With the privatization and intense competition that characterize the volatile energy sector,
the gas turbine industry currently faces new challenges of increasing operational flexibility …

Gas-path diagnostics is an essential part of gas turbine (GT) condition-based maintenance
(CBM). There exists extensive literature on GT gas-path diagnostics and a variety of …

In this work, a novel data-driven fault diagnostic framework is developed by using hybrid
multi-mode machine learning strategies to monitor system health status. The coexistence of …

Airbreathing aero-engines are regarded as excellent propulsion devices from ground takeoff
to hypersonic flight, and require control systems to ensure their efficient and safe operation …

In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines
is proposed by developing an ensemble of dynamic neural network identifiers. For health …

Predictive maintenance (PM) strategies are based on real-time data for diagnosis of
impending failure and prognosis of machine health. It is a proactive process, which needs …

The development of an automated health monitoring framework is critical for aviation system
safety, especially considering the expected increase in air traffic over the next decade …

Gas turbines are widely used in power generation. To ensure reliability, data-driven
diagnosis has become increasingly popular. However, sufficient historical data are …

The main goal of this paper is to design and develop a fault detection and isolation (FDI)
scheme for aircraft gas turbine engines by using neural networks. Towards this end, first for …

When using traditional support vector data description (SVDD) to deal with classification
problems, low accuracy is often achieved, especially in the case of noise interference. The …