Micro-seismic signal multi-scale denoising method and device and readable storage medium

Abstract

The invention discloses a micro-seismic signal multi-scale denoising method and device and a readable storage medium, and the method comprises the steps: 1, obtaining a micro-seismic signal, carryingout the EMD or EEMD decomposition, and filtering the high-frequency noise in the decomposed signal; 2, respectively constructing a Hankel matrix of each IMF component; 3, carrying out singular value decomposition is based on the Hankel matrix of each IMF component to obtain a score vector of principal component analysis, carrying out primary denoising, and carrying out soft threshold secondary denoising on each component signal and residual component after primary denoising; and 4, superposing the component signal subjected to secondary denoising and the residual component to obtain a denoisedmicro-seismic signal. According to the method, singular value decomposition is associated with principal component analysis, information of singular value decomposition serves as a score vector of principal component analysis, the PCA calculation process is simplified, and the defect that denoising cannot be conducted on a single column vector through the score vector of singular value decomposition is overcome.

Description

technical field [0001] The invention belongs to the technical field of microseismic signal processing, and in particular relates to a method, device and readable storage medium for multi-scale denoising of microseismic signals. Background technique [0002] Microseismic monitoring technology, as an advanced and efficient monitoring method for ground pressure activity, has been widely used in mines, hydropower, tunnels and other fields. Microseismic monitoring technology collects seismic wave signals generated by rockbursts and fault slips through sensors, and then processes and analyzes the seismic wave signals to obtain information such as the location, magnitude, and energy of the event, and provide a basis for mine risk assessment. However, the mine environment is complex, and the signals monitored by the sensors usually have a lot of background noise, which will seriously affect the signal-to-noise ratio, energy calculation, and reduce the accuracy of P-wave first-arriva...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a brand-new technical means to realize microseismic signal denoising, wherein, the microseismic signal is firstly decomposed by EMD or EEMD, and then for a single component signal, the singular value decomposition is associated with the principal component analysis, with singular The value decomposition information is used as the score vector of principal component analysis, which saves the steps of calculating mean and covariance in conventional principal component analysis methods, and simplifies the calculation process; at the same time, in order to realize the singular value decomposition of a single component signal, the present invention uses a single The component signal is constructed into a multi-dimensional Hankel matrix, which overcomes the defect that the single component signal (single column vector) cannot be denoised by the score vector of singular value decomposition

Images