TY - JOUR
T1 - Estimation of Gas Turbine Unmeasured Variables for an Online Monitoring System
AU - Loboda, Igor
AU - Miró Zárate, Luis Angel
AU - Yepifanov, Sergiy
AU - Maravilla Herrera, Cristhian
AU - Pérez Ruiz, Juan Luis
N1 - Publisher Copyright:
© 2018 Walter de Gruyter GmbH, Berlin/Boston.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - One of the main functions of gas turbine monitoring is to estimate important unmeasured variables, for instance, thrust and power. Existing methods are too complex for an online monitoring system. Moreover, they do not extract diagnostic features from the estimated variables, making them unusable for diagnostics. Two of our previous studies began to address the problem of "light"algorithms for online estimation of unmeasured variables. The first study deals with models for unmeasured thermal boundary conditions of a turbine blade. These models allow an enhanced prediction of blade lifetime and are sufficiently simple to be used online. The second study introduces unmeasured variable deviations and proves their applicability. However, the algorithms developed were dependent on a specific engine and a specific variable. The present paper proposes a universal algorithm to estimate and monitor any unmeasured gas turbine variables. This algorithm is based on simple data-driven models and can be used in online monitoring systems. It is evaluated on real data of two different engines affected by compressor fouling. The results prove that the estimates of unmeasured variables are sufficiently accurate, and the deviations of these variables are good diagnostic features. Thus, the algorithm is ready for practical implementation.
AB - One of the main functions of gas turbine monitoring is to estimate important unmeasured variables, for instance, thrust and power. Existing methods are too complex for an online monitoring system. Moreover, they do not extract diagnostic features from the estimated variables, making them unusable for diagnostics. Two of our previous studies began to address the problem of "light"algorithms for online estimation of unmeasured variables. The first study deals with models for unmeasured thermal boundary conditions of a turbine blade. These models allow an enhanced prediction of blade lifetime and are sufficiently simple to be used online. The second study introduces unmeasured variable deviations and proves their applicability. However, the algorithms developed were dependent on a specific engine and a specific variable. The present paper proposes a universal algorithm to estimate and monitor any unmeasured gas turbine variables. This algorithm is based on simple data-driven models and can be used in online monitoring systems. It is evaluated on real data of two different engines affected by compressor fouling. The results prove that the estimates of unmeasured variables are sufficiently accurate, and the deviations of these variables are good diagnostic features. Thus, the algorithm is ready for practical implementation.
KW - deviations
KW - gas turbine
KW - monitoring
KW - unmeasured variables
UR - http://www.scopus.com/inward/record.url?scp=85043780176&partnerID=8YFLogxK
U2 - 10.1515/tjj-2017-0065
DO - 10.1515/tjj-2017-0065
M3 - Artículo
SN - 0334-0082
VL - 37
SP - 413
EP - 428
JO - International Journal of Turbo and Jet Engines
JF - International Journal of Turbo and Jet Engines
IS - 4
ER -