Fast prediction method for multirotor global tonal noise based on acoustic modal analysis

Multi-rotor global tone noise is a type of noise produced by the rotor blades of multi-rotor drones that can cause significant problems for both operators and nearby residents. Predicting multirotor global tonal noise can be challenging due to the complex aerodynamic interactions between the rotors and the air. However, there are several techniques that can be used to estimate the level of global tonal noise. One approach is to use computational fluid dynamics (CFD) simulations to model the airflow around the multirotor drone and predict the noise generated by the rotor blades. CFD simulations can be used to predict the pressure fluctuations and sound radiation from the rotor blades, which can then be used to estimate the level of global tonal noise generated by the multirotor drone. However, CFD simulations can be computationally expensive and require specialized software and expertise. Another approach is to use empirical models to estimate the level of global tonal noise. Empirical models are based on experimental data and can be used to estimate the noise generated by the rotor blades based on the rotor design and operating conditions. These models can be simpler and faster than CFD simulations but may not be as accurate.

Acoustic modal analysis is a technique for identifying and analyzing system acoustic properties such as natural frequencies and mode shapes. By applying this technique to a multirotor drone, it is possible to identify the specific acoustic modes responsible for generating global tonal noise. To this account, Nanjing University of Aeronautics and Astronautics researchers: PhD Xice Xu,  Professor Yang Lu, PhD Mengxue Shao and Associate researcher  Chunbo Lan conducted a study to predict global tonal noise at a small computational cost and then provide a fast model for online noise prediction and control. The research work is now published in the peer-reviewed Journal Mechanical Systems and Signal Processing.

The research team identified that with advancement of multirotor aircrafts, the aerodynamic noises have caused a serious impact on the environment. The aerodynamic noise produced by multirotor aircraft can be exceptionally intricate due to the number of rotors involved, making it a significant obstacle for both predicting and controlling the noise. they divided the rotor noise sources of rotary wing vehicles into two main components: deterministic (tonal noise) and nondeterministic (broadband noise). The deterministic further includes thickness, loading, blade vortex and high-speed impulsive noise. The first two were classified as rotational noise and the later required specific flight conditions.

Analysis of blade load harmonics has shown that for rotors with low solidity and blade count, the fundamental discrete level is primarily determined by steady rotation forces. However, during forward flight or due to installation effects, unsteady loading noise may be generated, which can radiate preferentially around the vertical axis if not mitigated through proper phasing between the synchronized rotors. As a result, a comprehensive acoustic model is necessary to analyze the complex noise generated from various sound sources.

The authors proposed a new method for predicting global noise starts by establishing a global noise model for a single rotor in the acoustic modal domain using near-field acoustic holography. From there, the global noise model for rotors with different configurations was obtained by mapping the acoustic modal coefficients. The wave superposition principle was then used to predict the global noise of a multirotor based on rotor configuration information. To assess the effectiveness of the new method, they compared the predicted global noises of single and multirotor configurations with other numerical methods. The results indicated that the acoustic modal analysis accurately predicted global noise with a relatively low computational cost. Additionally, a parametric study was conducted to evaluate the impact of various configurations on global noise, and the synchronization method was analyzed. Finally, the authors carried out experiments in an anechoic chamber to validate the proposed method. They found that when the separation distance between rotor shafts was greater than 2.8 R, the aerodynamic interference between rotors can be ignored, and the method can be successfully applied globally. However, if the distance was less than 2.8 R, the aerodynamic interference can result in prediction errors, especially at higher elevation angles. As the elevation angle decreases, the prediction error rapidly diminishes.

The authors’ findings has advantages in near the future. We shall be able to make fast and accurate prediction on global tonal noise without spending extensive computational resources. We shall also be able to accurately predict global noise from different sound sources, including multi rotors with varying configurations. This would help us keep these rotary vehicles at a safe distance away from the general public in order to curb the effect of noise pollution. The method proposed by Professor Yang Lu and colleagues has been experimentally validated in an anechoic chamber, demonstrating its effectiveness in predicting global noise. Overall, predicting multirotor global tonal noise can be challenging, this new research work makes a valuable contribution to the field of multirotor noise prediction and control, providing a fast and accurate global tone noise prediction method that can be applied to various multirotor configurations.