Application of global regression method for calibration of wind tunnel balances

Aerodynamic forces and moments on scaled models are measured in wind tunnels by multi-component strain gauge\ud balances whose performance and accuracy are characterized by careful calibrations. It is well recognized that calibration loads that are representative of the combined loads experienced by the balance/model in wind tunnel test conditions lead to high accuracy of the measured loads. But, in the traditional method the calibration loads are restricted to single-component and two component loads that are unrepresentative of model loads. A recently developed method called Global Regression Method (GRM)places no such restrictions and therefore, permits application of multi-component calibration loads similar to model loads, leading\ud to improved accuracy of measured loads. In addition, with use of GRM it is possible to substantially reduce the number of calibration loads and hence, the calibration effort by optimization of load schedule.\ud The GRM was recently implemented and a MATLAB software developed for balance calibration data analysis at NAL. In\ud order to illustrate the application of GRM and use of the computer program calibrations of a 6-component internal balance were carried out with different types and number of calibration loads that included combined loads similar to model loads and the data were analyzed using GRM. The balance accuracy was assessed for a set of check loads consisting primarily of combined loads. Results showed that the accuracy when the calibration loads were similar to model loads was significantly better than that obtained using single- and two–component calibration loads. It was also found that improved accuracy could be obtained with\ud substantially reduced number of loadings.\ud The paper presents an overview of the GRM and brief details of application of the GRM to calibration of multicomponent\ud balances. A description of the above calibrations and discussions of the results are included