| The property of mineral resources belongs to state,according to the needs of economic development,the state grants mining rights to units or individuals in the form of issuing mining licenses,and serves the development of national economy by orderly mining.In recent years,a small number of lawbreakers have been driven by huge economic interests,who unauthorized exploitation of national resources without a mining license,and the mining methods are very destructive.In order to stop this phenomenon,the law enforcement have taken some of the preventive measures.But most of the existing illegal mining supervision using the administrative level statistics report,masses report,and the public site inspections of carpet method,which are long cycle,poor timeliness,human factors influence,low accuracy,so that some illegal mining regulatory difficulties.Despite using precautions,still seriously affect the normal order of production in mines,which take place safety accidents and serious damage to the ecological environment.Therefore,in order to identify the underground mining area in the condition that people no need to enter the underground or the measured underground space,and make the identification of illegal mining possible.The paper based on the summary of underground illegal mining types and identify approaches,in order to solve three key technical problems: “acquisition of surface deformation information,the association of surface deformation information and the underground mining location,legal and illegal mining screening”,integrated using space earth observation technology,GIS,theoretical achievements of mining engineering technology,which can solve the problem of In SAR obtain the information of the surface deformation in the mining areas.The surface subsidence caused by underground coal mining is taken as the research object,based on the revelation of the surface deformation information and the associated with underground mining face,construct GIS spatial and temporal data model that can integrate data from multiple sources to reflect the geological space and distribution characteristics in the process of multi-level spatial.The identification model of legal underground mining and illegal underground mining are established,and the technology of In SAR and GIS were integrated to realize efficient and rapid ION monitoring of illegal underground mining in mining areas.The research contents and main achievements of this paper are summarized as follows:(1)The research and development status of In SAR technology for surface deformation monitoring in mining areas are summarized,and further combing the imaging principle of In SAR technology,as well as the basic principle,data processing flow and working method of D-INSAR,PS-INSAR and SBAS-INSAR.Analysis the main error sources of In SAR deformation detection,and the main influencing factors of In SAR in deformation monitoring in mining areas are analyzed from the aspects of deformation gradient,decorrelation etc.At the same time,the integrated application of In SAR and GIS technology as well as the research status of underground illegal mining monitoring are summarized.(2)Put forwards a kind of illegal mining underground recognition oriented GIS spatial temporal data model.The mine underground mining induced geological phenomena and dynamic process,and combined with the actual needs of underground illegal mining real-time monitoring,this paper introduces the support geological events many factors driving the basic concept of spatial-temporal data model of GIS and frame structure,which define the various geological objects and the related geological events.Meanwhile,the spatial and temporal variations of mining subsidence process was simulated and described,build support for the geological process of time and space dynamic expression of GIS data model,and the various classes of mining subsidence structure and spatial-temporal database table structure are described in detail,based on this,put forwards the integration of In SAR and GIS technology for underground illegal mining recognition method,and constructs illegal mining recognition platform architecture,provide secure platform for different types of illegal mining event identification and monitoring.(3)Proposes an underground unlicensed mining identification method based on D-In SAR mining subsidence characteristics.The underground unlicensed mining events that cause large scale surface deformation,an algorithm model for automatically delineating surface mining subsidence area is constructed,and a dual-track D-In SAR monitoring scheme with sequential adjacent-type is designed.By elaborating the process,method and related parameters of D-In SAR data processing,accurate access to the area within the scope of the differential interference figure,according to the surface subsidence area caused by underground mining unique space,geometry,deformation features,built an algorithm model,which can fast and accurate delineated the surface mining subsidence area from distribution range larger differential interference figure.On this basis,realize the recognition from the mining subsidence area is delineated illegal mining events,and comparative analyzed the result of the recognition and field validation.By comparison with data and on-the-spot investigation to verify the identification of illegal underground mining results are basically identical with actual situation,which has good recognition effect,and pinpoint the location of the mines is accurate,and the gap of the actual location is generally controlled in the range of 20 m.(4)Proposes an unlicensed underground mining recognition method,which integrated PS-In SAR and optical remote sensing.For small scale deformation and hidden unlicensed mining events under buildings,these illegal events are shallow coal resources exploitation,and the buildings on the ground in the longer time sequence can remain strong and stable radar scattering characteristics,through joint PS-In SAR technique and high optical remote sensing to extract PS point set subsidence information of the surface buildings(residents),and the extracted information of building subsidence analysis by deformation characteristics of temporal and space.This paper proposes an algorithm that from the larger coverage building subsidence information can quickly and accurately detect the suspected illegal mines.At the same time,taking Shandi village in the suburb of Yangquan City of Shanxi Province as the research object,the high-resolution data of quickbird02 and worldview02 and 20 PALSAR image data were selected for experimental research.Two illegal coal mining sites occurred in the village from December 29,2006 to January 9,2011 were detected.The detected illegal coal mining points were compared with the historical investigation data,and the local area was obtained The accuracy rate is 40% and the detection rate is 66.67%,and the mining time is basically consistent.It shows that the method is feasible and has certain engineering applicability and value.(5)Combined with In SAR technology and mining subsidence prediction method,an inversion method for underground goaf location based on trans-boundary mining identification is proposed.Firstly,the spatial-temporal relation model and underground mining surface is established according to the mining subsidence principle;then,the deformation information is accurately obtained by using In SAR;finally,according to the spatial-temporal relation model,the specific location and other parameters of underground inclined coal seam goaf location are reversely calculated.Compared with other similar methods,this method is not dependent on the complex nonlinear model,and the complete parameter,therefore has higher engineer application value.In order to confirm the applicability of the proposed method,using FLAC3 D software to simulate experiment and analysis,and choose the Fengfeng mining's 132610 working face and 11 Radar-sat scene-2 image data to carry out experimental study.The results show that the average relative error of goaf location is6.35%.Compared with the similar algorithms based on complex nonlinear model,the average relative error is reduced by 1.75% and 6.25% compared with the algorithm that ignores the coal seam dip angle.The method proposed in this paper can provide a new monitoring method for further identifying and discovering the cross boundary mining events deep underground Form and way.There are 94 figures and 12 tables,220 references in this paper. |
PDF Full Text Request