| With the coal mine enters deep mining operations,the danger of coal and gas outburst becomes increasingly serious.AE and EMR gas monitoring and early warning technology of has been widely used in coal and rock dynamic disasters.However,the AE and EMR gas monitoring technology in the tunnels is not perfect enough,there are many factors affecting the accuracy of AE and EMR gas monitoring,and various problems such as the existence of various AE and EMR signals and the low accuracy of early warning.Based on the above problems,this paper constructs a simulated down hole AE and EMR interference system in the laboratory,the data transmission and monitoring sensitive parameters of AE and EMR gas monitoring technology were studied.Based on the actual situation of Jinjia Coal Mine,a real-time online monitoring system for AE and EMR gas was constructed,various factors affecting acoustic and electrical monitoring data were selected and optimized?Based on this,the source noise reduction was completed.Based on the dangerous precursor information,a comprehensive early warning system for AE and EMR gas was established,a good early warning effect was obtained.The main research results are as follows:?1?Through the laboratory simulation of the underground AE and EMR interference system,the various links of the simulated underground data transmission are realized,it is based on this,the optimal receiving frequency of the AE probe is1300Hz.The EMR signal decreases with the increase of the monitoring distance,the effective value is determined as the abnormal response sensitivity index.?2?Constructed a real-time online monitoring system for AE and EMR gas,selecting and optimizing various factors affecting AE and EMR signals,It was determined that the sensitive index of the AE and EMR signal is the effective value and the middle line of the roadway is the best monitoring position,the best monitoring distance is between 6-12m.?3?The characteristics of the AE and EMR signal of different interference sources were tested,the characteristic laws of the main interference signals are determined to be two types:one is the tip pulse type,and the other is the"n"type interference signal.Based on the above characteristics of the interference signal,the filtering method combined with the rate of change judgment and the recursive least squares method is adopted to realize the automatic identification and filtering of the AE and EMR interference signals.?4?Selecting and optimizing the impact of statistical time on early warning effects,It was determined that 8h is the best statistical time for highlighting the regularity and 24h is the best statistical time compared with the conventional index.It was determined that the acoustic and electrical gas signal has a great correlation with the conventional predictive index?h2 and achieves significant correlation.?5?Based on the AE and EMR gas characteristics of the 13 coal-rock dynamic disasters in Jinjia Coal Mine,a dynamic early warning system for coal and gas outburst based on PCA and case-based reasoning was constructed.The verification and analysis were carried out,and a good early warning effect was obtained.The above research results have practical guiding significance for the sound and electricity monitoring technology of coal and gas outburst,it have played a certain role in the standardization of sound and electricity monitoring technology,it has practical guiding significance for coal and gas outburst warning.In addition,1 paper was published based on the results of this study,including 1articles published in national core periodical. |
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