Prognostics, the ability to predict remaining useful life of a flight critical component is not clearly defined in current health and usage monitoring system (HUMS). As a consequence, the present use of HUMS is limited to just altering maintainers of impending fault. A HUMS with enhanced prognostic capability that can reliably estimate the remaining useful life of flight critical components is needed to lower maintenance costs, improve operational readiness, and reduce logistics footprint. Over the past few years, a few prognostic algorithms have been developed and tested using HUMS monitoring data. A common limitation of these methods is that they are all data-driven approaches and their data requirement for training is intensive. This can be problematic for helicopter transmissions, which are for the most part, very reliable. It is unlikely that there will be training data for every component in the drive train. The method presented in this paper is physics-based and therefore overcomes the limitation of data-driven prognostic algorithms. The application feasibility of the physics-based approach to enhance HUMS prognostic capability is demonstrated with a shaft prognosis case study.
展开▼
