The remaining useful lifetime (RUL) estimated from the in-situ degradation data has shown
to be useful for online predictive maintenance. In the literature, the RUL is often estimated by …

Remaining useful life (RUL) estimation is regarded as one of the most central components in
prognostics and health management (PHM). Accurate RUL estimation can enable failure …

Predictive maintenance is a promising solution to keep the long-run operation of industrial
systems at high reliability and low cost. In this spirit, we aim to develop an adaptive …

The use of degradation data to estimate the remaining useful life (RUL) has gained great
attention with the widespread use of prognostics and health management on safety critical …

The degradation process of a complex system may be affected by many unknown factors,
such as unidentified fault modes, unmeasured operational conditions, engineering variance …

Product reliability in the field is important for a wide variety of critical applications such as
manufacturing, transportation, power generation, and health care. In particular, the …

Remaining useful life prediction for degrading systems plays a key role in prevalent
prognostics and health management discipline. Compared with the offline remaining useful …

This article addresses the problem of estimating the remaining useful life (RUL) of degrading
products by fusing the accelerated degradation data and condition monitoring (CM) data …

To develop a cost-effective condition-based maintenance strategy, accurate prediction of the
Remaining Useful Life (RUL) is the key. It is known that many failure mechanisms in …

The remaining useful life (RUL) of a system is defined as the length from the current time to
the end of the useful life. The concept of the RUL has been widely used in operational …