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基于频域子空间模态参数识别方法,提出了一种适用颤振试飞数据处理的频域子空间与非线性优化相结合的模态参数识别方法。通过GARTEUR模型数据对其进行了仿真验证,结果表明,模态阻尼识别精度在5%以内。将该方法用于实际颤振飞行试验的数据处理,结果表明,通过非线性优化后能够提高模态阻尼的识别精度,且具有抗噪声能力强、密集模态识别能力强和识别速度快等优点。
Based on the method of frequency domain subspace modal parameter identification, a modal parameter identification method based on frequency domain subspace and nonlinear optimization for flutter test data processing is proposed. The results of simulation with GARTEUR model show that the modal damping recognition accuracy is within 5%. The method is applied to the data processing of actual flutter flight test. The results show that the method can improve the recognition accuracy of modal damping by nonlinear optimization and has the advantages of strong anti-noise ability, intensive modal recognition ability and fast recognition speed .