基于贝叶斯框架的时变漂移核滤波剩余寿命预测

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振动与冲击 ›› 2025, Vol. 44 ›› Issue (12) : 249-258.

故障诊断分析

基于贝叶斯框架的时变漂移核滤波剩余寿命预测

梁雅琴，白洁，石慧*，李丽君，李哲昊

作者信息 +

Remaining useful life prediction of time-varying drift kernel filter based on Bayesian framework

LIANG Yaqin,BAI Jie,SHI Hui*,LI Lijun,LI Zhehao

Author information +

文章历史 +

摘要

动态运行环境使得系统退化过程复杂多变，降低系统剩余寿命预测准确性，为确保部件在实际运行中的可靠性评估，本文提出了一种基于贝叶斯框架的时变漂移核滤波方法。首先，采用Wiener模型描述系统退化过程，通过多源映射函数构建状态空间方程。其次，提出贝叶斯突变点检测法确定突变点位置，采用漂移核滤波算法根据先验知识更新状态粒子的后验概率，并自适应分配权重，在突变点前后选择不同核函数进行粒子重采样并估计其分布，提高预测精度。最后，通过C-MAPSS数据集验证了该方法的优越性。

Abstract

In the context of life prediction for components, dynamic environments complicate the degradation process. To ensure the reliability of components during actual operation, a time-varying drift kernel filter based on Bayesian framework is proposed in time-varying operating environment. Firstly, the Wiener model is employed to characterize the degradation process, and the state space equation is constructed utilizing the multi-source mapping function. Next, the Bayesian online mutation point detection is employed, utilizing prior knowledge to predict and update the posterior probability of particles to determine the location of the mutation point. Then, the drift kernel filter is used to adaptively allocate weights and select different kernel functions for particle resampling before and after change points. This approach enhances prediction accuracy. Finally, the effectiveness of the drift kernel filter is verified through the C-MAPSS dataset.

导出引用

梁雅琴, 白洁, 石慧, 李丽君, 李哲昊. 基于贝叶斯框架的时变漂移核滤波剩余寿命预测[J]. 振动与冲击, 2025, 44(12): 249-258

LIANG Yaqin, BAI Jie, SHI Hui, LI Lijun, LI Zhehao. Remaining useful life prediction of time-varying drift kernel filter based on Bayesian framework[J]. Journal of Vibration and Shock, 2025, 44(12): 249-258

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