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 …

Modern engineering systems are gradually becoming more reliable and premature failure
has become quite rare. As a result, degradation signal data used for prognosis are often …

Reliability of prognostics and health management systems relies upon accurate
understanding of critical components' degradation process to predict the remaining useful …

The remaining useful life (RUL) prediction is critically involved in machinery to ensure safe
and reliable operation. Nevertheless, acquiring the full-cycle degradation data is difficult and …

Degradation is one of the major root causes of system failure. In some applications, the
degradation levels are different upon failure, in which the fixed failure threshold assumption …

Prognostics focuses on predicting the future performance of a system, specifically the time at
which the system no long performs its desired functionality, its time to failure. As an important …

Although the importance of remaining useful life (RUL) prediction is widely recognized in
industries, its implementation in real scenarios is highly restricted by the complexity of 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 …

Remaining useful life (RUL) prediction under time-varying operating conditions is critical to
the prognostics and health management of rotating machinery. In the literature, both the …

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 …