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摘要:
针对航天产品小子样、长寿命的特点,提出了基于Bootstrap理论的小子样寿命评估模型。采用B-样条函数构造Bootstrap样本经验分布函数,进行放回抽样。在此基础上,分别采用非参数Bootstrap方法和参数Bootstrap方法建立了寿命评估模型。采用提出的模型对空心阴极循环点火寿命试验数据进行评估,得到多个寿命特征结果,与传统的参数极大似然估计方法的计算结果进行了对比分析,其评估精度满足工程的应用需求,验证了该模型的工程实用性和有效性。
Abstract:This paper proposes a small sample lifetime evaluation model based on Bootstrap method for aerospace products which have the characteristics of small sample and long service life. Using B-spline function as the Bootstrap sample empirical distribution function, a random case sample with replacement is obtained. And on this basis, the lifetime evaluation model is established by using non-parametric Bootstrap method and parametric Bootstrap method respectively. Hollow cathode ignition test data are evaluated based on the proposed method, and multiple lifetime characteristic results are acquired. The results are contrastively analyzed with those concluded by conventional maximum likelihood estimation method of parameters, and it meets the need of the engineering precision, which demonstrates the engineering practicability and effectiveness of the method.
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Key words:
- small sample /
- lifetime evaluation /
- Bootstrap /
- B-spline function /
- empirical distribution function
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表 1 空心阴极点火寿命试验数据
Table 1. Hollow cathode ignition lifetime test data
点火循环模式 点火失效次数 点火成功后工作1 min,关闭冷却20 min 13 957 点火成功后工作1 min,关闭冷却20 min 14 255 点火成功后工作2 h,关闭冷却30 min 13 780 点火成功后工作2 h,关闭冷却30 min 14 576 点火成功后工作2 h,关闭冷却30 min 14 632 表 2 划分点数值和函数值
Table 2. Divide point value and function value
编号 数值 函数F5值 a0 13 780 0 a1 13 822.6 0.096 3 a2 13 865.2 0.192 5 a3 13 907.8 0.233 1 a4 13 950.4 0.269 a5 13 993 0.304 8 a6 14 035.6 0.340 7 a7 14 078.2 0.376 6 a8 14 120.8 0.409 6 a9 14 163.4 0.437 1 a10 14 206 0.464 6 a11 14 248.6 0.492 1 a12 14 291.2 0.519 7 a13 14 333.8 0.547 2 a14 14 376.4 0.574 7 a15 14 419 0.603 7 a16 14 461.6 0.648 9 a17 14 504.2 0.694 1 a18 14 546.8 0.739 3 a19 14 589.4 0.784 5 a20 14 632 1 a21 14 674.6 1 表 3 寿命结果的相对误差
Table 3. Relative error of lifetime results
序号 计算方法 寿命结果 与T相对误差 1 近似的平均寿命 14 240 0 2 传统参数估计 14 242 0.000 14 3 非参数评估模型 14 245 0.000 35 4 参数寿命评估模型 14 260 0.001 3 5 非参数评估模型 (14 006,14 459) (-0.016,0.015) -
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