Study On Comprehensive Rockburst Warning Based On Microseismic Monitoring In Micangshan Highway Tunnel

Western major projects have launched and implemented,such as "Trans Asian railway network","The Sichuan Tibet Railway","The Sichuan Tibet Highway " and " South Water to North ",which led large projects of Chinese western region with unprecedented speed to flourish,and emerged a large number of deep buried long tunnel engineering.However,the unique geological background conditions in the western region of China often make the construction of major projects in a very complex and fragile geological environment.Most of the rock burst processes are sudden and violent.When a strong rock burst happens,a large number of rock debris speedly thrown out or thrown with the boulder,which often poses a serious threat to the safety of staff and equipment,and so it has become a major technical barrier of the future of Chinese deep underground construction.In this paper,we applied the combining method of microseismic monitoring system and neural network to warn early rock burst,which based on the previous on the rock burst research and combined with the questions of rock burst in TaoBa highway Micangshan tunnel exit section of the excavation process.The main work and research results are as follows:(1)According to the construction site and construction technology,microseismic monitoring programs suitable to Micangshan tunnel of highway tunnel have established.We explore the event location of each sensor array and the error of the actual blasting position,by a comparative analysis of the six different sensors arranged in an array.Finally we concluded that layout scheme of the positioning error is the smallest to layout 9 sensors in double hole,and this scheme is used for the subsequent stages of excavation microseismic monitoring and positioning accuracy reach 20 m.(2)In this paper,the new wave method of velocity determination was adopted,that is to determine wave velocity by microseismic monitoring system software set,according to known blasting point coordinate,coordinates of sensors and P wave arrival time velocity inverse method.The method was used with the simple and rapid characteristic especially for microseismic monitoring of the highway tunnel excavation with the face continuely advancing.we summed up that location error of Pwave arrival pickup and S wave arrival pickup was less than using P wave arrival pickup separately,comparing the effect between different wave arrival pickup scheme and microseismic monitoring results of localization accuracy.(3)Micangshan tunnel microseismic signal database was established,and microseismic signal were divided into three categories: excavation blasting,rock microfracture,machine operations and noise events.At the same time,Three types of microseismic signals were analyzed and identified on several aspects of microseismic signals,such as the waveform characteristics,temporal and spatial characteristics of frequency and amplitude analysis,which improve the accuracy of microseismic monitoring at the working field.(4)We found that rock inside the microfracture activity more intense and microseismic events occur frequently with the impact of the artificial excavation disturbance when the area is under the condition of more complete rock mass,hard rock,groundwater and high crustal stress,through analyzing of the relationship between seismic activity characteristics,the geological conditions and the situation of the three scene of rock burst.Usually this area is called rockburst danger zone.(5)By analyzing of the relationship between microseismic events in space-time distribution rule and rockburst,we found that when the number of microseismic event abnormal enlargement or a sharp increase in the microseismic events and a tendency to aggregate,the time of increase of the number of events is near the rock burst occurrence of the time period,The position of the aggregation of microseismic events is high risk area of the rock burst occurrence.(6)By analyzing of variation of microseismic source parameters before and after the occurrence of rock burst,we conclude that the time when microseismic energy increases logarithmically,microseismic events maximum magnitude number is on the high side or cumulative depending on the volume and the steep energy index dips,are sign of the occurrence of rock burst.It is conducive for qualitative analysis on the rock burst prediction of the scene through drawing analysis for the variation trend of these parameters.(7)By the explaination and disposition of the collected microseismic signal,many rupture information that reflect inner rock rupture source was gotten,such as microseismic event number,microseismic energy,seismic moment,apparent volume.And according to the comprehensive seismic information of the three days before the rock burst,the rock burst neural network prediction model was established based onmicroseismic monitoring,which provides rock burst prediction guidance for on-site follow-up construction stage.