基于神经网络的直升机适航噪声预估方法研究
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摘要
适航噪声分析是民用直升机研发的一个环节,根据直升机的设计参数,建立三种适航状态的分析模型,获得直升机的噪声水平。文章在提炼直升机噪声的主要影响参数的基础上,利用神经网络适用于非线性预估的特点,采用美国联邦航空局(FAA)的资讯通报发布的直升机适航噪声飞行试验数据,进行神经网络的设计和训练,建立了基于神经网络的直升机适航噪声分析方法,在保证分析误差的基础上,实现了直升机适航噪声的预估。
The prediction of helicopter certificated noise is one step of a civil helicopter development,which needs to construct models of three flight conditions required by helicopter noise certification,to predict helicopter noise levels,using the helicopter parameters as input. Based on the nonlinear character of neural network,the neural network for helicopter certificated noise prediction was modeled,and trained using the helicopter certificated noise levels data published by FAA. For the significant effects of neural network inputs to performance,the general parameters affecting helicopter noise levels were analyzed in the paper. The results indicated that the desirable helicopter noise levels could be simulated from the neural network.
The prediction of helicopter certificated noise is one step of a civil helicopter development,which needs to construct models of three flight conditions required by helicopter noise certification,to predict helicopter noise levels,using the helicopter parameters as input. Based on the nonlinear character of neural network,the neural network for helicopter certificated noise prediction was modeled,and trained using the helicopter certificated noise levels data published by FAA. For the significant effects of neural network inputs to performance,the general parameters affecting helicopter noise levels were analyzed in the paper. The results indicated that the desirable helicopter noise levels could be simulated from the neural network.
引文
[1]陈平剑,仲唯贵,段广战.直升机气动噪声研究进展[J].实验流体力学,2015,29(3):18-24.
[2] Farassat F. Derivation of formulations 1 and 1A of Farassat[R]. NASA/TM-2007-214853,2007.
[3] Liu Y,Anusonti-Inthra P,Diskin B. Development and validation of a multidisciplinary tool for accurate and efficient rotorcraft noise prediction(MUTE)[R]. NASA/CR-2011-217057,2011.
[4]王阳,徐国华.直升机飞行参数对起降过程中旋翼桨-涡干扰噪声影响的分析[J].空气动力学学报,2010,28(3):322-327.
[5] CCAR-36-R2,航空器型号和适航合格审定噪声规定[S].北京:中国民用航空局,2018.
[6] AC 36-1H,Noise levels for U.S. certificated and foreign aircraft[S]. FAA Advisory Circular,2001.
[7]孙伟,张呈林.神经网络在直升机概念设计中的应用[J].南京航空航天大学学报,2009,41(1):121-125.
[2] Farassat F. Derivation of formulations 1 and 1A of Farassat[R]. NASA/TM-2007-214853,2007.
[3] Liu Y,Anusonti-Inthra P,Diskin B. Development and validation of a multidisciplinary tool for accurate and efficient rotorcraft noise prediction(MUTE)[R]. NASA/CR-2011-217057,2011.
[4]王阳,徐国华.直升机飞行参数对起降过程中旋翼桨-涡干扰噪声影响的分析[J].空气动力学学报,2010,28(3):322-327.
[5] CCAR-36-R2,航空器型号和适航合格审定噪声规定[S].北京:中国民用航空局,2018.
[6] AC 36-1H,Noise levels for U.S. certificated and foreign aircraft[S]. FAA Advisory Circular,2001.
[7]孙伟,张呈林.神经网络在直升机概念设计中的应用[J].南京航空航天大学学报,2009,41(1):121-125.