The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …

Condition monitoring, diagnostics, and prognostics are key factors in today's competitive
industrial sector. Equipment digitalisation has increased the amount of available data …

Aero engine fault diagnosis is very important to ensure flight safety. However, the lack of
fault data limits aero engine fault diagnosis. Fortunately, transfer learning can transfer data …

Flight departure delay prediction is one of the most critical components of intelligent aviation
systems. The accurate prediction of flight departure delays can provide passengers with …

In the present study, the application of a diagnostic method using a physics-based model is
proposed during engine verification testing. A physics-based engine model is constructed …

The scouring process near spur dikes could jeopardize the stability of riverbanks. Thus,
accurate estimation of the maximum scour depth near spur dikes is crucial in river …

At present, aero engine fault diagnosis is mainly based on the steady-state condition at the
cruise phase, and the gas path parameters in the entire flight process are not effectively …

With the development of artificial intelligence, machine learning technique has been applied
in turbomachinery optimization. However, the performance of a classic machine learning …

Abstract Electronic Centralized Aircraft Monitoring (ECAM) parameters play a vital role in the
operation of an aircraft to reduce the workload of the cockpit crew. A wide-body commercial …

The prediction of remaining useful life (RUL) is one of the important measures to ensure the
safety and reliability of mechanical equipment. Aiming at the low accuracy of residual life …