Research on fault diagnosis of gas turbine rotor based on adversarial discriminative domain adaption transfer learning
S Liu, H Wang, J Tang, X Zhang - Measurement, 2022 - Elsevier
In the process of gas turbine rotor fault diagnosis based on data-driven, transfer learning is
an effective method to solve the lack of gas turbines labeled data, which will result in domain …
an effective method to solve the lack of gas turbines labeled data, which will result in domain …
An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines
M Amozegar, K Khorasani - Neural Networks, 2016 - Elsevier
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines
is proposed by developing an ensemble of dynamic neural network identifiers. For health …
is proposed by developing an ensemble of dynamic neural network identifiers. For health …
A review on gas turbine anomaly detection for implementing health management
N Zhao, X Wen, S Li - … : Power for Land, Sea, and Air, 2016 - asmedigitalcollection.asme.org
With the rapid improvement of equipment manufacturing technology and the ever increasing
cost of fuel, engine health management has become one of the most important parts of …
cost of fuel, engine health management has become one of the most important parts of …
Application of selected Levy processes for degradation modelling of long range mine belt using real-time data
D Vališ, D Mazurkiewicz - Archives of civil and mechanical engineering, 2018 - Springer
When analysing big data generated by a typical diagnostic system, the maintenance
operator has to deal with several problems, including a substantial number of data …
operator has to deal with several problems, including a substantial number of data …
Monitoring tool wear using classifier fusion
E Kannatey-Asibu, J Yum, TH Kim - Mechanical Systems and Signal …, 2017 - Elsevier
Real time monitoring of manufacturing processes using a single sensor often poses
significant challenge. Sensor fusion has thus been extensively investigated in recent years …
significant challenge. Sensor fusion has thus been extensively investigated in recent years …
Incremental classifiers for data-driven fault diagnosis applied to automotive systems
One of the common ways to perform data-driven fault diagnosis is to employ statistical
models, which can classify the data into nominal (healthy) and a fault class or distinguish …
models, which can classify the data into nominal (healthy) and a fault class or distinguish …
Generating a virtual physical model through measurement data and reverse engineering: Applying a performance prediction model for an industrial gas turbine during …
S Kim - Applied Thermal Engineering, 2023 - Elsevier
The gas turbine virtual physical model can be applied to various fields such as performance
optimization, diagnostics, and prognostics. For this purpose, it is important to increase the …
optimization, diagnostics, and prognostics. For this purpose, it is important to increase the …
Novel classifier fusion approaches for fault diagnosis in automotive systems
Faulty automotive systems significantly degrade the performance and efficiency of vehicles
and are often major contributors of vehicle breakdown; they result in large expenditures for …
and are often major contributors of vehicle breakdown; they result in large expenditures for …
An integrated health management process for automotive cyber-physical systems
C Sankavaram, A Kodali… - … conference on computing …, 2013 - ieeexplore.ieee.org
Automobile is one of the most widely distributed cyber-physical systems. Over the last few
years, the electronic explosion in automotive vehicles has significantly increased the …
years, the electronic explosion in automotive vehicles has significantly increased the …
Online breakage detection of multitooth tools using classifier ensembles for imbalanced data
A Bustillo, JJ Rodríguez - International Journal of Systems Science, 2014 - Taylor & Francis
Cutting tool breakage detection is an important task, due to its economic impact on mass
production lines in the automobile industry. This task presents a central limitation: real data …
production lines in the automobile industry. This task presents a central limitation: real data …