The active vibration control technology has been successfully applied to several helicopter types. However, with the increasing of control scale, traditional centralized control algorithms are experiencing significant increase of computational complexity and physical implementation challenging. To address this issue, a diffusion collaboration-based distributed Filtered-x Least Mean Square algorithm applied to active vibration control is proposed, drawing inspiration from the concept of data fusion in wireless sensor network. This algorithm distributes the computation load to each node, and constructs the active vibration control network topology of large-scale system by discarding the weak coupling secondary paths between nodes, achieving distributed active vibration control. In order to thoroughly validate the effectiveness and superiority of this algorithm, a helicopter fuselage model is designed as the research object. Firstly, the excellent vibration reduction performance of the proposed algorithm is confirmed through simulations. Subsequently, specialized node control units are developed, which utilize STM32 microcontroller as the processing unit. Further, a distributed control system is constructed based on multi-processor collaboration. Building on this foundation, a large-scale active vibration control experimental platform is established. Based on the platform, experiments are carried out, involving the 4-input 4-output system and the 8-input 8-output system. The experimental results demonstrate that under steady-state harmonic excitation, the proposed algorithm not only ensures control effectiveness but also reduces computational complexity by 50%, exhibiting faster convergence speed compared with traditional centralized algorithms. Under time-varying external excitation, the proposed algorithm demonstrates rapid tracking of vibration changes, with vibration amplitudes at all controlled points declining by over 94%, proving the strong robustness and adaptive capability of the algorithm.

Noise reduction program design is an effective approach that relies on efficient noise prediction for reducing ground noise during flight. The existing noise prediction methods have the limitations of being computationally expensive or only applicable to far-fields. In this paper, a High-Efficiency Prediction Method (HEPM) for helicopter global/ground noise based on near-field acoustic holography is proposed. The HEPM can predict the global noise based on acoustic modal analysis and has the advantages of high prediction accuracy and low time cost. The process is given as follows: firstly, the rotor noise on the holographic surface in the specified flight is obtained by simulations or experiments. Secondly, the global noise model, which maps time-domain noise to acoustic modes, is established based on near-field acoustic holography and Fourier acoustic analysis methods. Finally, combined with acoustic modal amplitude, the model established enables efficiently predicting the global/ground noise in the corresponding flight state. To verify the accuracy of the prediction method, a simulation study is conducted in hovering and forward flight states using a model helicopter with a 2-meter rotor and Rotor Body Interaction (ROBIN) fuselage. The comparison of HEPM with numerical results shows that the average prediction errors of the global and ground noise are less than 0.3 dB and 0.2 dB, respectively. For a region containing 100000 observers, the computation time of the HEPM is only one-fifth of that of the acoustic hemisphere method, demonstrating the rapidity of the proposed method.

Multi-rotor aircraft has great potential in urban traffic and military use and its noise problem has attracted more attention recently. Multi-rotor aircrafts are typically controlled by changing the rotation speeds of the rotors. To reduce the noise of multiple frequency-modulated rotors, a global noise attenuation method is proposed in this study. First, the fast prediction method is used to estimate the global noise of the multirotor with different configurations online. Meanwhile, the sound field reproduction method is used to obtain the control signal of the loudspeaker array to achieve global noise attenuation. Then, the influence of array arrangement on noise reduction is analyzed in the acoustic modal domain, which reveals that different optimization models are needed to minimize the noise power or/and the noise pressure in some directions when the scale of the array is limited. Next, to improve the real-time performance of the system, the online calculation of the optimal control signal is transformed into the offline design of the optimal filter, which satisfies the target frequency-domain characteristics. Finally, the experimental results of the noise of a model quadrotor in the anechoic chamber were consistent with the predicted results. The simulation results of noise attenuation for the quadrotor show that the method proposed reduced the global noise power by about 13 dB. Moreover, the noise region radiated from the quadrotor to the ground with the boundary of 40 dB was reduced to 8.4% of that before control.