结构在线损坏识别和动态可靠性预测方法基于无气味卡尔曼波器
Yan Zhang1, Yongbo Zhang1,2, Jinhui Yu1
1School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
这项研究引入了一种新的结构健康监测方法,使用无臭卡尔曼波器 (UKF) 实时识别损坏并预测系统可靠性.
科学领域:
- 结构工程 结构工程
- 可靠性工程可靠性工程
- 信号处理 信号处理
背景情况:
- 传感器技术的进步使得结构性在线监控成为可能.
- 在实时损坏诊断和动态可靠性预测方面仍然存在挑战.
研究的目的:
- 开发一种在线结构损坏识别方法.
- 为结构实现准确的实时动态可靠性预测.
主要方法:
- 使用无气味卡尔曼波器 (UKF) 来识别结构损坏.
- 使用预期最大化 (EM) 算法进行性能模型参数估计.
- 实现了动态可靠性预测的条件概率.
主要成果:
- 拟议的方法准确地识别了在运行过程中结构损坏的状态.
- 实现精确,实时和动态可靠性预测.
- 在具有随机效应的维纳降解过程中证明有效性.
结论:
- 基于UKF的方法增强了结构性健康管理.
- 为评估结构完整性和预测未来性能提供可靠的工具.
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