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A Study of Online Inspection for Multi-level Prognostics

机译:多层次预测的在线检查研究

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A system's degradation behavior is often correlated with internal and external covariates which are usually difficult to access owing to expensive measurement cost. This paper presents a Particle Filtering based multi-level prognostics approach to predict the Remaining Useful Life of a system based on its State of Health degradation estimation with online inspections of covariates. A degrading system is simulated with covariates at different level. By investigating the covariate online, the degradation estimation shows a better prediction and lower cost than the estimation without inspection.
机译:系统的退化行为通常与由于昂贵的测量成本而难以访问的内部和外部协变量相关。本文介绍了基于粒子滤波的多级预测方法,以预测基于与协变的在线检查的健康退化估计状况的系统剩余使用寿命。利用不同水平的协变量模拟降级系统。通过在线调查协变量,降级估计显示出比没有检查的估计更好的预测和更低的成本。

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