289 / 2018-04-29 07:43:00

Analysis of Microseismic Monitoring Data and Early Warning Model of Rock Burst in Coal Mine

rock burst,Microseismic information,Monitoring and early warning,Spatial distribution,Genetic algorithm

矿山动力灾害 > 岩爆冲击

With the widespread application of microseismic monitoring systems in coal mines, a amount of microseismic monitoring data has been accumulated. In order to solve the problem of poor generalization ability of the early warning model, the article combines the data analysis method to establish a model that can be automatically adjusted. At the same time, the information of the monitoring data is further excavated. Firstly, starting from the two angles of time and space, the temporal variation law and spatial parameters of microseismic events before high-energy microseismic events or rockburst are analyzed. Secondly, according to the law of change, two important influencing parameters, frequency ratio and spatial dispersion, were selected and a preliminary warning model was established. Then, the R-value scoring method is used to estimate the early warning capability of the model, and the genetic algorithm is used to automatically determine the parameters of the early warning model. Finally, use the new data to test the model's early warning capabilities. The results show that this method has a higher prewarning capability and can quantitatively demonstrate the state of early warning, which is convenient for practical application. In addition, as a statistical result, this model is more suitable for analyzing the period of high frequency of microseismic events. With the increased sensitivity of microseismic monitoring equipment, the accuracy of the warning can be further improved.