A dimensionality reduction approach in helicopter level flight performance testing

Abstract

Evaluation of the power required in level flight is essential to any new or modified helicopter performance flight-testing effort. The conventional flight-test method is based on an overly simplification of the induced and profile power components required for a helicopter in level flight. This simplistic approach incorporates several drawbacks that not only make execution of flight sorties inefficient and time consuming, but also compromise the level of accuracy achieved. This paper proposes an alternative flight-test method for evaluating the level-flight performance of a conventional helicopter while addressing and rectifying all identified deficiencies of the conventional method. The proposed method, referred to as the corrected-variables screening using dimensionality reduction (CVSDR), uses an original list of 36 corrected variables derived from basic dimensional analysis principles. This list of 36 corrected variables is reduced using tools of dimensionality reduction to keep only the most effective level-flight predictors. The CVSDR method is demonstrated and tested in this paper using flight-test data from a MBB BO-105 helicopter. It is shown that the CVSDR method predicts the power required for level flight about 21% more accurately than the conventional method while reducing the required flight time by an estimate of at least 60%. Unlike the conventional method, the CVSDR is not bounded by the high-speed approximation associated with the induced power estimation, therefore it is also relevant to the low airspeed regime. This low-airspeed relevancy allows the CVSDR method to bridge between the level-flight regime and the hover. Although demonstrated in this paper for a specific type of helicopter, the CVSDR method is applicable for level-flight performance flight testing of any type of conventional helicopter.