变速箱剩余寿命预测的时间加权核心密度
Weizhen Zhang1, Jianchao Zeng1,2, Hui Shi3
1School of Electronic and Information Engineering, Taiyuan University of Science and Technology, Taiyuan, 030024, China.
Scientific reports
|March 25, 2025
概括
准确的变速箱剩余使用寿命预测对于工业自动化至关重要. 这项研究引入了一种新的时间变化的内核密度估计 (KDE) 方法,比现有模型提高了预测准确度.
科学领域:
- 机械工程 机械工程
- 可靠性工程可靠性工程
背景情况:
- 变速箱的可靠性对于工业自动化系统至关重要.
- 由于复杂的环境和有限的故障数据,预测轮箱剩余的使用寿命具有挑战性.
- 现有的方法经常受到不准确的模型和参数估计的影响.
研究的目的:
- 分析时间变化的内核密度估计 (KDE) 对变速箱剩余使用寿命预测的影响.
- 开发一种更准确,更强大的方法来预测变速箱退化.
主要方法:
- 建立了一个具有时间变化的KDE模型,包含增量退化功能和样本时间.
- 用指数加权移动平均值进行退化样本预测.
- 利用递归更新来优化时间变化的重量和内核密度估计.
主要成果:
- 提出的时间变化的KDE方法在剩余的使用寿命预测方面表现出卓越的性能.
- 与DGN和Ensemble模型相比,实现了较低的根平均平方误差 (RMSE) 和平均绝对误差 (MAE).
- 使用现实世界变速箱运行数据验证了适应性和有效性.
结论:
- 开发的可变时间的KDE方法为变速箱剩余使用寿命预测提供了更高的准确性.
- 该方法解决了现有模型的局限性,特别是数据稀缺性和动态条件.
- 这些发现有助于提高工业自动化中的可靠性和维护策略.
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