Adaptive optimization narrow-band Decomposition Method and Its Application

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Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (15) : 1-6.

PENG Yanfeng CHENG Junsheng YANG Yu LI Baoqing

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Abstract

Adaptive and sparsest time-frequency analysis (AONBD) method is proposed. Signal decomposition is translated into optimizing the parameters of the filter. The optimization objective is obtaining the sparsest solution of signals. The original signal is adaptively decomposed into several intrinsic narrow-band components (INBC) via optimization. AONBD method has two steps. First，the best filter is obtained by optimization. Secondly，the sparsest solution is derived by filtering the original signal using the designed filter. The basic theory and decomposition steps of AONBD are described. Comparisons are made between AONBD，adaptive sparsest time-frequency analysis (ASTFA) and empirical mode decomposition (EMD) by utilizing a simulation signal. The results show that AONBD method is superior to the other two methods in restraining the end effect and mode mixing，anti-noise performance，improving the orthogonality and accuracy of components. AONBD method is applied to analyzing the vibration signal of rotor. And the results indicate that AONBD can be effectively applied to mechanical fault diagnosis.

Key words

Adaptive optimization narrow-band decomposition / Intrinsic narrow-band components / Local narrow-band signal / Singular local linear operator / Rotor fault diagnosis

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PENG Yanfeng CHENG Junsheng YANG Yu LI Baoqing. Adaptive optimization narrow-band Decomposition Method and Its Application[J]. Journal of Vibration and Shock, 2016, 35(15): 1-6

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