SunYuan1, YangFeng1, ZhengJing2, et al. Research on microseismic signal denoising based on variational mode decomposition and wavelet energy entropy[J]. Journal of Mining Science and Technology, 2019, 4(6): 469-479.
Citation: SunYuan1, YangFeng1, ZhengJing2, et al. Research on microseismic signal denoising based on variational mode decomposition and wavelet energy entropy[J]. Journal of Mining Science and Technology, 2019, 4(6): 469-479.

Research on microseismic signal denoising based on variational mode decomposition and wavelet energy entropy

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  • Microseismicmonitoringtechnologyiswidelyusedinsuchfieldsasminingengineering,petroleumandgasexploitation,andsafetymonitoring.Inordertosolvetheproblemofrandomnoiseinmicroseismicsignalscollectedbymicroseismicmonitoring,adenoisingalgorithmbasedonvariationalmode decomposition(VMD)combinedwithwaveletenergyentropy(WEE) andimprovedthresholdfunction isproposed.Wavelettransformationisperformedoneachintrinsicmodefunction(IMF)componentafter VMDdecompositionoftheoriginalmicroseismicsignals.Thenoisestateofeachscalesignalischaracterizedbywaveletenergyentropy.Thethresholdofeachscalelayeriscalculatedbywaveletcoefficients ofthemaximumsubintervalofwaveletenergyentropyandthenthemicroseismicsignalsarereconstructedbythenewIMFsdenoisedthroughtheimprovedthresholdfunction.Theresultsfromnumericalsimulationsignalandrealsignalshowthattheproposedalgorithmissuperiortoempiricalmodedecomposi
    tion(EMD),ensembleEMD(EEMD)andVMDcombinedwithwaveletenergyentropyhardthreshold functionandsoftthresholdfunction.Thesignal-to-noiseratioofmicroseismicsignalsareimproved.

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