Aeroacoustic analysis of fixed- and variable-pitch controlled multirotors and noise reduction via rotor phase control

This research conducts a comparative analysis of the aerodynamic and aeroacoustic characteristics of fixed-pitch and variable-pitch controlled multirotors (i.e., revolution per minute and collective pitch control). The study encompasses hovering and forward flight conditions, considering wind gust effects. Specifically, high-resolution time-frequency analysis is conducted to investigate the interference and modulation effects of multirotor noise. The analysis reveals significant variations in spectral characteristics depending on the control method. Notably, the frequencies of tonal noise from variable-pitch controlled multirotor do not exhibit short-periodic modulation, in contrast to those of fixed-pitch controlled multirotor. Considering the distinctive spectral characteristics of variable-pitch controlled multirotor, this study explores the effectiveness of noise reduction in variable-pitch controlled multirotor by implementing rotor phase control methods. To validate the noise reduction in time series simulations, a deep learning model is employed to determine the dynamically optimized rotor phases. A multilayer perceptron neural network was trained to derive the optimal rotor phase angles over time, considering the target observer points and flight conditions. The results demonstrate a substantial reduction in noise at the target observer points.