| Rock burst is a kind of disaster which seriously threatens the safety of mine and is extremely destructive.When it occurs,the coal and rock mass around the working face or roadway is suddenly destroyed under the action of high stress,accompanied by loud sound and impact vibration,and the vibration energy is transmitted to the outside in the form of elastic wave.The elastic wave contains basic information such as the internal structure and energy evolution of coal and rock mass caused by loading.The effective processing and application of these information is of great significance for understanding the changes of energy and structure of underground strata,the temporal and spatial evolution of fracture and the monitoring and prediction of rock burst.Aiming at the identification of elastic wave characteristics in time and frequency domain caused by sub-instability of rock burst,this paper uses the methods of theoretical analysis,experimental research and field application to carry out the optimization method of picking up the first arrival time of microseisms.the location algorithm of microseismic source,the signal waveform characteristics of different loading sections of rock and its field application.In the optimization research of picking up the first arrival time of microearthquakes,based on STA/LTA algorithm and AIC algorithm,the picking effect of noisy signals is analyzed by using correlation denoising methods such as digital filter,wavelet denoising and EMD decomposition denoising,and the optimal algorithm for picking first arrival time under different signal-to-noise ratio is proposed.The research shows that the first arrival time can be calculated directly for signals with signal-tonoise ratio greater than 30 d B.For the signal whose signal-to-noise ratio is 10-20 d B,the signal after noise reduction can be used to pick up the first arrival time,and for the signal whose signal-to-noise ratio is less than 10 d B,the signal after noise reduction can be combined with AIC method to pick up the first arrival time.In the research of microearthquake source location algorithm,based on the global grid search method,a new microearthquake location search method,"fish swarm algorithm + mountain climbing method",is proposed.The fish swarm algorithm searches the source in the global mode.Compared with the grid search method,the calculation of all grid nodes can save a lot of time,and the final search result is close to the real source point,but the accuracy is poor.The mountain climbing method is a calculation method for the local extreme point,which combines the two methods and uses the mountain climbing search method to search the final source point on the basis of searching the initial more accurate source point by the fish swarm algorithm.In the study of signal waveform characteristics of different loading sections of rock,according to three different types of rock failure experiments to simulate different failure types of rock strata,acoustic emission instruments are used to monitor the whole process of rock loading at the same time.At the same time,the acoustic emission data collected are used to analyze the characteristics of acoustic emission waveforms of the three failure types in time domain,frequency domain,time and frequency domain and power spectrum.The characteristics of rock failure in elastic stage,plastic stage and sub-instability stage are extracted.The proposed method is applied to the field microseismic data of Hongyang No.3 Coal Mine to automatically identify the first arrival time of noisy microseismic signals,and use all the sensors in the system to collect the signals transmitted by the same microshock to locate the microseismic source.The failure type of microseismic source is obtained by moment tensor calculation,and the characteristics of microseismic signals in time domain,frequency domain,time-frequency domain and power spectrum are analyzed.The stress state of rock is judged by comparing the analysis results of different types of failure signals of rock in the laboratory. |
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