Predictive maintenance is a well studied collection of techniques that aims to prolong the life
of a mechanical system by using artificial intelligence and machine learning to predict the …

The fuel system, which aims to provide sufficient fuel to the engine to maintain thrust and
power, is one of the most critical systems in the aircraft. However, possible degradation …

The increasing complexity of modern aircraft systems necessitates advanced monitoring
solutions to ensure operational safety and efficiency. Traditional aircraft health monitoring …

Remaining useful life predictions depend on the quality of health indicators (HIs) generated
from condition monitoring sensors, evaluated by predefined prognostic metrics such as …

This paper presents a comprehensive survey on interpretable intelligent fault diagnosis for
rotating machinery, addressing the challenge of the “black box” nature of machine learning …

The degradation of aircraft engine performance necessitates real-time monitoring. We
introduce a real-time performance-degradation monitoring method comprising a baseline …

Data-driven condition-based maintenance (CBM) and predictive maintenance (PdM)
strategies have emerged over recent years and aim at minimizing the aviation maintenance …

Deep learning approaches have recently been extensively explored for the prognostics of
industrial assets. However, they still suffer from a lack of interpretability, which hinders their …

For over a century, induction furnaces have been used in the core of foundries for metal
melting and heating. They provide high melting/heating rates with optimal efficiency. The …

In this paper, the use of Deep Neural Net (DNN) to estimate Remaining Useful Life of using
a NASA C-MAPPS dataset training data is explored. The idea is to use DNN and …