EGT Prediction of a Micro Gas Turbine Using Statistics and Artificial Intelligence Approach

被引:18
作者
Koleini, Iman [1 ]
Roudbari, Alireza [2 ]
Marefat, Vahid [3 ]
机构
[1] Univ Tehran, Fac New Sci & Technol, Tehran, Iran
[2] Shahid Sattari Aeronaut Univ Sci & Technol, Dept Aeronaut Engn, Tehran, Iran
[3] Urmia Univ Technol, Dept Mech Engn, Orumiyeh, West Azerbaijan, Iran
关键词
NEURAL-NETWORK; PERFORMANCE; MODEL; ENGINE;
D O I
10.1109/MAES.2018.170045
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Small size gas turbine application has increased with the advancement of technology. These engines have simple structures, fewer number of operating components, and less design and construction costs in comparison with large gas turbines. Small size gas turbines can be used in different fields such as remotely piloted vehicles, unmanned aerial vehicles, helicopters, and special purpose aircraft such as vertical takeoff and landing aircrafts [1]. The advantages of these engines compared to the large gas turbine engines leads to high usage of small-sized engines and growing demand for research activities and experimental test results on the operating parameters of these engines, such as exhaust gas temperature (EGT). In general, research on gas turbine engines, related with the present work, can be divided into two parts. The first part includes studies about past experiments and modeling of gas turbine engines, and the second part focuses on data mining methods applied on gas turbine engines. These two areas are discussed in the following sections. © 1986-2012 IEEE.
引用
收藏
页码:4 / 13
页数:10
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