	Q₁	0.000 353	0.000 35
33	P₂	Q₂	0	0.000 35
36	P₃	Q₃	0	0.000 35
48	P₄	Q₄	0	0.000 35
54	P₅	Q₅	0.001 081	0.001 1
59	P₆	Q₆	0.001 662	0.001 1
63	P₇	Q₇	0.000 561	0.001 1
74	P₈	Q₈	0.000 867	0.001 1
78	P₉	Q₉	0.000 366	0.001 1
81	P₁₀	Q₁₀	0	0.001 1
85	P₁₁	Q₁₁	0	0.001 1
88	P₁₂	Q₁₂	0.003 080	0.002 8
102	P₁₃	Q₁₃	0.000 411	0.002 8
113	P₁₄	Q₁₄	0.006 179	0.006 2

分布类型	模型参数	可靠寿命
指数分布	χ_0.95²(12)=21.026 χ²统计量:8.374 3 P值:0.755 2 $ \hat \theta = 3\;487.63$	t_0.95=178.892 0
威布尔分布	χ_0.95²(11)=19.675 χ²统计量:3.778 2 p值:0.976 0 $ \hat \eta = 129.027\;9$ $\hat m = 2.110\;8 $	t_0.95=31.591 5
Ⅰ型极大值分布	χ_0.95²(11)=19.675 χ²统计量:2.926 0 P值:0.991 7 $ \hat \mu = 39.620\;6$ $\hat \sigma = 17.860\;3 $	t_0.95=20.024 5
Ⅱ型极大值分布	χ_0.95²(11)=19.675 χ²统计量:8 397.637 P值:0 $ \hat \eta {\rm{ = 5}}{\rm{.153}}\;{\rm{9}}$ $\hat m{\rm{ = 0}} $	无解

分布函数	威布尔分布	Ⅰ型极大值分布
常规应力水平下模型参数	m=2.11 η=129.03 p=0.976 0 t_0.95=31.59	μ=39.62 σ=17.86 p=0.991 7 t_0.95=20.02
100 ℃下模型参数	η_{100 ℃}=1.12	μ_{100 ℃}=3.88
加速因子	K=114.92	K=3.31×10¹⁵

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