Multi-step ahead battery SOC estimation using data-driven prognostics and health management [PDF]
This paper proposes a data-driven multi-step ahead battery state of charge (SOC) forecasting system that can be used for prognostics and health management (PHM) of a battery management system (BMS).
Yu, H., McEwan, A., Pimentel, J.
core +1 more source
Knowledge-based and Expert Systems in Prognostics and Health Management: a Survey
Prognostics and Health Management (PHM) has become increasingly popular in recent years, and data-driven methods and artificial intelligence have emerged as dominant tools within the PHM field.
Forest, Florent, Bouhadra, Kalil
core +1 more source
Expected First Occurrence Time of Uncertain Future Events in One-Dimensional Linear Systems
The rapid advancement of machine learning algorithms has significantly enhanced tools for monitoring system health, making data-driven approaches predominant in Prognostics and Health Management (PHM). In contrast, model-based approaches have seen modest
Acuña Ureta, David Esteban +2 more
core +1 more source
Standards Related to Prognostics and Health Management (PHM) for Manufacturing
Gregory W. Vogl +2 more
openaire +1 more source
A Functional Architecture of Prognostics and Health Management using a Systems Engineering Approach
Prognostic and Health Management (PHM) describes a set of capabilities that enable effective and efficient approaches towards data analysis for fault diagnostics and failure prognostics.
Li, R. +5 more
core
A novel global health index framework for asset prognostics and health management in the oil and gas industry. [PDF]
Alfahdi K, Gultekin H, Summad E.
europepmc +1 more source
Turbofan Engine Remaining Useful Life Prediction with Reliable Prediction Intervals via LSTM-Based Quantile Regression and Conformal Calibration. [PDF]
Diao R, Zhou M, Meng G, Wang S.
europepmc +1 more source
Simulation degradation datasets for health prognosis of a control moment gyroscope's flywheel system. [PDF]
Tang D, Liang S, Han D, Chen B, Yu J.
europepmc +1 more source
A temperature- and impedance-aware LSTM-PINN framework for physically consistent battery SOH prediction. [PDF]
Kumar PN +5 more
europepmc +1 more source

