Abstract System remaining useful life (RUL) estimation is one of the major prognostic
activities in industrial applications. In this paper, we propose a sensor-based data-driven …

Recent advances in sensing technologies have enabled engineers to collect big data to
predict the remaining useful life (RUL) of complex systems. Current modeling techniques for …

Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …

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

Condition-based maintenance and the prediction of the remaining useful life (RUL) of cutting
tools are of crucial importance to reduce unexpected downtime and ensure quality. Our …

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

Remaining useful life (RUL) is a critical metric in prognostics and health management (PHM)
because it reflects the future health status and fault progression of products. Most RUL …

In prognostics approaches, features (eg, vibration level, root mean square or outputs from
signal processing techniques) extracted from the measurement (eg, vibration, current, and …

Machine performance degradation assessment and remaining useful life (RUL) prediction
are of crucial importance in condition-based maintenance to reduce the maintenance cost …