Research And Implementation Of Microseismic Acquisition System Based On DNW-EMD Denoising Algorithm

China’s economic,scientific,and technological development has been remarkable,internet plus’ s traditional industries are the further practical achievements of modern thinking in the present era,which has promoted the development of social economy and provided new vitality for the development of traditional industries.Internet plus mine has also become the main theme of contemporary mining development.With the increase of mining scale,depth and intensity,the occurrence of mine earthquake seriously threatens the life safety of employees and the safety of economic development.Over the years,through the research of a large number of scholars,a microseismic early warning platform has been put forward.By locating and warning the location where the mine earthquake occurs,the loss of personnel and financial resources can be avoided to the maximum extent.The whole foundation and key of microseismic early warning and prediction is the signal acquisition and transmission of the mine earthquake.Due to the complex working environment and complex rock structure under the mine,a lot of noise is generated.The network is not smooth;This paper proposes a microseismic acquisition system based on the DNW-EMD denoising algorithm,which is based on New Waveform Improved Empirical Mode Decomposition,due to the abundance of signal data.Based on the research of a large number of documents,this paper puts forward a denoising method based on DNW-EMD,aiming at the problem of signal denoising in the process of microseismic signal acquisition,as well as the problems of threshold size error and pseudo-Burgis oscillation before and after processing in the commonly used wavelet soft threshold denoising algorithm and hard threshold denoising algorithm according to the characteristics of microseismic signal,and the fact that the traditional empirical mode decomposition denoising algorithm can not screen out the pseudo-decomposition variables with low correlation with the main signal and extract the residual useful information of the decomposition variables that can be removed,which will cause the low signal-to-noise ratio and signal distortion of the synthetic signal.DNW-EMDdenoising algorithm is an improved empirical mode decomposition denoising algorithm based on a new threshold function wavelet.This algorithm can maximize the denoising while retaining the effective components of the signal to the greatest extent,and achieve a high signal-to-noise ratio of the signal.This research is of great significance to the research of anti-noise and acquisition system of microseismic signals.The microseismic acquisition system mainly deploys the system in several locations around the mining area,and then collects microseismic signals.At the same time,the received seismic signals are converted into electrical signals and then sent to the early warning platform.The early warning platform recently calculates the location according to the time difference of receiving seismic signals at each point.Based on the above problems,the acquisition system proposed in this paper is composed of hardware and software,and the hardware is composed of multiple modules to realize the functions of acquisition,timing and storage.The software is developed by C++ programming language,MFC and other development languages,and technologies such as multithreading and cache are used many times in the system to improve the processing speed of the system.The microseismic acquisition system based on DNW-EMD denoising algorithm developed in this paper has been deployed in a coal mine in Erdos City,Inner Mongolia in July 2022.In more than half a year,it has avoided the danger of mine earthquakes several times,providing practical guarantee for the development of coal industry and personnel safety.