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机构地区:[1]中国空气动力研究与发展中心空气动力学国家重点实验室,绵阳621000 [2]中国空气动力研究与发展中心计算空气动力研究所,绵阳621000
出 处:《航空学报》2015年第7期2177-2185,共9页Acta Aeronautica et Astronautica Sinica
摘 要:针对飞机研制中操稳特性需求,分别讨论了小扰动理论和参数辨识两种获得飞机稳定和操纵大导数的分析手段,由两种气动布局比较接近的小型无人机ANCE和大型客机Boeing 747数据验证了参数辨识方法的有效性和辨识结果的正确性。在此基础上对两者进行了大导数辨识,并由Monte Carlo仿真分析了飞行试验测量中的随机噪声对大导数辨识精度和模态响应特征值的影响。结果表明:随机噪声对由飞机固有气动特性决定的一些相对较小的大导数辨识精度影响较大,而部分大导数辨识精度较高;随机噪声对长周期和螺旋模态特征值影响较大,短周期、荷兰滚和滚转模态特征值辨识分析结果较为可信。Small perturbation theory and parameter identification method are applied to obtaining the stability and control derivatives of an airplane. To accomplish the stability and control characteristics analysis during the airplane design, we develop the parameter identification algorithm, which are validated with data of an unmanned airplane vehicle ANCE and a Boeing transport airplane Boeing 747. Firstly, we estimate the stability and control derivatives of the airplanes and compare them with the small perturbation theory results. Then the accuracy of the estimated derivatives and the dispersion of the eigenvalues of different response modes are quantitatively analyzed by Monte Carlo simulation based on the known measurement noises during the flight test. The estimating accuracy of certain relatively small derivatives, which are dominated by airplanes; inherent aerodynamic characteristics, degenerates with these noises. The response eigenvalues of short-period mode, Dutch-roll mode and roll mode under random noises can be accurately acquired with the parameter identification algorithm presented here, while the response eigenvalues of phugoid mode and spiral mode are more sensitive to noises.
关 键 词:大导数辨识 随机噪声 操稳特性 响应模态 小扰动理论
分 类 号:V212.12[航空宇航科学与技术—航空宇航推进理论与工程]
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