As one of the key techniques in Prognostics and Health Management (PHM), accurate
Remaining Useful Life (RUL) prediction can effectively reduce the number of downtime …

With advances in sensing and monitoring techniques, real time multi-sensor monitoring data
of stochastic degrading devices has become the reality. How to effectively fuse these multi …

The remaining useful life (RUL) prediction in complex systems is subject to complex working
conditions, such as overloads, random vibration and shocks, gradual corrosion and wearing …

Most prognostics and health management publications focus on the development of
algorithms to monitor and estimate the health condition of individual components. However …

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

With the rapid development of sensor and information technology, now multisensor data
relating to the system degradation process are readily available for condition monitoring and …

Accurate remaining useful life prognosis of bearings in wind turbines is beneficial for
operation and maintenance schedule at wind farms. The major technical challenges include …

Remaining useful life (RUL) prediction is fundamental to prognostics and health
management (PHM). Considering the advantages of both model-based and data-driven …

With the rapid development of Industrial Internet of Things, more and more sensors have
been used for condition monitoring and prognostics of industrial systems. Big data collected …

The single sensor is difficult to acquire the complete degradation information of the
component, and the degradation model cannot adaptively track the staged degradation …