Analysis of Blasting Vibration Signal Based on EEMD fractal and&nbsp; Quadratic Time-Frequency SPWV Distribution

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Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (22) : 41-47.

Analysis of Blasting Vibration Signal Based on EEMD fractal and Quadratic Time-Frequency SPWV Distribution

YANG Ren-shu1 ，FU Xiao-qiang1 ，ZHANG Shi-ping2， SU Hong1

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Abstract

By combining of EEMD (Ensemble Empirical Mode Decomposition) and fractal box dimension algorithm, also the blasting vibration signal statistical self-similar characteristics,the paper puts forward the EEMD fractal box dimension generalized self-similarity method and uses generalized self-similarity factor to identify the blasting vibration signal principal component.The accuracy of the method is verified by the locomotive vibration signal.A multi-fractal algorithm is used to analyze the original blasting signal and the dominant component restructuring signal,it describes the multi-fractal characteristics of blasting vibration signals in non scale zone quantitatively.Getting the Cohen quadratic SPWV (Smooth Pseudo Wigner-Ville) time-frequency distribution characteristics of original signal and dominant components restructuring signal.The result shows that:the EEMD fractal box dimension generalized self-similarity of method can accurately identify the vibration signal principal component.the combination method of EEMD advantage component restructuring signal multi-fractal and the quadratic SPWV distribution analysis, reveals the local time-frequency characteristics contained in blasting vibration signal,can more effectively improve the modal aliasing and remove cross-term interference,strengthen signal time-frequency aggregation.

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YANG Ren-shu1,FU Xiao-qiang1,ZHANG Shi-ping2， SU Hong1. Analysis of Blasting Vibration Signal Based on EEMD fractal and Quadratic Time-Frequency SPWV Distribution[J]. Journal of Vibration and Shock, 2016, 35(22): 41-47

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