Propeller synchrophasing is an effective way of reducing interior noise and vibration of turboprop-driven aircraft. However, synchrophasing has achieved limited success in practice for the reason that the predetermined phase angles are not acoustically optimized for maximum noise reduction during all flight conditions. An investigation has been conducted out which includes two folds: first, the noise vector based on laboratory experimental data has been modeled and second, optimal phase to acquire minimum noise is obtained via optimization search. An improved identification method of vector noise model which can be less dependent to noise phase message is presented. Compared with traditional methods, this method can greatly reduce the real-time requirement between phase optimization model and control model or sound acquiring model, so it can eliminate the influence which communication delay brings on identification precision. A synchrophasing experimental platform is established to verify the vector noise modeling. It adopts two propellers-driven servo motors to simulate the interior noise environment of the aircraft. The influence of the date sampling condition on identification is also researched. Ant colony optimization with two improvements is applied to phase optimization of four propellers. Simulation results show that the improved algorithm requires much less calculation.

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