Comparison of Small Rotor Tonal and Random Noise Decomposition Methods

Abstract

This paper examines and compares methods of separating tonal and broadband components of the noise generated by small rotors as commonly found on small unmanned aerial systems (sUAS). Time synchronous analysis (TSA) methods with varying averaging algorithms, such as ensemble averaging (EA), exponential weighted moving averaging (EWMA) and Kalman filter averaging (KFA), are compared against themselves and against a cross-correlation-based method. The decomposition methods are used on noise measurements of a small isolated rotor under static operation and edgewise flight conditions at 10 m/s in the UNSW anechoic wind tunnel (UAT). The best method for isolating tones is TSA-EWMA and for isolating the broadband spectrum of noise is the cross-correlation method, based on the spectral reconstruction of the experimental data.