Abstract In context of industry 4.0, intelligent manufacturing and maintenance play a
significant role. The fault detection and diagnosis (FDD) of industrial gas turbine (IGT) …

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 …

There are many challenges against an accurate gas turbine fault diagnostics, such as the
nonlinearity of the engine health, the measurement uncertainty, and the occurrence of …

Nowadays, renewable energy has been emerging as the major source of energy and is
driven by its aggressive expansion and falling costs. Most of the renewable energy sources …

The major challenges faced by the gas turbine industry, for both the users and the
manufacturers, is the reduction in life cycle costs, as well as the safe and efficient running of …

Fault diagnosis plays a significant role in conducting condition-based maintenance and
health management for gas turbines (GTs) to improve reliability and reduce costs. Various …

When a robust mathematical model of a process equipment is available, model-based
diagnostic methods can be used to identify the occurrence of faults in a system. However …

An effective and reliable gas path diagnostic method that could be used to detect, isolate,
and identify gas turbine degradations is crucial in a gas turbine condition-based …

Multi-sensor measurement is widely employed in rotating machinery to ensure the safety of
machines. The information provided by the single sensor is not comprehensive. Multi-sensor …

The fault diagnosis of gas turbines plays a vital role in engine reliability and availability. The
data-driven diagnostic model has been verified useful for identifying and characterizing …