Analysis of Balance Calibration Machine Data Using Automatically Generated Math Models

A new process was developed at Ames Research Center that automatically generates a permitted and a recommended math model for the analysis of strain–gage balance calibration data. The accuracy of these math models was investigated using two calibration data sets that were provided by the German– Dutch Wind Tunnels. These calibration data sets were obtained in a balance calibration machine. The first calibration data set was generated using the traditional OFAT method. The second data set was obtained using the MDOE approach. A single data reduction matrix was computed for the OFAT data set using the permitted math model. Two data reduction matrices were calculated for the MDOE data set using the permitted and the recommended math model. Measured and fitted loads at check points were compared in order to assess the accuracy of the three data reduction matrices. This comparison showed that the data reduction matrix of the recommended math model, i.e., of the math model that uses only the most significant terms of each gage, is as accurate as the data reduction matrix of the much larger permitted math model. In addition, it was demonstrated that, for the given balance calibration task, the two data reduction matrices of the MDOE data set are as accurate as the data reduction matrix of the much larger OFAT data set.