… learning (ML) in the past years has opened up new opportunities to the field of gas turbine
(GT) … An important tool for enabling applications are the feature selection and feature learning (…

… A gas turbine trip is … learning models able to predict gas turbine trip requires the definition
of a set of target data and a procedure of feature engineering that improves machine learning …

… of gas turbine condition monitoring, diagnostics, and prognostics using machine-learning …
The initial search query was: “gas turbine” AND (“soft sensor” OR “machine learning” OR “…

… -world gas turbine combustion system, we demonstrated that the proposed deep learning
based … To demonstrate effectiveness of unsupervised feature learning for combustor anomaly …

… Therefore, the applied transfer learning methods do not fully consider the feature … , a
feature adaptive transfer learning method focusing on the dynamic simulation of the gas turbine …

… based on conventional machine learning techniques has been … a transfer learning based
extreme learning machine to align the … of learning the transferable cross domain features while …

Gas turbine (GT) fault detection plays a vital role in the minimization of power plant operation
costs associated with power plant overhaul time intervals. In other words, it is helpful in …

… By looking at the enhanced data, we will also have better understanding of whether
additional sensors in the gas turbine can help in future machine learning algorithms. …

… the gas turbine system. In this paper, the Lab-scale rotor test device is simulated by a gas
turbine, … occurred from a gas turbine critical fault mode. In addition, blade rubbing is one of the …

… of gas turbine engines. In recent years, the rapid development and intense competition of the
gas turbine … This study proposes a transfer-learning based gas path analysis method. The …