Future trends in engine health management (EHM) systems are information fusion,
advanced analytical methods, and the concept of the Intelligent Engines. Machine Learning …

Abstract Recently Micro Gas Turbines deployment in smart grids is growing, which increases
engine load change during its lifecycle; consequently, lifetime reduces faster, and …

In this paper, a Fault Detection and Isolation (FDI) system based on an ensemble-based
hierarchical classifier is devised to detect and isolate twelve typical turbine faulty scenarios …

In the field of gas turbine (GT) monitoring and diagnostics, GT trip is of great concern for
manufactures and users. In fact, due to the number of issues that may cause a trip, its …

This paper presents a methodology for predictive and prescriptive analytics of a gas turbine.
The methodology is based on a combination of physics-based and data-driven modeling …

A diagnostic method for gas-path faults of turbofan engines, relying on a Probabilistic Neural
Network (PNN) coupled with a thermodynamic model of the engine, is presented. The novel …

Software for the simulation of the transient behavior of natural gas pipelines commercially
available, however, due to their high computational demands, they do not allow real time …

In recent years, more and more attention has been paid to the use of artificial neural
networks (ANN) for the diagnostics of gas pumping units (GPU). Usually, ANN training is …

This paper covers three contemporary topics in the development and deployment of
machine learning based diagnostics for large fleets of industrial machines. First, we address …

This chapter proposes a methodology for building hybrid models of gas turbine power plants
for solving the task of prescriptive and predictive plant health analytics. The hybrid models …