Accurate predictions of remaining useful life (RUL) equipment using machine learning (ML) or deep (DL) models that collect data until the fails are crucial for maintenance scheduling. Because unavailable fails, collecting sufficient to train a model without overfitting can be challenging. Here, we propose method generating time-series RUL resolve problems posed by insufficient data. The propose...

The Prognostic and Health Management (PHM) has been developed for more than two decades. It is capable to anticipate the impending failures make decisions in advance extend lifespan of target systems, such as Proton Exchange Membrane Fuel Cell (PEMFC) systems. a critical stage PHM. Among various prognostic methods, data-driven ones could predict system based on device’s knowledge historical dat...