Mine microquake signal noise reduction filtering method based on VMD

Abstract

The invention discloses a mine microquake signal noise reduction filtering method based on VMD, and belongs to the signal processing technical field; the method comprises the following steps: reading a sequential sequence x (t) of noised microquake signals; carrying out VMD decomposition for the sequential sequence x (t) of the microquake signals; calculating a cross correlation coefficient between the microquake signal sequential sequence x (t) and each variation modal component uk; considering the variation modal component with the central frequency bigger than 200Hz and the cross correlation coefficient with the noised microquake signal sequential sequence x (t) smaller than 0.3 as noises, and filtering the noises; reconstructing residual variation modal components, thus obtaining noise reduction and post-filter microquake signals. The method can effectively prevent modal aliasing phenomenon, is strong in adaptability and instantaneity, and can effectively carry out noise reduction filtering treatment for the microquake signals.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a VMD-based noise reduction filtering method for mine microseismic signals. Background technique [0002] Microseismic data are induced when the rock breaks. However, the underground noise pollution of coal mines is serious, so the microseismic data contains a large amount of external noise, and it is necessary to separate the effective microseismic signal from the noise. [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, and high misjudgment rate. The picking accuracy is low, and the algorithm is not real-time. For example, EMD will produce mode aliasing phenomenon during the decomposition process, that is, one o...

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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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