All Outputs (2)

Deep scattering spectrum germaneness for fault detection and diagnosis for component-level prognostics and health management (PHM). (2022)
Journal Article
ROHAN, A. 2022. Deep scattering spectrum germaneness for fault detection and diagnosis for component-level prognostics and health management (PHM). Sensors [online], 22(23), article 9064. Available from: https://doi.org/10.3390/s22239064

Most methodologies for fault detection and diagnosis in prognostics and health management (PHM) systems use machine learning (ML) or deep learning (DL), in which either some features are extracted beforehand (in the case of typical ML approaches) or... Read More about Deep scattering spectrum germaneness for fault detection and diagnosis for component-level prognostics and health management (PHM)..

Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM). (2022)
Journal Article
ROHAN, A. 2022 Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM). Mathematics [online], 10(12), article number 2031. Available from: https://doi.org/10.3390/math10122031

In the current Industry 4.0 revolution, prognostics and health management (PHM) is an emerging field of research. The difficulty of obtaining data from electromechanical systems in an industrial setting increases proportionally with the scale and acc... Read More about Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM)..