TY - GEN
T1 - Ridge estimation and principal component analysis to solve an ill-conditioned problem of estimating unmeasured gas turbine parameters
AU - Shevchenko, Maksim
AU - Yepifanov, Sergiy
AU - Loboda, Igor
PY - 2013
Y1 - 2013
N2 - This paper addresses the problem of estimation of unmeasured gas turbine engine variables using statistical analysis of measured data. Possible changes of an engine health condition and lack of information about these changes caused by limited instrumentation are taken into account. Engine thrust is under consideration as one of the most important unmeasured parameters. Two common methods of aircraft gas turbine engine (GTE) thrust monitoring and their errors due to health condition changes are analyzed. Additionally, two mathematical techniques that allow reducing in-flight thrust estimation errors in the case of GTE deterioration are suggested and verified in the paper. They are a ridge trace and a principal component analysis. A turbofan engine has been chosen as a test case. The engine has five measured variables and 23 health parameters to describe its health condition. Measurement errors are simulated using a generator of random numbers with the normal distribution. The engine is presented in calculations by its nonlinear component level model (CLM). Results of the comparison of thrust estimates computed by the CLM and the proposed techniques confirm accuracy of the techniques. The regression model on principal components has demonstrated the highest accuracy.
AB - This paper addresses the problem of estimation of unmeasured gas turbine engine variables using statistical analysis of measured data. Possible changes of an engine health condition and lack of information about these changes caused by limited instrumentation are taken into account. Engine thrust is under consideration as one of the most important unmeasured parameters. Two common methods of aircraft gas turbine engine (GTE) thrust monitoring and their errors due to health condition changes are analyzed. Additionally, two mathematical techniques that allow reducing in-flight thrust estimation errors in the case of GTE deterioration are suggested and verified in the paper. They are a ridge trace and a principal component analysis. A turbofan engine has been chosen as a test case. The engine has five measured variables and 23 health parameters to describe its health condition. Measurement errors are simulated using a generator of random numbers with the normal distribution. The engine is presented in calculations by its nonlinear component level model (CLM). Results of the comparison of thrust estimates computed by the CLM and the proposed techniques confirm accuracy of the techniques. The regression model on principal components has demonstrated the highest accuracy.
UR - http://www.scopus.com/inward/record.url?scp=84890137421&partnerID=8YFLogxK
U2 - 10.1115/GT2013-94496
DO - 10.1115/GT2013-94496
M3 - Contribución a la conferencia
AN - SCOPUS:84890137421
SN - 9780791855188
T3 - Proceedings of the ASME Turbo Expo
BT - ASME Turbo Expo 2013
T2 - ASME Turbo Expo 2013: Turbine Technical Conference and Exposition, GT 2013
Y2 - 3 June 2013 through 7 June 2013
ER -