Aiming at the problem that the actual engineering vibration noise signal has strong noise with strong nonlinear characteristic, a phase space reconstruction method based on adaptive intrinsic dimension estimation manifold learning was proposed. Firstly, one-dimensional time series with noise were reconstructed into a high dimensional phase space by phase space reconstruction. Secondly, the intrinsic dimension of each sample point in the phase space was estimated based on the maximum likelihood estimate (MLE) and adaptive weighted average method was used to obtain the global intrinsic dimension. At last, the manifold learning algorithm local tangent space alignment ( LTSA) was employed project the signal with noise from the high-dimensional phase space to the intrinsic dimensional space of useful signal and eliminate the noise distributed in high-dimensional space. The Lorenz simulation and wind noise reduction of vibration signal instance proved that the proposed method has good performance in nonlinear noise reduction.
马婧华,汤宝平,宋涛. 基于自适应本征维数估计流形学习的相空间重构降噪方法[J]. 振动与冲击, 2015, 34(11): 29-34.
MA Jing-hua, TANG Bao-ping, SONG Tao. Phase space reconstruction method based on adaptive intrinsic dimension estimation manifold learning. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(11): 29-34.
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