Research And Implementation Of Mine Earthquake Positioning System Based On Deep Learning And Swarm Intelligence

With the increase of mining depth of mine resources in my country,the frequency of mine earthquake events that are disturbed by mining has gradually increased.Mine earthquake events threaten the safe mining of mine resources.Efficient monitoring and accurate positioning of mine earthquake events have become the key work that urgently needs to be solved.Compared with earthquakes,mine earthquakes caused by mining have the characteristics of fast response time and shallow source,which are easy to cause underground roadway damage and ground vibration.Traditional microseismic monitoring systems mostly rely on manual work,mainly to analyze the lowdimensional characteristics of waveforms,positioning accuracy.Low,time-consuming and labor-intensive.With the rise of emerging technologies such as artificial intelligence and big data,the use of information technology to replace traditional methods and the detection of mine earthquake hazards have become the main development trend of the coal mining industry at this stage,and related concepts such as mine big data and smart mines have come into being.pregnancy.Therefore,in view of these problems,this paper proposes a research on mine earthquake location method based on deep learning and swarm intelligence,and develops software to realize system functions.Based on the analysis of a large number of domestic and foreign literatures,this paper proposes an hourly window P-wave picking method based on the CGAS model and a quantile difference based on seagull optimization for the problem of picking up the arrival time of the P-wave in the mine earthquake detection system and the problem of mine earthquake location.The value mine earthquake location method,in which the hourly window P-wave picking method of the CGAS model uses the deep learning model training method instead of the traditional energy ratio method for picking,while the seagull optimization quantile difference mine earthquake location method uses The swarm intelligence optimization algorithm is combined with the objective function proposed in this paper to find the optimal positioning.After experimental verification,the algorithm in this paper provides a solution to the problem of picking up and locating when the mine earthquake arrives from multiple angles and aspects.Compared with the traditional algorithm,the accuracy and anti-noise performance have been improved,and it has an important reality for the research of mine earthquake.significance.The mine earthquake location system is developed based on the stand alone application.On this basis,Python,My SQL and other related languages are used as the main development languages.Multi-threading,high concurrency and other related technologies are used in many places in the system to improve the running speed of the system.The system is developed in the way of objects to improve the usability and scalability of the system and ensure that the subsequent development and maintenance of the system is more efficient.