IDENTIFICATION OF HELICOPTER COMPONENT LOADS USING MULTIPLE-REGRESSION

Multiple regression analysis of helicopter flight data is used to deve lop prediction models for rotating system component loads from paramet ers measured in the fixed system. The data base that is analyzed conta ins load measurements for a helicopter performing several types of fli ght maneuvers, including symmetric pullouts, rolling pullouts, climbin g turns, and level flight. The data are divided into two parts: one fo r model development and one to serve as a blind test of the model. For steady level flight, linear and nonlinear regression analyses are per formed to predict main rotor pushrod and blade normal bending vibrator y loads. Correlations above 95% were achieved on the test data for the steady level flight condition. For comparison, analytical results cal culated using the CAMRAD/JA rotor analysis computer code for the helic opter in level flight are included. Regression models to predict vibra tory loads during maneuvering flight are also developed. Evaluations o n the test data indicate that correlations ranging from 79 to 95% are possible for the types of maneuvers contained in the data base.