对于具有年龄和状态依赖的跳转扩散过程的退化系统的剩余使用寿命预测
Bincheng Wen1, Mingqing Xiao1, Xilang Tang2
1ATS Lab, Air Force Engineering University, 710038 Xi'an, China.
ISA transactions
|December 26, 2024
概括
准确的剩余使用寿命 (RUL) 预测需要考虑系统年龄,操作条件和环境变化. 本研究引入了一个新模型,将这些因素考虑在内,以提高RUL估计的准确性.
科学领域:
- 预测和健康管理 (PHM)
- 可靠性工程可靠性工程
- 随机过程 随机过程
背景情况:
- 预测剩余使用寿命 (RUL) 对于系统维护和运营规划至关重要.
- 现有的降解模型往往忽略了状态依赖性和环境跳跃效应,限制了RUL的准确性.
- 准确的RUL估计需要整合年龄,状态和环境因素的模型.
研究的目的:
- 提出一个一般化的年龄状态依赖跳转扩散 (ASDJD) 模型,以提高RUL估计.
- 通过结合年龄依赖,状态依赖和退化跳跃来解决现有模型的局限性.
- 为预测系统寿命提供更强大的框架.
主要方法:
- 发展了年龄状态依赖的跳转扩散 (ASDJD) 模型.
- 使用首次撞击时间 (FHT) 来推导RUL分布的近似分析表达式.
- 使用预期条件最大化 (ECM) 和最大概率估计 (MLE) 进行参数估计.
主要成果:
- 拟议的ASDJD模型有效地解释了年龄依赖,状态依赖和退化跳跃.
- 使用模拟和现实世界轴承数据集的验证证实了该模型的有效性.
- 该研究证明了国家依赖的重大影响,并对RUL估计准确度进行了跳跃.
结论:
- 国家依赖和环境跳跃是必须包含在RUL估计中的关键因素.
- 拟议的ASDJD模型为复杂系统中的RUL预测提供了更全面的方法.
- 这项研究通过改进的退化建模,有助于推进预后和健康管理领域.
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