Mining coal-rock interface nodal GPR rapid dynamic detection system and experi-mental research
Coal-rock interface recognition technology is one of the key technologies for intelligent mining in coal mines.Based on high-frequency radar wave detection technology,high-precision detection of coal-rock interfaces can be achieved with mining,but there are still safety risks for equipment caused by rib spalling and roof caving in ultra-high mining heights(≥6 m)in mines,as well as spatial restrictions on equipment passing through during sudden changes in mining height(mining height ≤ 2 m).Based on previous work,this paper proposes a rapid dynamic detection system and method for coal-rock interfaces in mines using nodal GPR.The main contents include:① Explaining the principle of the nodal GPR observation system in mines,designing a coal-rock interface recognition observation system plan and radar an-tenna sensor installation method based on the actual environment of the mine working face;② Studying and proposing a nodal acquisition control system and information interaction transmission design plan to achieve dynamic data acquisition,control,and storage;③ Studying and proposing enhanced processing methods for sensor detection data and coal-rock in-terface recognition algorithms based on nodal acquisition methods and radar reflection echo characteristics of coal-rock in-terfaces,which can effectively achieve intelligent recognition and tracking of coal-rock interfaces,as well as calculation of coal seam thickness and spatial coordinates.To verify the feasibility of this method,multiple geological radar antenna sensors with a center frequency of 1.5 GHz were used for physical model verification experiments,and a comparative ana-lysis of nodal data acquisition and continuous data acquisition results was conducted.The experimental results show that both nodal and continuous acquisition methods can effectively identify coal-rock interfaces.Compared with continuous acquisition methods,the nodal detection method proposed in this paper can achieve rapid and dynamic repetitive data ac-quisition,with a single acquisition time controlled within 10 seconds,an average error of 1.07 cm for coal seam thickness detection results,a maximum error of 1.47 cm,and an average error percentage of 7.64％.This method provides technical support for dynamic high-precision detection of coal-rock interfaces in intelligent mining in mines.
coal and rock identificationgeological radarnodal GPR observation systemerror analysis
NETL
NSTL
万方数据
维普
