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Microseismic signal noise reduction filtering method based on VMD and wavelet packet

A wavelet packet and microseismic technology, applied in the field of signal processing, can solve the problems of high false positive rate, weak real-time algorithm, and low picking accuracy.

Inactive Publication Date: 2017-12-26
SHANDONG UNIV OF SCI & TECH
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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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  • Microseismic signal noise reduction filtering method based on VMD and wavelet packet

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Embodiment Construction

[0076] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0077] A noise reduction and filtering method for microseismic signals based on VMD and wavelet packets, the process is as follows figure 1 shown, including the following steps:

[0078] Step 1: Read the monitoring data time series X(t) of the noisy microseismic signal, where t=1,2,...,T; figure 2 shown;

[0079] Step 2: Perform VMD decomposition on the noisy microseismic signal to obtain a series of variational modal components; image 3 shown;

[0080] VMD decomposition is performed on noisy microseismic signals, and the variational constraint problem is to find k modal functions u k (t)(k=1,2,3...6), the sum of the estimated bandwidths of the decomposed modal components is required to be the smallest, and the sum of each mode is equal to the noisy microseismic signal X. The specific structure is:

[0081] Through the Hilbert transformat...

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Abstract

The invention discloses a microseismic signal noise reduction filtering method based on a VMD and a wavelet packet and belongs to the signal processing technology field. In the invention, a mode of combining the VMD and the wavelet packet is adopted; adaptivity of a VMD decomposition method and characteristics of a high mathematical theory basis, high frequency noise suppression and the like in the algorithm are used; and the wavelet packet has the characteristics of carrying out multilevel division on a frequency band, further decomposing a high frequency portion which is not subdivided in multiresolution analysis, and adaptively selecting a frequency band according to a characteristic of an analyzed signal so that a time frequency resolution is increased. In the invention, based on a condition of maintaining randomness, non-stationary performance and a burst transient characteristic of a microseismic signal, the microseismic signal is filtered. The algorithm is simple and easy and an effect is ideal. Effective noise reduction filtering can be performed on a mine noisy microseismic signal. And a good technical value and an application prospect are possessed.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a noise reduction filtering method for microseismic signals based on VMD and wavelet packets. 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 proce...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/36G01V1/28
CPCG01V1/364G01V1/288G01V2210/123G01V2210/324
Inventor 彭延军刘统斌王元红卢新明贾瑞生
Owner SHANDONG UNIV OF SCI & TECH
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