Contending Remaining Useful Life Algorithms



Published Nov 3, 2020
Eric Bechhoefer Marc Dube


Operational readiness, reliability and safety are all enhanced through condition monitoring. That said, for many assets, there is still a need for a prognostic capability to calculate remaining useful life (RUL). RUL allows operation and maintenance personnel to better schedule assets, and logisticians to order long lead time part to help improve balance of plant/asset availability. While a number of RUL techniques have been reported, we have focused on fatigue crack growth models (as opposed to physics or deep learning of based models). This paper compares the performance of stress intensity models (linear elastic model, e.g. Paris’ Law), to Head’s theory (geomatical similarity hypothesis) and to Dislocation/Energy theories of crack growth. It will be shown that these models differ mainly in the crack growth exponent, and that this leads to large differences in the estimation of RUL during early state fault propagation, though the results of all three models converge as the RUL is shorted.

How to Cite

Bechhoefer, E., & Dube, M. (2020). Contending Remaining Useful Life Algorithms. Annual Conference of the PHM Society, 12(1), 9.
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RUL, Diagnstics, Condition Based Maintenance, HUMS

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