Calibration uncertainty estimation for internal aerodynamic balance


Autoria(s): Reis, M. L C C; Castro, R. M.; Falcão, J. B P F; Barbosa, I. M.; Mello, O. A F
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

01/12/2008

Resumo

Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

Formato

185-190

Identificador

Proceedings of the 12th IMEKO TC1 Education and Training in Measurement and Instrumentation and TC7 Measurement Science Joint Symposium on Man, Science and Measurement 2008, p. 185-190.

http://hdl.handle.net/11449/70849

2-s2.0-84872539184

Idioma(s)

eng

Relação

Proceedings of the 12th IMEKO TC1 Education and Training in Measurement and Instrumentation and TC7 Measurement Science Joint Symposium on Man, Science and Measurement 2008

Direitos

closedAccess

Palavras-Chave #Calibration uncertainty #Internal strain-gage balance #Wind tunnel tests #Applied loads #Calibration coefficients #Calibration data #Goodness of fit #Least squares methods #Load components #Multicomponents #Multivariate polynomial #Sensor response #Calibration #Data reduction #Estimation #Least squares approximations #Measurements #Sensors #Wind tunnels #Aerodynamics
Tipo

info:eu-repo/semantics/conferencePaper