FU Xiaoqiang, CUI Xiuqin, YANG Liyun, LEI Zhen, CAI Xueji, LI Yang. Application of Variational Mode Decomposition Algorithm in Elimination of Trend Term of Coal Mine Shaft Blasting Signal[J]. Safety in Coal Mines, 2020, 51(10): 248-252.
    Citation: FU Xiaoqiang, CUI Xiuqin, YANG Liyun, LEI Zhen, CAI Xueji, LI Yang. Application of Variational Mode Decomposition Algorithm in Elimination of Trend Term of Coal Mine Shaft Blasting Signal[J]. Safety in Coal Mines, 2020, 51(10): 248-252.

    Application of Variational Mode Decomposition Algorithm in Elimination of Trend Term of Coal Mine Shaft Blasting Signal

    • In the test process of blasting signal, influenced by the test environment and the instrument, the signals detected near blasting area often contain the trend item interference, which cannot achieve the fine extraction of signal characteristics. The blasting signals are effectively collected, and the trend items are eliminated and the time-frequency characteristics are extracted using the variational mode decomposition(VMD). The results show that: the trend term of blasting vibration signal has the characteristics of high amplitude and low frequency; it’s more broadly distributed in time. The real components in the signal have the characteristics of wide frequency and low amplitude, and the aggregation is stronger on the time axis, there is a significant degree of differentiation between them. The variational mode decomposition is highly adaptive to the blasting signal and can effectively avoid the generation of the mode aliasing effect.
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