奇异谱分解在超声速无人机声振试验数据处理中的应用
Singular Value Spectrum Decomposition and Its Application to the acoustic vibration test parameters’ processing of supersonic aircraft
In order to realize the precise identification of the acoustic vibration test parameters about the supersonic aircraft, a new filtering method combining phase space reconstruction and singular spectrum decomposition is proposed. Firstly, feasibility of this method is demonstrated through numerical simulation. Secondly, in order to separate the signal subspace and the noise subspace, phase space reconstruction of the test parameters is processed, and the attractor track matrix is also decomposed with singular value decomposition (SVD). Finally, aiming at the shortage of the maximum difference spectrum theory, the concept of optimizing difference spectrum theory is given, and reconstruction is proposed on the basis of the peak position of the optimizing difference spectrum. Reconstruction results show that the proposed method is suitable for processing the acoustic vibration test data of the supersonic aircraft, providing a solution for the precise description of the supersonic aircraft flying state.
相空间重构 / 奇异值分解 / 超声速 / 声振试验 / 信号滤波 {{custom_keyword}} /
phase space reconstruction / singular value decomposition / supersonic / acoustic vibration test / signal processing {{custom_keyword}} /
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