Study On The Method Of Arrival Automatic Pickup Of Microseismic P-wave Phase

In a series of artificial mining activities such as mining,tunnel mining and subway construction,the dislocation of underground strata can easily cause micro vibration events.For a long time,real-time monitoring of micro-vibration events has been a hot topic at home and abroad.Among them,the picking up of the microseismic phase at the first arrival is the key link in monitoring microseismic events.And it is the premise and foundation to realize focal location and focal mechanism interpretation.There are many methods to pick up the first phase of seismic phase.Because the calculation process of different methods is different,and the applicable environment is also very different.At present,STA/LTA,AIC,autoregressive analysis,and neural network methods are widely used.In practical engineering applications,the environment of microseismic monitoring system is complex,and the microseismic signal collected by the microseismic signal contains a large amount of interference noise,which causes great interference to the traditional method of accurate picking.In this paper,based on the study of traditional seismic phase pickup methods,an improved algorithm is proposed.The basic idea of the algorithm are as follows.Firstly,the signal is de-noised by EEMD decomposition and reconstruction.And then use STA/LTA to calculate the approximate time.Finally,AIC is used to calculate the exact arrival time.The main contents of the study are as follows:(1)The advantages and disadvantages of various traditional methods are analyzed.STA/LTA algorithm has many parameters and is difficult to control.And the pick-up time is often lagging behind.In the case of prior source information,the AIC algorithm can pick up an accurate first arrival of the seismic phase.The method of autoregressive analysis can obtain good results under certain conditions,but it is difficult to model because of the large number of parameters of the method.Neural network method has better fault tolerance,but this method requires accurate training samples.(2)In this paper,a new method of noise reduction is proposed to solve the problem of large noise interference when the microseismic signals are picked up at low signal-to-noise ratio.This method applies STA/LTA to EEMD decomposition and reconstruction,and determines a criterion for selecting IMF components.(3)Based on the STA/LTA algorithm has faster picking speed,but the result is error.And AIC algorithm picks up the exact results,but the algorithm is complex.In this paper,a new arrival pickup algorithm is proposed by combining the two methods.(4)The effectiveness and practicability of the proposed algorithm are verified by many experiments in this paper.In the low SNR environment,the accuracy of the algorithm is 96.56%.Which the accuracy of AIC algorithm is 94.32%,when the time window is selected.And the STA/LTA picking accuracy is 85.34%.The experimental results show that the proposed algorithm not only improves the signal-to-noise ratio(SNR),but also reduces the root mean square error(RMS).