航空学报 > 2022, Vol. 43 Issue (9): 225914-225914   doi: 10.7527/S1000-6893.2022.25914

考虑随机冲击影响的自适应Wiener过程剩余寿命预测方法

董青1, 郑建飞1, 胡昌华1, 余铜辉2, 牟含笑1   

  1. 1. 火箭军工程大学 导弹工程学院, 西安 710025;
    2. 火箭军驻西安地区第一军事代表室, 西安 710100
  • 收稿日期:2021-06-07 修回日期:2021-07-16 出版日期:2022-09-15 发布日期:2022-09-30
  • 通讯作者: 郑建飞,E-mail:zjf302@126.com E-mail:zjf302@126.com
  • 基金资助:
    国家自然科学基金(61773386, 61833016, 61922089, 62073336);陕西省自然科学基金(2020JM-360)

Remaining useful life prediction for adaptive Wiener process method with random shock

DONG Qing1, ZHENG Jianfei1, HU Changhua1, YU Tonghui2, MU Hanxiao1   

  1. 1. College of Missile Engineering, Rocket Force University of Engineering, Xi'an 710025, China;
    2. The First Military Representative Office of the Rocket Force in Xi'an, Xi'an 710100, China
  • Received:2021-06-07 Revised:2021-07-16 Online:2022-09-15 Published:2022-09-30
  • Supported by:
    National Natural Science Foundation of China (61773386, 61833016, 61922089, 62073336); National Natural Science Foundation of Shaanxi Province (2020JM-360)

摘要: 现有针对存在随机冲击影响的退化设备剩余寿命预测(RUL)方法, 不适用于退化设备测量间隔分布不均匀、监测数据的测量频率与历史数据频率不一致的情况, 并且未考虑将来退化过程中自适应漂移的可变性。鉴于此, 基于自适应Wiener过程, 提出了一种考虑随机冲击影响的非线性退化设备剩余寿命预测方法。首先, 利用正态分布描述随机冲击对设备退化量的影响, 建立融合随机冲击影响的自适应Wiener过程退化模型, 推导出首达时间意义下剩余寿命的解析表达式。然后, 通过考虑退化漂移可变性和随机冲击对退化率的影响, 构建出状态空间模型实现设备剩余寿命在线更新, 并应用期望最大化方法实现模型参数估计。最后, 通过数值仿真以及惯性导航系统陀螺仪、锂电池2个实例, 从不同角度验证了所提方法的有效性和实用性。

关键词: 随机冲击, 自适应Wiener过程, 正态分布, 期望最大化, 剩余寿命预测

Abstract: The existing method for predicting the Remaining Useful Life (RUL) of the degraded equipment with random shock is not suitable for the situation with uneven measurement intervals and inconsistent measurement frequencies. This type of method also ignores the variability of adaptive drift in the future degradation process. In view of this, based on the adaptive Wiener process, this paper proposes a RUL prediction method for the non-linearly degraded equipment with random shock. Firstly, the normal distribution is used to describe the influence of random shock on equipment degradation, and an adaptive Wiener process degradation model considering random shock is established. Then, the analytical expression of RUL is derived in the sense of the first arrival time. Considering the variability of degradation drift and the influence of random impact on the degradation rate, a state space model is developed to realize online update of equipment RUL, and the model parameter estimation is conducted based on expectation maximization algorithm. Finally, numerical simulation, inertial navigation system gyroscope and lithium battery examples verify the effectiveness and practicability of the proposed method from different angles.

Key words: random shock, adaptive Wiener process, normal distribution, expectation maximization, remaining useful life

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