A Noise Reduction and Filtering Method of Mine Microseismic Signals Based on VMD

Abstract

The invention discloses a VMD-based noise reduction filtering method for mine microseismic signals, which belongs to the technical field of signal processing, and comprises the following steps: reading the time series sequence x(t) of the microseismic signal containing noise; t) Perform VMD decomposition; calculate the time series x(t) of the microseismic signal and each variational modal component u k The cross-correlation coefficients; the variational modal components whose center frequency is greater than 200 Hz and whose cross-correlation coefficient with the time series x(t) of the noisy microseismic signal is less than 0.3 are filtered out as noise, and the remaining variational modal components are reassessed. structure to obtain the microseismic signal after noise reduction filtering. The invention can effectively avoid the modal mixing phenomenon, has the advantages of strong self-adaption and real-time performance, and can perform effective denoising and filtering processing on microseismic signals.

Description

Technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a method for reducing noise of mine microseismic signals based on VMD. Background technique [0002] When the rock breaks, it induces microseismic data and forms microseismic data, and the noise pollution in the coal mine is serious. Therefore, the microseismic data contains a lot of external noise, and the effective signal of the microseismic needs to be separated from the noise. [0003] At present, the commonly used methods for noise reduction and filtering of rock fracture microseismic signals include empirical mode decomposition (EMD), integrated empirical mode decomposition (EEMD), wavelet analysis, etc. These methods are slow in operation, poor in noise resistance, and high in misjudgment. The picking accuracy is low and the algorithm is not real-time. For example, EMD will produce modal aliasing in the decomposition process, that is, one or more IMFs obtai...

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Problems solved by technology

[0003] At present, the commonly used noise reduction filtering methods for rock fracture microseismic signals include Empirical Mode Decomposition (EMD), Integrated Empirical Mode Decomposition (EEMD), wavelet analysis, etc. These methods have slow calculation speed, poor anti-noise performance, high misjudgment rate, The picking accuracy is low and the algorithm is not real-time

For example, EMD will produce mode aliasing phenomenon in the decomposition process, that is, one or more IMFs obtained by decomposition contain extremely different characteristic time scales, and the signal and noise are aliased in one or more IMFs, which is difficult to achieve effective Ground noise reduction filter effect

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