The domain discrepancy caused by power level gap between training set (source domain)
and test set (target domain) limits the generalization of data-driven models in practical …

This paper investigates various types of faults in District Heating & Cooling (DHC) systems.
Many authors point out that the lack of data hinders the development of good data-driven …

In recent years there has been a growing interest in gas turbine fault diagnosis, especially
under dynamic conditions, due to the evolving operating profile of gas turbines and the need …

Abstract As an Open Set Recognition (OSR) problem, nuclear power plant fault diagnosis
requires not only the correct classification of known faults, but also the effective identification …

Natural gas-fired combined cycle unit is appropriate alternative of coal-fired unit for clean
power generation. To address the dramatic nonlinearity, strong coupling and observable …

Process monitoring is important for ensuring industrial production safety. If faults are
detected in time, maintenance plan will be made to avoid economic losses. Traditional …

Improving the accuracy of gas turbine performance diagnosis is important for reducing
maintenance costs. Conventional model-based diagnostics use either compressor map …

The unpredictable flame-out may occur due to various factors such as weather conditions
and bird strikes. After flame-out, the engine should undergo a challenging and risky restart …

Machine learning models have been used to precisely forecast emissions from diesel
engines, specifically examining the impact of various fuel types (HVO10, HVO 30, HVO40 …

To solve the difficult problem of selecting initial guess values for component-level aero-
engine start-up models, a novel method based on the flow-based back-calculation algorithm …