样本数据对舰载机有寿件使用寿命模型的影响分析

张永强; 赵洋; 崔骏夫; 高万春; 李军亮; 马海洋

doi:10.12382/bgxb.2025.0157

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样本数据对舰载机有寿件使用寿命模型的影响分析

更新时间：2026-02-10

- 样本数据对舰载机有寿件使用寿命模型的影响分析
- Influence of Sample Data on Fault Modeling for Service Life-limited Components of Carrier-based Aircraft
- 兵工学报 2025年46卷第S2期页码：250157
- 作者机构：
  
  海军航空大学青岛校区, 山东青岛 266041
- 作者简介：
  
  * 邮箱: wying40852@163.com
- 基金信息：
  
  国家社会科学基金项目(2024-SKJJ-B-027)
- DOI：10.12382/bgxb.2025.0157
  中图分类号：
- 收稿：2025-03-07，
  
  网络首发：2026-02-03，
  
  纸质出版：2025
- 稿件说明：
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张永强, 赵洋, 崔骏夫, 等. 样本数据对舰载机有寿件使用寿命模型的影响分析[J]. 兵工学报, 2025,46(S2):250157.

Yongqiang ZHANG, Yang ZHAO, Junfu CUI, et al. Influence of Sample Data on Fault Modeling for Service Life-limited Components of Carrier-based Aircraft[J]. Acta Armamentarii, 2025, 46(S2): 250157.
张永强, 赵洋, 崔骏夫, 等. 样本数据对舰载机有寿件使用寿命模型的影响分析[J]. 兵工学报, 2025,46(S2):250157. DOI： 10.12382/bgxb.2025.0157.

Yongqiang ZHANG, Yang ZHAO, Junfu CUI, et al. Influence of Sample Data on Fault Modeling for Service Life-limited Components of Carrier-based Aircraft[J]. Acta Armamentarii, 2025, 46(S2): 250157. DOI： 10.12382/bgxb.2025.0157.

摘要

舰载机有寿件控寿时限过短会导致部件效能发挥不足、动用成本高、到寿更换频繁等缺陷

优化控寿时限需要建立准确的使用寿命模型。故障数据与右删失数据是建模的重要样本

当前主流文献隐含2个假设:在故障样本稀疏时

加入右删失数据可提升建模精度;故障样本越多越好

且当故障满足大样本(30个)条件时

右删失数据不再起作用。这些假设缺乏验证

难以针对不同类型的有寿件提供有效指导。对此

结合舰载机有寿件常见的5种寿命分布

基于3组参数分别仿真生成故障样本与不同类型的右删失样本

利用极大似然与AD检验进行参数估计与分布拟合

并将估计与拟合的试验结果与真值比对。试验结论表明:故障样本的最佳收集范围为50~80个;右删失样本在故障满足大样本时仍可提升分布拟合精度;值重复的右删失样本(例如大量的到寿数据)会明显降低分布拟合准确度

因此应避免使用;右删失样本对不同分布参数估计的效果不同

使用时应区别对待。案例比较与分析表明

采用所提方法收集到的样本建模

准确度与误差方面更优

基于模型所优化的控寿时限

可使有寿件的使用效能增加20%

动用成本节省13.3%。

Abstract

The short service life control thresholds for the service life-limited components of carrier-based aircraft result in insufficient performance utilization

high operational costs

and frequent replacements upon reaching their lifespan limits. An accurate service life prediction model needs to be established to optimize the control thresholds. Failure data and right-censored data are essential samples for modeling. Current studies on scheduled replacement strategies for the service life-limited components assume two hypotheses:(1) the right-censored data is added to improves the modeling accuracy only when the failure samples are sparse

and (2) it becomes ineffective when the failure samples reach a threshold (e.g.

30samples). However

these hypotheses lack empirical validation. To address this issue

a lifespan modeling framework integrating failure data and right-censored data (including repeated scheduled replacements) is proposed. Five common lifetime distributions are simulated under three parameter configurations. Distribution parameters are estimated via maximum likelihood estimation (MLE)

and distribution fitting of samples is evaluated using Anderson-Darling (A-D) tests. The experimental results demonstrate that the optimal collection range is 50-80 failure samples; the right-censored data enhances the accuracy of distribution fitting even with sufficient failure samples (>30); the value-repeated right-censored samples (e.g.

excessive scheduled replacement data) significantly degrade the accuracy of distribution fitting; and the efficacy of right-censored data varies across the different distribution parameters—minimal for exponential distributions but critical for log-normal

necessitating distribution-specific utilization strategies. Case studies validate that the models constructed using the proposed data collection framework achieve superior accuracy and lower errors. The utilization efficiency of life-limited components is increased by 20% and the operational cost is reduced by 13.3%by optimizing the scheduled replacement intervals based on these models.

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