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一种用于随机跳跃的降解过程的剩余有用寿命估计的新方法
Yue Zhuo1, Lei Feng1, Jianxun Zhang1
1Zhijian Laboratory, Rocket Force University of Engineering, Xi'an 710025, China.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
本研究引入了一种新的非均跳转扩散模型,用于预测系统退化和剩余使用寿命 (RUL). 这种先进的方法提供了比现有技术更准确和更强大的RUL估计,改善了预测性维护.
科学领域:
- 工程 工程师 工程师 工程师
- 可靠性工程可靠性工程
- 数据科学数据科学数据科学
背景情况:
- 系统退化可以表现出复杂的行为,包括随机跳跃,影响可靠性.
- 传统模型可能无法准确地捕捉这些非单调的降解模式.
- 准确的剩余使用寿命 (RUL) 估计对于预测性维护和运行安全至关重要.
研究的目的:
- 为具有复杂降解路径的系统引入非均的跳跃扩散过程模型.
- 为准确的降解演变预测和RUL估计开发一个状态空间表示.
- 通过使用真实世界的工业数据来验证拟议模型的有效性.
主要方法:
- 制定一个非均的跳跃扩散过程模型.
- 将其翻译为状态空间模型进行分析.
- 应用蒙特卡洛模拟与颗粒过用于RUL预测.
- 使用最大概率估计 (MLE) 和预期最大化 (EM) 算法进行模型识别.
主要成果:
- 拟议的模型准确地捕捉了降解路径中的随机跳跃.
- 基于颗粒过的蒙特卡洛模拟有效地预测了退化演变.
- 与CNN和LSTM方法相比,该方法提供了更准确和更强大的RUL估计.
- 与高炉壁上的真实世界温度传感器数据的验证证实了有效性.
结论:
- 非均跳转扩散模型为降解系统中的RUL估计提供了优越的方法.
- 这种方法增强了复杂系统的预测性维护策略和运行安全.
- 该研究为分析和预测非单调性降解模式提供了一个强大的框架.
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