基于波音算法的航空发动机风扇噪声预测

作为涡扇发动机的一个关键噪声源,随着涵道比的不断加大,风扇噪声在飞机起飞时对整机噪声的贡献量也日益增加;因此预测风扇噪声对飞机噪声适航评估工作有极大意义。采用Boeing风扇噪声预测算法,结合飞机起飞航迹,利用MATLAB软件编程,经过多普勒效应修正、几何发散衰减修正和大气吸声衰减修正,得到起飞时风扇噪声预测模型。以某型发动机为算例,计算出实际飞机起飞时噪声适航审定中所需测量的每隔0. 5 s动态声压级的预测值。把最终得到的有效感觉噪声级预测值与欧洲航空安全局提供的有效感觉噪声级真实值进行对比,验证了该模型的准确性;此模型能有效降低新飞机的研发成本和风险,缩短噪声适航审定周期。

Prediction of Aero Engine Fan Noise Bases on Boeing Algorithm

As a key noise source of turbofan engine, as the bypass ratio increases, the contribution of fan noise to the noise of the overall aircraft is also increasing during the aircraft takeoff. Therefore, predicting fan noise is of great significance to the evaluation of aircraft noise airworthiness. Based on Boeing fan noise prediction algorithm, combined with aircraft takeoff flight path, and using MATLAB software programming. Through the Doppler effect correction, geometric divergence attenuation correction and atmospheric sound absorption attenuation correction, the fan noise prediction model during takeoff is obtained.A certain type of engine is taken as an example to calculate the predicted value of the dynamic sound pressure level every 0.5 seconds required for the actual airworthiness certification of the aircraft. The accuracy of the model was verified by comparing the final predicted value of effective sensory noise level with the real value of effective sensory noise level provided by the European aviation safety authority. This model can effectively reduce the development cost and risk of new aircraft and shorten the cycle of noise airworthiness certification.