Modeling of Remaining Useful Life for Prognostics and Systems Health Management
DescriptionCurrent methods for reliability assessment of complex systems have fundamental flaws, due to their inability to keep pace with new technologies, to account for complex usage profiles, and to address intermittent faults. Intermittent failures are often difficult to predict and may not be repeatable, and thus are often recurrent and lead to "no-fault found" diagnostic conclusions. The proposed research approach is a radically new approach which builds upon prognostics and system health management (PHM) methodologies with the integration of failure time and degradation data and physics of failure knowledge. In particular, we will develop new classes of integrated models that combine failure time and degradation data together with dynamic environment information to predict malfunctions and remaining useful life for complex systems with intermittent failures. The proposed research methods will be transferrable to a wide range of complex systems, including electronic-rich systems, critical automotive components, and power systems etc.
|Effective start/end date||1/10/13 → 26/03/15|