A Dimensionality Reduction Approach in Helicopter Hover Performance Flight Testing

Abstract

The power required to hover a helicopter is fundamental to any new or modified performance flight-testing effort. The conventional method of relating two nondimensional variables (coefficients of power and weight) is overly simplified and neglects compressibility effects in the power required to hover under a wide range of gross weights and atmospheric conditions. An alternative flight-test method for assessing hover performance while addressing this deficiency of the conventional method is proposed. The method uses an original list of 15 corrected variables derived from fundamental dimensional analysis, which is further reduced by means of dimensionality reduction to include only the most essential and effective predictors. The method is demonstrated using data of a Bell Jet-Ranger and shows that at the 95% confidence level; the averaged prediction error is only 0.9 hp (0.3% of the maximum continuous power). Using the same data, the conventional method yields a much larger averaged prediction error of 1.7 hp.