基于奇异值分解的频响函数降噪方法

为了提高外场测试中频响函数的信噪比，提出了一种基于奇异值分解的频响函数降噪方法。该方法首先对脉冲响应函数在相空间内进行重构；然后对重构轨道矩阵进行奇异值分解达到降噪的目的。其中，降噪阶次通过奇异熵增量进行确定。采用GARTEUR飞机模型建立具有密集模态的仿真算例进行验证。结果表明，在噪声干扰较大时，该降噪方法能够显著改善模态参数的识别精度，尤其是阻尼的识别精度。

Noise Reduction of Frequency Response Function Using Singular Value Decomposition

In order to increase the signal to noise ratio of frequency response f unction (FRF) in field test, an effective FRF noise reduction method based on si ngular value decomposition (SVD) was presented. Firstly, the phase space reconst ruction of the impulse response function was established, and then the trajector y attractor matrix was decomposed by using SVD. The optimal de noising order wa s determined according to the increment of singular entropy. A numerical simulati on with closely spaced modes was employed using the GARTEUR plane model. The res ults show that the accuracy of estimated modal parameters is improved obviously from the de noised FRF, especially for the damping ratio accuracy.