Research On Monitoring And Warning Of Gas Concentration In Fully Mechanized Mining Watching Based On IWOA-GRU

Gas safety is one of the significant factors that have plagued the safety and production operations of coal mine personnel in China for a long time and have caused serious threats to the safety of coal mine personnel and equipment.As the first site of coal mining,the fully mechanized coal mining watching belongs to the area with a high incidence of gas accidents.In light of this,the study of gas concentration abnormal change trend in the fully mechanized mining watching,to achieve stable gas concentration monitoring and early warning of the abnormal gas concentration trend,which may ensure the protection life safety of coal mine personnel and induce the production of coal resource.The abovementioned aspects have high research value and practical significance.This thesis takes the gas concentration monitoring data of fully mechanized mining watching as the research object.Based on the analysis of the current research status of gas concentration monitoring and early warning methods domestically and abroad,this thesis study the characteristics of the abnormal change trend of gas concentration in fully mechanized mining watching,and confirming the numbers of fully mechanized mining face gas concentration prediction.Based on the said basis,a gated circulation unit(GRU)neural network is used to predict gas concentration in a fully mechanized mining watching.Aiming at the GRU prediction process which the gradient descent algorithm tends to fall into the local optimal problem,the improved Whale Optimization Algorithm(IWOA)is used to optimize the neural network model numbers and predict the gas concentration.Combining the prediction results with the gray correlation analysis of the predicted samples,the IWOA-GRU gas concentration early warning model is established and applied to the early warning of gas concentration in fully mechanized coal mining watching,and the reliability of the early warning was verified by experimental simulation.In this thesis,based on the coal mine KJ95X safety monitoring platform,a fully mechanized mining watching gas concentration early warning system is designed.Through the interactive application of the host computer,database,and early warning model,the real-time prediction of fully mechanized mining watching gas concentration is achieved,and the fully mechanized watching gas concentration.Realizing the data display,prediction,and early warning functions.In this thesis,through the research of gas concentration data monitoring and early warning methods in fully mechanized mining watching,it can realize accurate prediction of gas concentration in fully mechanized mining face and early warning of abnormal gas rising trend,which can certainly improve and supplement the coal mine safety monitoring system.The abovementioned guarantees the safe production of coal mines and has certain theoretical research value and engineering application value.