By using in situ health information, many existing studies for online remaining useful life
(RUL) prediction adopt a stochastic process-based degradation model and a computation …

As one of the key technologies to maintain the safety and reliability of stochastic degrading
systems, remaining useful life (RUL) prediction, also known as prognostics, has been …

Multivariate functional principal component analysis (MFPCA) is a widely used tool for
modeling and prognosis of degradation signals. However, MFPCA usually assumes …

This paper proposed a network framework, namely DR-DTPN, which integrates data repair
and degradation trend prediction to address the serious deviation of equipment degradation …

In many applied and industrial settings, the use of Artificial Intelligence (AI) for quality
technology is gaining growing attention. AI refers to the broad set of techniques which …

With the rapid development of sensor and communication technology, multi-sensor data is
available to monitor the degradation of complex systems and predict the failure modes …

The accurate and reliable prediction of remaining useful life (RUL) plays a crucial role in
ensuring the safe operation of batteries. Most existing RUL prediction methods are based on …

This study proposes a method to incorporate covariate information into sparse functional
data analysis. The method aims at cases where each subject has a limited number of …

In order to accurately predict the remaining useful life (RUL) of mechanical equipment under
conditions of missing data, this paper proposes a novel integrated framework for data repair …

Sensors are generally used to monitor the degradation status of various engineering
systems and units. Previous studies have developed parametric models to describe the …