424 results about "Subsidence" patented technology

The invention discloses a coal mining subsidence area surface crack intelligent extraction method based on an improved Transform model, and belongs to the technical field of remote sensing image processing. Firstly, an unmanned aerial vehicle carrying a high-resolution optical camera is used for collecting images, the image overlapping rate of 70%-80% is guaranteed, and a training data set is constructed through professional labeling, cutting screening and data enhancement. The encoder of the innovative model is very distinctive, and the adaptive multi-scale patch mapping layer can dynamically adjust the patch size according to the local complexity of the image and efficiently extract features; double-attention fusion is combined with optimization position coding, and long-distance dependency capture is enhanced; and the calculation amount and the overfitting are reduced by the dynamic sparse connection full-connection layer. Residual attention enhancement pyramid pooling and a space-channel attention bottleneck mechanism are adopted, key features are highlighted, and noise is suppressed; and a breakpoint detection and connection rule determination module is utilized to realize complete restoration of the ground fracture. After the data set is used for training a model, deployment is carried out, and through preprocessing, encoding and decoding and post-processing, ground fracture information can be accurately obtained, and a data foundation is built for mining area safety management and geological disaster prevention and control.

The invention provides a mine water disaster monitoring and early warning method and system based on multi-source heterogeneous data fusion, and the method comprises the steps: collecting multi-source data of a mining area, carrying out the time-space alignment of the multi-source data, and generating a data set, the multi-source data comprising remote sensing data; preprocessing the data, inputting the preprocessed data into a multi-modal fusion network, and extracting surface water body distribution, lithologic permeability, underground water level and structural fracture characteristics to obtain a three-dimensional hydrogeological static model; the hydrological numerical model based on physical driving is coupled with the static model, and the dynamic model is used for simulating the dynamic change of an underground water flow field and a pollutant diffusion path; based on the dynamic model updated in real time, multi-target collaborative evaluation is carried out to evaluate the mining area water resource, ecological and social collaborative effect; and calling an unmanned aerial vehicle to inspect a leakage position or a settlement position in the hydrogeological risk map based on a multi-target collaborative evaluation result. According to the method, the prediction accuracy is improved through the multi-source data.

The invention provides a ground surface settlement monitoring method and system fusing Beidou and InSAR data. The method comprises the following steps: receiving positioning data from a Beidou satellite system and earth surface deformation data acquired by a synthetic aperture radar interference measurement system; based on the positioning data and the earth surface deformation data, correcting the earth surface deformation data according to the environmental factors through a space-time fusion model to obtain corrected earth surface deformation data; by means of the corrected surface deformation data, a multi-stage analysis technology is adopted, the development trend of surface subsidence is determined, a surface subsidence distribution diagram is generated, and the surface subsidence distribution diagram is used for displaying spatial distribution characteristics of surface subsidence; and according to the ground surface settlement distribution diagram, the future ground surface settlement condition is monitored by using the space-time fusion model, and a ground surface settlement monitoring report can provide a scientific basis for early warning and prevention of geological disasters. The ground surface settlement monitoring efficiency and monitoring effect are improved.

The invention relates to the technical field of geological exploration, and discloses a water-rich sandy stratum tunnel base settlement prediction method and system, and the method comprises the steps: constructing a multi-source cooperative exploration system; deploying a sanding-seepage-stress coupling model at an edge computing node, and mining the relevance of data of different dimensions through a space-time attention fusion network; based on the prediction matrix and mineral exploitation working condition parameters; when the predicted settlement exceeds a safety threshold value or the sanding expansion rate is abnormal, a high-precision remeasurement mechanism is triggered, and a cross-hole radar and acoustic logging combined verification module is activated; and iteratively optimizing coupling model parameters by adopting a transfer learning algorithm through deviation analysis of measured data and a prediction result. According to the method, a scientific basis is provided for stratum stability evaluation and prevention and control measure formulation in the mineral exploitation process, and the probability of engineering risks caused by base settlement of the water-rich sandy stratum is effectively reduced.

The invention relates to the technical field of measurement, in particular to a method and device for measuring a subsidence basin boundary of a coal mine goaf, and the method comprises the steps: obtaining synthetic aperture radar SAR image data of the subsidence basin boundary of the coal mine goaf, and carrying out the preprocessing of the data, and generating a registered SAR image data set; establishing a first multi-main image interferometric phase data set, and inverting a mining process according to the central position of the differential interference fringe pattern; carrying out stacking processing on the differential interferograms to obtain an average rate diagram of the mining-induced surface deformation, so as to delineate the range of the mining-induced surface deformation; and generating a single main image differential interferometric phase data set and a second multi-main image interferometric phase data set, and establishing a coupling image interferometric phase data set to realize high-precision measurement of the boundaries of the subsidence basins of the coal mine goaf. Therefore, the mining process can be reconstructed under the condition of lack of mining area historical data, high-precision measurement of the subsidence basin boundary range and the subsidence magnitude of the coal mine goaf is realized, and the refinement level of a monitoring result is improved.

The invention relates to the technical field of coal mining safety monitoring, and discloses a coal mining subsidence space-time evolution intelligent prediction method, which comprises the following steps: acquiring multi-dimensional geological dynamic data such as surface displacement, underground water pressure and rock stratum stress of a coal mining area, extracting a space-time characteristic sequence by using a GCLSTM algorithm, and calculating a space-time fluctuation coefficient; extracting a principal component vector through spectral decomposition, mapping to obtain a space-time correlation weight, dynamically correcting an original prediction value to generate a fusion prediction value, and judging a subsidence space-time evolution trend; constructing a three-dimensional subsidence curved surface model to identify a high-risk area and generate graded early warning; and establishing a joint optimization model to solve an optimal mining path, and generating a subsidence risk minimization scheme. According to the method, intelligent analysis of multi-dimensional data fusion and spatial-temporal characteristics is realized, the prediction accuracy is improved, an effective means is provided for coal mining subsidence prevention and control and safe mining, and the method has a remarkable engineering application value.

The invention relates to the technical field of land degradation monitoring, in particular to a remote sensing comprehensive monitoring method for land degradation of a coal mining subsidence area. The method comprises the following steps: establishing a prediction model, obtaining a predicted soil erosion intensity sequence, a predicted primary productivity sequence, a predicted surface water content index sequence and a predicted arid remote sensing monitoring index sequence by utilizing the prediction model, and then respectively obtaining a first trend index, a second trend index, a third trend index and a fourth trend index at the current moment; obtaining a first index, a second index, a third index and a fourth index by using the soil erosion intensity, the primary productivity, the surface water content index, the arid remote sensing monitoring index, the first trend index, the second trend index, the third trend index and the fourth trend index at the current moment; and obtaining a land degradation degree index of the coal mining subsidence area based on the first index, the second index, the third index and the fourth index at the current moment. According to the method, the land degradation degree of the coal mining subsidence area can be accurately judged.

The invention provides a sedimentation inversion prediction method based on water-soil coupling and well reservoir dynamic feedback, which comprises the following steps: by collecting geological, hydrological, deformation monitoring and engineering construction data, constructing a three-dimensional geologic model containing a shallow unconsolidated formation and an underlying bedrock layer, and setting physical boundary constraints; establishing a water-soil bidirectional coupling model, integrating a seepage model and a deformation model, and realizing bidirectional coupling through a dynamic feedback mechanism; calculating the leakage / extraction amount based on the dynamic water level in the well and the hydraulic long pipe model, dividing the layer leakage amount and feeding back the layer leakage amount to the seepage model; model parameters are inversed and calibrated in combination with actually measured data; and finally, predicting a settlement spatio-temporal evolution process based on the calibration model, and generating a risk prevention and control scheme in combination with building settlement indexes. The method has the advantages that comprehensive information is obtained through multi-source data fusion, the deformation mechanism model considering the water-soil bidirectional coupling and the well storage effect is established, and the defects in multi-factor coupling, boundary condition processing and parameter inversion in the prior art are overcome.

The invention relates to the technical field of mining subsidence prediction, and discloses a complex working face mining subsidence prediction method and system.The complex working face mining subsidence prediction method comprises the steps that a geological feature coding network is constructed, and complex geological information is converted into digital feature vectors; constructing a subsidence parameter inversion model based on deep learning; the problem of insufficient new mining area data is solved by applying a transfer learning framework; analyzing and optimizing model performance through parameter sensitivity; efficient subsidence calculation is realized based on a non-uniform block model; according to the method, the limitation that a traditional subsidence prediction method depends on empirical parameters is broken through, the prediction precision under the complex geological condition is improved, the dependence on monitoring data is reduced, the calculation efficiency of a large-scale block model is improved, the multi-working-face superposition subsidence effect can be accurately simulated, and the method is suitable for being popularized and applied. Powerful support is provided for safe mining of mines and environmental protection.

The invention relates to the technical field of geological engineering, in particular to a comprehensive evaluation method and system for a mine geological environment, and the method comprises the following steps: collecting mine surface geological data based on a target mine region, collecting vegetation types and vegetation coverage area data, evaluating the occurrence probability of landslide and land subsidence of a plurality of regions of a mine, and obtaining a comprehensive evaluation result; and obtaining a surface risk assessment result. According to the method, the accuracy and the reliability of risk assessment are improved by integrating the surface geological data and the vegetation coverage data and combining meteorological information and topographic analysis, the judgment for geological stability is enhanced by combining fixed-point assessment and stratigraphic analysis, so that early warning for a hidden danger area is more timely and specific, and the risk assessment accuracy and the risk assessment reliability are improved. By monitoring surface deformation in real time and combining long-term data analysis, a more dynamic and continuous geological environment change trend is provided, mining strategies and disaster prevention and reduction measures can be adjusted in time, and the environmental influence of mining activities is reduced.

The invention belongs to the technical field of underground engineering intelligent construction, and particularly discloses a shield tunneling performance prediction method and system based on an interpretable BO-LGBM model, and the method comprises the steps: receiving detection data in a shield tunneling process, and determining tunneling parameters, geological parameters and karst parameters based on the detection data, so as to construct an input feature set; constructing an LGBM model, performing multi-stage screening on the input feature set to obtain a comprehensive feature importance sequence, and determining key target features corresponding to model prediction influence according to the comprehensive feature importance sequence; on the basis of key target features, a Bayesian optimization algorithm is used to optimize hyper-parameters of the LGBM model, and a trained BO-LGBM prediction model is obtained; the BO-LGBM prediction model is used for predicting ground surface settlement, tunneling efficiency, specific energy and overexcavation rate of the detection data; and obtaining a performance index based on the trained prediction model so as to evaluate model performance and prediction precision. According to the invention, the model prediction accuracy of the shield performance can be improved.

The invention belongs to the technical field of mining, and provides a numerical simulation and transfer learning combined mine surface deformation prediction method, which comprises the steps of carrying out numerical simulation on ore body mining and carrying out preprocessing to obtain source domain data, calculating an actual surface deformation value of a mining area to obtain target domain data, constructing a surface settlement prediction model comprising an LSTM layer, a respe layer and a DCNN layer, and carrying out migration learning on the surface settlement prediction model. Inputting the source domain data into the ground surface subsidence prediction model to pre-train the ground surface subsidence prediction model, adding a full connection layer to the pre-trained ground surface subsidence prediction model, setting the full connection layer to be in a trainable state, taking the target domain data as a target domain for transfer learning of the frozen ground surface subsidence prediction model, and training again to obtain a ground surface subsidence prediction model; parameters of the frozen ground surface settlement prediction model are finely adjusted, weights are updated, a prediction model is obtained, to-be-predicted mine field geological data are input into the prediction model for prediction, and a predicted ground surface settlement value result is obtained. The method can predict the deformation of the earth surface in different mining stages.

The invention discloses a method for judging the influence of coal mining on next-time mining damage of a high-pressure gas pipeline, and relates to the technical field of pipeline safety. Comprising the following steps: acquiring basic general situation data and actual measurement data of a research area in which a to-be-measured sub-high-pressure gas pipeline is laid; determining a predicted direction according to the direction relationship between the measured data of the research area and the general situation of the research area; the predicted direction is compared with the mining direction of the working face general situation, and the coal seam mining direction of the research area is determined; performing multi-angle subsidence prediction on the earth surface around the sub-high-pressure gas pipeline to be measured through the prediction model to obtain an earth surface movement deformation value; fourier fitting is carried out on the surface movement deformation value, boundary conditions of the research area are input into a fitting function, and a failure criterion of the to-be-tested sub-high pressure gas pipeline is obtained; and determining the mining damage of the to-be-detected secondary high-pressure gas pipeline according to the failure criterion. Whether the secondary high-pressure gas pipeline is in the safe state or not can be quickly judged, and the safety and stability of the coal mining process are ensured.

Disclosed are a joint landslide monitoring system and method. The system includes: a high-frequency electromagnetic wave monitoring module configured to continuously emit electromagnetic wave signals into a monitoring area, perform interference processing on signals received by a receiving antenna to obtain target signals, and obtain surface deformation information of the monitoring area according to a phase difference of the target signals; a low-frequency seismic wave monitoring module configured to propagate seismic waves downward from a ground surface in the monitoring area, receive reflected waves from a creeping medium that the seismic waves encounter, obtain frequency-domain interference characteristics of internal creeping; and determine a longitudinal force on a 3D stratigraphic landslide mass shear surface; and a cloud platform configured to determine a maximum subsidence amount and a subsidence velocity of the monitoring area, and issue alert information when the maximum subsidence amount or the subsidence velocity exceeds a preset range.

The invention discloses a coal mine subsidence monitoring method based on multi-source data fusion, and belongs to the technical field of coal mine subsidence monitoring and safety management. Inputting the fused data into the model to automatically identify boundaries and features of the subsidence area; constructing a relationship between surface deformation and underground mining parameters, and obtaining optimal solutions of parameters such as mining depth and the like by adopting Bayesian posterior inversion in combination with MCMC sampling; calculating the volume of the goaf according to the inversion parameters and estimating the mining quantity; and updating the data, and triggering multimode early warning based on the threshold value of the subsidence amount or the rate. The technical problem that the monitoring precision is low due to the fact that a traditional coal mine subsidence monitoring technology depends on a single data source is solved.

The invention discloses a mining area coal mining collapse cultivated land reclamation elevation determination method, and relates to the technical field of mining area coal mining collapse cultivated land reclamation, and the method comprises the steps: obtaining a mining area collapse region, a coal mining plan, an underground coal occurrence condition, a cultivated land damage boundary and a land use type, and carrying out the preprocessing; according to the pre-processed mining area collapse area, obtaining original surface elevation data before mining of the mining area through satellite image analysis; based on the preprocessed coal mining plan and underground coal occurrence conditions, predicting surface subsidence amount data at different stages by adopting a probability integral method, and superposing the predicted subsidence amount data and the original terrain elevation data to generate subsidence surface elevation data; through satellite image analysis and a probability integral method, the accurate reclamation elevation determination method for the mining area coal mining collapsed cultivated land is provided, firstly, original surface elevation data before mining of the mining area is obtained through satellite images, and the data obtaining precision and efficiency are remarkably improved;

The invention discloses a reservoir immersion prediction method, belongs to the technical field of reservoir immersion prediction, and can solve the problem that an existing reservoir immersion prediction method does not consider additional subsidence generated after loess immersion saturation collapse, so that the applicability is poor. The method comprises the steps that S1, the stratum type of a reservoir stratum is determined, and the collapsibility of the reservoir stratum is determined according to the stratum type; s2, determining the buried depth of the critical underground water level immersed in the reservoir according to the collapsibility; and S3, determining the groundwater heap water level after the reservoir stores water, and performing reservoir immersion prediction according to the groundwater heap water level and the critical groundwater level burial depth. The method is used for reservoir immersion prediction.

The invention relates to a geological disaster change detection method and system based on an improved twin U-Net and a central surrounding double-flow network. According to the method, an improved twin U-Net network is constructed as a feature extraction trunk, and a deformable convolution module is integrated in an encoder to adaptively adjust a receptive field; a central surrounding double-flow network is embedded in a decoding path, detail features are extracted through a central flow path, and a global context is obtained through a surrounding flow path; a feature fusion module is designed to realize double-path feature deep fusion, and a gating attention unit is adopted to calibrate feature response; introducing a contrast feature learning mechanism to reinforce feature space clustering characteristics; multi-modal degradation enhancement training is implemented to improve the robustness of the model; and an objective function containing difference perception loss and feature comparison loss is minimized through end-to-end joint optimization. The method can accurately identify geological disaster change areas such as landslide, debris flow and land subsidence, and has the advantages of high detection precision and strong anti-interference capability.

The invention provides an intelligent prediction method and system for settlement of a TBM penetrating through a pebble stratum, and belongs to the technical field of stratum settlement prediction. The method comprises the following steps: acquiring ground surface monitoring point position information, excavation surface position information and burial depth, inputting the information into a first deep neural network model, and acquiring and outputting tunnel vault displacement, haunch convergence and ground surface settlement; the second deep neural network model takes a position coordinate formed by earth surface monitoring point position information, excavation surface position information and burial depth and earth surface settlement as input, and outputs earth surface elastic modulus and Poisson ratio; obtaining stress-strain components of ground surface settlement, and constructing a control equation and boundary conditions based on the stress-strain components, the elastic modulus and the Poisson's ratio; obtaining prior geological information by using the residual error of the control equation; and by taking the control equation, the boundary condition and the prior geological information as constraint conditions, obtaining a settlement prediction value when the TBM passes through the pebble stratum based on the tunnel vault displacement, and realizing accurate prediction of the settlement of the pebble stratum.

The invention discloses a side slope monitoring and early warning device, relates to the technical field of side slope monitoring, and solves the technical problem that side slope monitoring is limited due to lack of corresponding monitoring measures for deformation or collapse of a soil layer in a side slope. The monitoring and early warning structure is mounted on the slope of a side slope body for monitoring; the monitoring and early warning structure comprises a plurality of mounting plates which are mounted on the inclined surface of the slope body in an attached manner; a plurality of groups of anti-skid components for protecting and stabilizing the slope surface of the slope body are arranged between every two adjacent mounting plates; according to the invention, the change of the soil layer in the slope body can be monitored, and the monitored change such as collapse and sinking of the soil layer can be transmitted to the terminal, so that early warning of the change of the slope body can be conveniently and timely carried out, the monitoring and early warning range and convenience of the slope body can be expanded, the slope surface of the slope body can be protected, large stone sliding on the slope surface can be reduced, and the safety of the slope body can be improved. And the safety of slope monitoring and early warning is improved.

The invention relates to the field of geological exploration, in particular to an intelligent analysis method and system for geological exploration data of a coal mining subsidence area. The invention discloses an intelligent analysis system for geological exploration data of a coal mining subsidence area. The intelligent analysis system comprises a data acquisition module, an underground three-dimensional model construction module, a foundation stability evaluation module, a residual deformation prediction module and a suitability judgment module. According to the method, multi-source data such as drilling data, geophysical prospecting data, remote sensing topographic data, monitoring actual measurement data and geotechnical test data are comprehensively analyzed, a unified underground three-dimensional model is constructed, and the limitation of data isolation of a traditional exploration method is broken through; according to the method, through drilling and geophysical prospecting bidirectional complementary correction and combination of a settlement monitoring sequence and static attributes, a more accurate and comprehensive geological exploration result is provided for a coal mining subsidence area, and the accuracy of foundation stability evaluation and deformation prediction is remarkably improved.

The invention relates to the technical field of a seabed substrate advanced detection device and method for a seabed mining vehicle, and provides a seabed substrate advanced detection device and method for a seabed mining vehicle, which can simultaneously obtain submarine topography and landform and detect multiple parameters of a seabed substrate. The deep sea detection system is matched with a mine car to ensure smooth proceeding of a rear mine car in deep sea bottom detection, and comprises a sea surface data processing system and a frame with the cross section in a structure shaped like a Chinese character'tian ', a master control device, a signal receiver and at least four detection modules arranged in a matrix are arranged on the frame, and the master control device is used for controlling the detection modules. The signal receiver is used for transmitting information of the detection module and the sea surface receiving device; the detection module comprises a side-scan sonar module used for rapidly obtaining the topography and landform in front, a transverse push toothed plate used for cutting into a soil body, a turbidity meter module used for measuring the concentration of suspended particles and dissolved matters in the seabed, and a pressing plate module used for obtaining the bearing capacity and the subsidence index of the seabed sediment.

The invention belongs to the technical field of geological disaster monitoring, and discloses an automatic geological disaster monitoring device and monitoring method. The method comprises the following steps: completing joint monitoring of surface goaf deformation on the ground; for a bent sinking zone, a fissure zone and a caving zone of the goaf, an electrical method system, a micro-seismic monitoring system and a distributed optical fiber sensor are arranged underground, dynamic tracking and monitoring of underground resistivity, fissure zone expansion, caving zone rock mass breaking change and the boundary of the goaf are conducted respectively, and delineation of underground abnormal bodies is completed; and cooperative monitoring: completing cooperative dynamic coupling monitoring of deformation processes of the curved sinking zone, the fissure zone and the caving zone of the goaf. According to the method, the accurate delineation of the underground abnormal body is completed; and dynamic coupling monitoring of ground and underground deformation of the coal mine goaf is realized.

The invention relates to the technical field of geological safety risk monitoring and early warning, and discloses a plain type city geological safety risk multi-disaster multi-parameter monitoring and early warning method, which comprises the following steps: S1, determining a plain type city geological safety risk type according to a plain type city geological survey result and a city geological safety risk survey evaluation result, comprising land subsidence, surface collapse, ground fissures and flood disasters, causes, dynamic characteristics and evaluation indexes of urban geological safety risks are analyzed, and a preliminary evaluation result is obtained; and S2, according to the preliminary evaluation result, through dynamic adjustment of an early warning threshold value and a multi-parameter early warning model, accumulation of long-time sequence monitoring data and clearness of a geological safety risk development trend, the precision of the monitoring early warning model can be improved, the research of a geological safety risk monitoring early warning system can be promoted, and the research efficiency can be improved. And the accuracy of monitoring and early warning of the plain type city geological safety risk is improved.

A method for screening a key stratum for overburden separation grouting in a coal mine includes: selecting overall analysis objects based on coal mine planning; conducting a primary screening of the analysis objects based on a scope of a subsidence zone; conducting a secondary screening of the analysis objects based on whether there is an old goaf; determining key stratums for screened-in analysis objects, prioritizing the key stratums based on a number of separation spaces and a range of a separation height, setting a safe height based on a diversion fissure zone, and prioritizing numbers of groutable layers based on a potential separation space and a water resistance of a rock stratum; prioritizing the groutable layers based on a fault impact; and comprehensively analyzing grouting priority levels of the key stratums based on results of the three prioritizations, and grouting separation layers of the key stratums in order of priority.

The invention discloses a key layer presplitting settlement control method based on overlying strata fracture angle arrangement. The method comprises the steps that geological mining parameters of a target mine are collected and determined; based on the physical and mechanical parameters of each rock stratum, determining the horizon height of the key stratum in combination with a thick and hard rock stratum judgment criterion; according to coal seam mining parameters and overlying strata lithology, the height of a water flowing fractured zone is judged, and high and low horizon classification is conducted on the water flowing fractured zone by combining the horizon of the key horizon; according to the development law of overlying strata damage along the fracture angle from bottom to top, the presplitting position in the horizontal direction of each layer key layer in the presplitting range is calculated and determined, and full-section directional presplitting cutting is carried out; based on thick and hard rock stratum mining-induced stress distribution characteristics and a damage deformation transmission mechanism, a working face moving boundary and a reduction distance of a building (structure) protection coal pillar after key stratum presplitting are calculated and determined. According to the method, presplitting implementation is guided based on the key layer fracture rule, and a new technical approach is provided for subsidence control of the mining area.

The invention discloses a deep filling and mining subsidence prediction method considering secondary compression of composite lithologic gangue, belongs to the technical field of subsidence prediction, is used for subsidence prediction, and comprises the steps of calculating the deflection of overlying roofs of a caving goaf and a filling goaf, obtaining a subsidence curve of ultra-thick sandstone based on a similarity principle, and calculating the subsidence curve of the ultra-thick sandstone. And a subsidence curve of the surface soil layer is obtained by combining a random medium theory, and a corresponding subsidence value of the surface soil layer can be obtained by substituting the coordinate value of any point on the x axis, so that subsidence prediction is realized. The random medium theory comprises the steps that bending and sinking of the huge thick sandstone are regarded as middle-shallow non-uniform coal seam mining, the bending and sinking area of the huge thick sandstone is decomposed into limited number of infinitely small coal seam units, and surface movement is regarded as superposition of surface subsidence caused by mining of each small mining unit decomposed by the sinking area of the huge thick sandstone. According to the method, accurate surface subsidence prediction is achieved, a huge thick sandstone surface subsidence space calculation model is deduced in combination with the similarity theory, and the difference between a calculation result and numerical simulation is only 10 mm.

The invention relates to the field of coal mining subsidence control, in particular to a floor rock stratum chemical modification expansion subsidence reduction control method. Comprising the steps of determining the range of a floor failure zone below a coal seam, and selecting a rock stratum with a certain thickness below the floor failure zone as an isolation protection zone; the lower part of the isolation protection belt is a chemical modified expansion belt; selecting a chemical agent for expansion according to mineral components of the chemically modified expansion zone rock stratum; directional drilling is conducted in a working face roadway, a directional drilling horizontal section is constructed in a chemical modified expansion zone, and directional drilling is conducted in the advancing direction of a working face towards the open-off cut direction; the expansion band is chemically modified through directional drilling fracturing; and after the working face is pushed over the horizontal section of the directional drilling hole and before the working face reaches the hole opening of the directional drilling hole, a chemical agent is injected into the chemical modified expansion zone through the directional grouting drilling hole. According to the method, the base plate rock stratum is chemically modified to generate an expansion effect, so that the base plate rock stratum is lifted to support the goaf, the subsidence of the overlying rock stratum is reduced, and the surface subsidence is controlled.

The invention relates to the technical field of mining area surface monitoring, in particular to a surface subsidence monitoring method, device and system for coal mine filling, and the method comprises the steps: obtaining the elevation data of a current coal mine area and the historical elevation data of a historical filling subsidence area; based on the elevation data, analyzing a time sequence change condition of the terrain of the current coal mine area to obtain a suspected subsidence area of the current coal mine area; analyzing the time sequence stability of the elevation data in each suspected subsidence area, and determining a suspected filling subsidence area of the current coal mine area; based on historical elevation data, establishing an elevation data change model; and analyzing the coincidence degree of the change trend of the elevation data in the suspected filling subsidence area and the elevation data change model to obtain the filling subsidence area. According to the method, the filling subsidence area can be accurately delimited, and misjudgment and missed judgment are avoided; the terrain development trend of the filling subsidence area can be predicted, the filling strategy is adjusted in a targeted mode, excessive filling is avoided, and therefore the cost is reduced.

The invention belongs to the field of coal mine underground goaf filling methods, and particularly relates to an ultra-long working face goaf inclined strip filling method. According to the method, a plurality of working faces are taken as a group, and fracturing roadways are arranged outside all the working faces. An inclined fracturing roof cutting area is constructed in the basic roof through the fracturing roadway, and the fracturing roof cutting area is constructed into a caving rock mass with fracturing broken waste rock on the two sides, a roof cutting block in the middle and the two inclined sides adjacent to a complete rock stratum. Then, the top cutting block bodies are used as a grouting diffusion face to conduct grouting on the fracturing broken waste rocks around the top cutting block bodies, and a plurality of inclined supporting strips which have high supporting capacity and are formed by mixing the broken waste rocks, the top cutting block bodies and slurry are formed; and the subsidence of the overlying sandstone group is controlled, and rock burst is prevented. Afterwards, the remaining fracturing drill holes, the remaining top cutting drill holes and the remaining grouting drill holes are used for conducting goaf filling on the follow-up working face in sequence, and therefore the problem that the construction work amount of long drill holes of the ultra-long working face is large is solved.