5061 results about "Coal mining" patented technology

The invention provides a coal mining digital twinning method based on multi-level dynamic deviation correction and AI optimization. The method comprises the steps of monitoring data acquisition and dynamic preprocessing, and performing denoising and space consistency detection on data; constructing and pre-processing the coal mine digital twinborn body; generating a nonlinear deviation field by adopting a high nonlinear variable interpolation and model mapping method; performing Kalman filtering error analysis and correction under the continuous analysis step, and marking an optimization model state in combination with a space mutation step; performing staged sliding window long-time-sequence fluctuation analysis, and classifying and marking regions according to an absolute value of an error and fluctuation; performing multi-level weighted error optimization based on a genetic algorithm, and adjusting material parameters and boundary conditions; carrying out material constitutive rectification based on dynamic Bayesian, and gradually enhancing the adaptability and accuracy of the model; and constructing a hybrid network structure AI optimization prediction model based on deep data driving, capturing the dynamic change of the material constitutive and the characteristic difference of the model constitutive, and realizing the precise digital twinborn simulation of the whole coal mining process.

The invention discloses a coal mine industry multi-dimensional data real-time monitoring and abnormity positioning method and system, and the method comprises the steps: collecting real-time data in coal mine operation, and carrying out the preprocessing; and carrying out dimension construction on the preprocessed data, and fusing the data of different dimensions to form multi-dimensional data. And inputting the multi-dimensional data into the anomaly detection model, and carrying out backtracking analysis on the abnormal data. And performing exception handling and response according to the detected exception and backtracking analysis. According to the coal mining industry multi-dimensional data real-time monitoring and anomaly positioning method and system provided by the invention, correlation analysis and fusion are performed on different-dimensional data, key features are extracted by using principal component analysis, and efficient fusion of the multi-dimensional data is ensured in combination with nonlinear transformation. The main information is reserved, and the accuracy of anomaly detection is improved by enhancing the representativeness of the features. The abnormal response time is shortened, and the emergency processing accuracy is improved.

The invention discloses a multi-source heterogeneous data fusion method of a sky tower ground well carbon flux observation system, which comprises the following steps of: 1, preprocessing and automatically correcting data to solve the problems of noise, space-time inconsistency, format difference and systematic error in a multi-source heterogeneous data acquisition process; the multi-source heterogeneous data are respectively from satellite remote sensing, unmanned aerial vehicle remote sensing, an eddy covariance flux tower, ground observation and underground observation; step 2, multi-level data fusion: extracting multi-source heterogeneous data from original signals step by step to form unified high-dimensional feature expression, and finally outputting real-time observation data of carbon emission and carbon sink of the coal mining area through a decision model; and step 3, performing comprehensive observation and application output, performing real-time analysis according to the real-time observation data, and outputting a detection result and early warning information. According to the method, an advanced algorithm with adaptive correction and multi-level fusion capability is adopted, and data fusion of five observation modules of the sky tower surface well is realized, so that the key bottleneck in the prior art is broken.

The invention relates to the field of excavation equipment obstacle avoidance based on image analysis, in particular to a coal mine excavation equipment obstacle avoidance method and system based on machine vision, and the method comprises the steps: obtaining the frequency domain characteristic parameters of the current electromagnetic noise during the operation of underground electromechanical equipment, and synchronously collecting the current original image frame output by a visual sensor; after a current de-noised image frame is obtained after dynamic de-noising processing, an obstacle contour feature point set is extracted through multi-scale edge detection, and an obstacle position confidence map is obtained according to space-time consistency analysis; obtaining point cloud coordinates of an image data loss area caused by electromagnetic interference, and mapping the point cloud coordinates to an image coordinate system to obtain a three-dimensional geometric complemented image; and constructing a dynamic occupation grid map of the underground environment according to the three-dimensional geometric complementation image and the obstacle position confidence map, and planning an obstacle avoidance path of the mining equipment according to the dynamic occupation grid map. And the obstacle avoidance capability of the mining equipment is improved, and safe and efficient coal mining operation is guaranteed.

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 belongs to the field of coal mine accident emergency management, and discloses a coal mine accident emergency response management system and method.A real-time multi-source data acquisition and fusion module acquires multi-source data and transmits the multi-source data to a central control room in real time for data fusion and processing; the intelligent decision support and accident simulation module performs accident scene simulation and provides intelligent decision support; the dynamic rescue resource scheduling and optimization module tracks the positions of rescue equipment and personnel, and dynamically optimizes a rescue path according to the real-time condition of an accident; the real-time communication and cooperation platform ensures real-time communication between the underground and the ground; the underground personnel positioning and evacuation system monitors the specific positions of underground personnel in real time and intelligently generates an optimal personnel evacuation route according to real-time environment data and accident simulation results. According to the method, the efficiency of accident emergency response is improved, casualties and property loss in coal mine production accidents are reduced, and the method has remarkable safety benefits and economic benefits.

A mining, releasing and filling process flow collaboration method for a nearly-upright super-thick coal seam belongs to the technical field of coal mining and comprises the following steps: dividing the nearly-upright super-thick coal seam into a plurality of sections, respectively establishing a low-level mining and releasing system at the bottom of each section, and respectively establishing a high-level filling system at the horizontal position of the top interface of each section; comprising a coal mining period and a filling period, after the low-position mining and caving system is established, coal mining and caving are carried out through a coal mining machine and a support in the coal mining period, in the machine following and support moving process, a novel support synchronously lays a separation net on a goaf, and after a filling step pitch is pushed forwards, the novel support unfolds slurry blocking cloth; then filling slurry is injected into the goaf through a high-position filling process roadway, a filling chamber and a filling hole in sequence, the stability of nearly upright surrounding rock is maintained, and it is ensured that the mining depth is safely extended; the method effectively solves the problems of difficulty in prevention and control of surrounding rock instability, difficulty in control of cutting type subsidence and low recovery rate of coal resources in the existing horizontal section fully mechanized caving mining method of the steeply inclined nearly-upright extra-thick coal seam.

The invention relates to the technical field of directional drilling track control, and discloses a coal mining underground directional drilling track control method and system, and the method comprises the steps: carrying out the fusion track analysis of a drilling machine based on sensor data, drilling parameters and pre-obtained geological hardness parameters, and obtaining a reference track of the drilling machine, a sensor, an azimuth angle sensor and a bit pressure sensor are used for synchronously collecting drill bit attitude data of a drilling machine to generate a real-time track of the drilling machine, then track offset calculation is carried out to obtain inclination angle deviation and azimuth angle deviation, and dynamic gain adjustment analysis is carried out on the drilling machine to obtain adjustment parameters of the drilling machine. And finally, the drill bit posture of the drilling machine is adjusted based on the adjusting parameters. According to the method, the directional control accuracy of the underground drilling track can be improved.

The invention provides a coal mine underground roadway surrounding rock reinforcement grouting system, and relates to the technical field of coal mining. Comprising a stirring barrel, a grouting pump, a moving frame, a grouting pipe mechanism, a steering mechanism, a grouting pipe length adjusting mechanism, a plugging mechanism and a power mechanism, and an input opening of the grouting pump communicates with the stirring barrel; the grouting pump and the stirring barrel are both arranged on the moving frame; the grouting pipe mechanism communicates with an output port of the grouting pump, and the grouting pipe mechanism is used for grouting the drill hole; the steering mechanism is connected with the grouting pipe mechanism and used for adjusting the angle of the grouting pipe mechanism so that the grouting pipe mechanism can be aligned with the drilled hole. The grouting pipe length adjusting mechanism is connected with the steering mechanism and the grouting pipe mechanism, and the grouting pipe length adjusting mechanism is used for adjusting the length of the grouting pipe mechanism; the periphery of the grouting pipe mechanism is sleeved with the plugging mechanism, and the plugging mechanism is used for plugging a drill hole when grouting is conducted on the interior of the drill hole through the grouting pipe mechanism; and the power mechanism is connected with the grouting pipe length adjusting mechanism.

The invention discloses a negative carbon coplanar filling system arrangement and mining method, which comprises the following steps of: stoping by adopting a rear gangue high-porosity filling coal mining technology, retaining a stoping roadway on one side of a filling section by utilizing a gob-side entry retaining technology, and reinforcing by adopting a roadway-side support body; the mining roadway serves as a CO2 filling roadway of the working face and a mining roadway on one side of an adjacent filling working face; when the working face advances by 300-500 m, the working face is separated from a rear goaf through a sealing wall, and a sealed storage space is formed; then, drill holes are formed in the goaf through the CO2 injection and filling roadway, and CO2 injection and filling pipelines are arranged in the mining roadway and the drill holes; and CO2 is injected into the goaf by the CO2 injection pump through the CO2 injection pipeline, and after injection is completed, CO2 injection in the next closed space is started until injection of the working face is completed. The system is simple in arrangement, CO2 filling and coal mining filling do not interfere with each other, operation is flexible, the sealing performance of the sealing space is good, the dual purposes of solid waste disposal and CO2 sealing are achieved, and green mining of coal resources is achieved.

The invention discloses a steeply-inclined nearly-upright extra-thick coal seam horizontal section fully-mechanized caving filling mining method, and relates to the technical field of coal mining. The method includes the following steps that the nearly-vertical super-thick coal seam is divided into different mining levels of 20-40 m, a low-position mining and releasing system is arranged at the horizontal position of the junction of a current section and a lower section, a high-position filling system is arranged in a top plate or bottom plate rock pillar at the horizontal position of the junction of the current section and an upper section, and the coal seam of the current section is mined through a fully-mechanized caving mining method; along with advancing of the coal face, a separation net and slurry blocking cloth are laid on the goaf through a net laying and slurry blocking support; a suspended cavity space detection characterization robot arranged in the high-position filling system is used for carrying out goaf space detection; the method comprises the following steps: dividing a nearly upright extra-thick coal seam into different sections for section mining, performing in-situ grouting filling on a subsequent mining space in the mining process, forming a stable filling interface in a goaf, fundamentally weakening stress concentration and reducing energy accumulation, and realizing collaborative proceeding of filling and coal mining.

The invention discloses a filling disaster prevention and control green mining method for a nearly-upright extra-thick coal seam, and relates to the technical field of coal mining. The method includes the following steps that the nearly-vertical super-thick coal seam is divided into different sections according to the thickness of 20-40 m; all the sections are mined through a fully mechanized caving mining method, after the coal face is advanced by 8-10 m, namely a mining and filling step pitch, slurry blocking cloth is arranged on a top coal caving filling mining hydraulic support, and a separation net is laid in a goaf; grouting and filling are conducted on the goaf through the high-position process roadway; the nearly vertical coal seam is divided into a plurality of horizontal sections, the descending mining sequence is adopted, goaf timely filling is matched, rock stratum movement can be precisely and cooperatively controlled, steeply inclined rock stratum displacement and deformation caused by coal seam mining are effectively reduced, surrounding rock stress is remarkably weakened, earth surface deformation is controlled, and compared with a traditional mining mode, the mining efficiency is improved. And the risk of coal rock dynamic disasters is greatly reduced.

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 belongs to the technical field of lithology identification, and discloses a coal cutter self-adaptive regulation and control method for coal rock identification based on cutting pick stress monitoring, so as to realize accurate and efficient identification of coal rock and self-adaptive regulation and control of a coal cutter based on cutting pick stress data and in combination with operation parameters of the coal cutter. According to the coal mining machine self-adaptive regulation and control method based on cutting pick stress monitoring and coal rock recognition, the pressure sensors arranged at the roots of all the cutting picks are used for obtaining cutting pick stress original data in real time, the coal rock interface is accurately and efficiently recognized by combining the operation parameters of the coal mining machine and utilizing a data processing and analysis algorithm, and the coal mining machine self-adaptive regulation and control method is high in practicability. And the cutting parameters of the coal mining machine are dynamically adjusted, so that safe, efficient and high-precision coal rock identification and self-adaptive regulation and control of the coal mining machine are realized, the intelligentization of coal mining operation is improved, the coal mining efficiency is improved, the abrasion of equipment is reduced, and the safety and stability of the mining operation are guaranteed.

The invention discloses an efficient thin seam coaling roller for a coal mining machine and a using method, and relates to the field of coal mining equipment. A thin seam efficient coaling roller for a coal mining machine comprises a coal mining spiral roller which is fixedly installed at the power output end of a driving rocker arm of the coal mining machine through a fixing bolt; the mounting cover is fixedly mounted at the position, close to the coal mining spiral drum, of the coal mining machine driving rocker arm; while the coal mining spiral drum rotates to mine coal, water spraying at the rocker arm of the coal mining machine, water spraying at the cutting tooth seat and mist curtains sprayed by the wide-angle fan-shaped atomizing nozzles work cooperatively, the dust falling effect is enhanced, a water mist cover is rapidly formed under the assistance of the mounting cover, and the water mist cover can effectively isolate coal dust inside, so that the dust falling effect is improved. And the coal dust diffusion is greatly reduced, the body health of miners is guaranteed, the occupational health risk is reduced, the abrasion of the coal dust to equipment is reduced, the service life of the equipment is prolonged, the maintenance frequency and cost of the equipment are reduced, and the comprehensive benefits of coal mining operation are improved.

The invention relates to a coal mining subsidence area plant foundation monitoring method and system based on multi-source data fusion, and the method comprises the steps: obtaining multi-source monitoring data of a target coal mining subsidence area plant area, the multi-source monitoring data comprising satellite remote sensing data, ground measurement data and interference radar data; performing time synchronization and space unification on the multi-source monitoring data to obtain monitoring data with unified space; performing fusion processing on the monitoring data with uniform space to obtain comprehensive deformation data; constructing a three-dimensional settlement deformation field according to the comprehensive deformation data, and extracting deformation rate and acceleration information of each monitoring point through a gradient calculation method; and according to the deformation rate and the acceleration information, obtaining risk assessment of the plant foundation in the target coal mining subsidence area. The technical problems of multi-source heterogeneous data fusion and real-time settlement monitoring and early warning are effectively solved, and the precision and timeliness of foundation settlement monitoring are improved.

The invention relates to the technical field of knowledge maps and large models, and discloses a fully-mechanized coal mining equipment large model decision support method and system. The method comprises the following steps: defining entities in data information of fully-mechanized coal mining equipment and a relationship between the entities to form triple data; converting the triple data into question and answer pairs based on the question and answer template, and optimizing the question and answer pairs; establishing a large language model, training the large language model based on question and answer pairs, performing fine tuning on the large language model based on a LoRA technology, and performing quantification processing on the equipment state in combination with fuzzy comprehensive evaluation to obtain a quantification result; the system uses the fine-tuned large language model to carry out entity and intention recognition on a natural language input by a user, a Cypher query statement is constructed to carry out query in a graph database, sub-graph information is obtained, the sub-graph information and the quantization result serve as cue words and are transmitted to the large language model, and retrieval information supporting large model decision making is obtained. The operation and maintenance efficiency of the fully-mechanized coal mining equipment is improved.

The invention provides a coal mine digital twin geologic model construction method and system based on precise exploration, and relates to the technical field of coal mine geologic modeling, and the method comprises the steps: respectively obtaining ground static data, roadway dynamic data and coal mining real-time data; preprocessing the ground static data, the roadway dynamic data and the coal mining real-time data to obtain preprocessed data; integrating the preprocessed data, and constructing a three-dimensional dynamic geologic model according to the integrated data; dynamically updating the three-dimensional dynamic geologic model according to the coal mining real-time data so as to ensure the real-time performance and the accuracy of the model; according to the method, the three-dimensional dynamic geologic model is displayed through a three-dimensional visualization technology. Through multi-source data fusion and dynamic updating, transparent management of coal mine geological information is realized, and a powerful guarantee is provided for safe and efficient mining of a coal mine.

The invention discloses a coal mining vegetation disturbance analysis method based on long-time-sequence multi-source data, and relates to the technical field of mining area ecological monitoring and evaluation.The coal mining vegetation disturbance analysis method comprises the steps that on the basis of preprocessed mining area long-time-sequence spectral image data, a vegetation classification map is obtained through principal component analysis in combination with a classification algorithm; based on the vegetation classification map, obtaining a vegetation health index, evaluating the vegetation health condition and the vegetation change trend of the mining area, and obtaining vegetation health state time sequence data; based on the vegetation health state time sequence data, obtaining high-quality vegetation comprehensive data; constructing a vegetation state prediction model based on an LSTM model; and predicting a future vegetation state through a vegetation state prediction model based on the high-quality vegetation comprehensive data. According to the method, through an efficient multi-source data fusion mechanism and an advanced LSTM time sequence prediction technology, the accuracy and comprehensiveness of mining area vegetation state evaluation are remarkably improved.

The present invention relates to the technical field of prevention and control of geological disasters in mountainous coal mining areas. Disclosed are an InSAR-based measurement method for the angle of critical deformation of a coal mining area, and a system. The method comprises: acquiring a mining-induced surface deformation field image by means of small baseline subset-interferometric synthetic aperture radar; in the mining-induced surface deformation field image, separately drawing profile lines along a coal seam strike and a coal seam dip, and selecting target deformation points on the profile lines as points to be monitored; according to the incident angle, the flight direction and the azimuth angle of a satellite, obtaining vertical and horizontal deformation values; using a probability integral method to calculate parameters such as inclination, curvature and horizontal deformation; and drawing a curve graph on the basis of the vertical deformation of a target region and the above parameters, so as to obtain a corresponding angle of critical deformation. The InSAR-based measurement method for angle of critical deformation of a coal mining area provided by the present invention has the advantages of improved temporal resolution and reduced phase noises and the like, can achieve high precision and high efficiency, and can generate clear and visible Excel tables for surface deformation data of mining areas and corresponding profile data.

The invention relates to production collaborative scheduling, in particular to a production collaborative scheduling method based on an intelligent mine comprehensive management and control platform. According to the intelligent linkage control system, a sensing-data-application three-layer framework is constructed, key links such as coal mining, transportation, storage, washing and selection and lifting are integrated, cross-equipment and cross-system intelligent linkage control is achieved, and the dispatching adaptive capacity and the cooperation efficiency under the complex working condition are remarkably improved. Comprising the following steps: S1, collecting equipment states, environmental parameters and production progress data of each production link of a mine, processing the data through an edge computing node, and uploading the data to a cloud platform; s2, constructing a digital twin mine model, and configuring an initial production scheduling rule and a resource constraint condition; s3, when an abnormal or disturbance event is detected, the system gives out an early warning and automatically responds, a scheduling instruction is issued to each equipment system, and linkage execution is realized; and S4, continuously returning a scheduling execution result and a running state to the platform for evaluation and analysis, and training and optimizing the scheduling model by using feedback data to realize self-adaptive capability enhancement.

The invention discloses a coal mining subsidence early warning system based on image processing, and relates to the technical field of mine environment monitoring, and the system comprises the steps: collecting image data of a coal mining area, carrying out the preprocessing of the image data, and generating standardized image data; performing continuous image frame processing on the standardized image data through an optical flow analysis method, calculating earth surface displacement and deformation information, and generating subsidence dynamic change data; combining the subsidence dynamic change data with the standardized image data, and inputting the combined data into an adaptive convolutional neural network to identify a subsidence area; according to the subsidence change trend and the coal mining progress, subsidence risks are evaluated, and real-time early warning signals are generated. According to the invention, by analyzing the motion trails of the pixel points in the image, the dynamic change of the coal mining area can be captured in real time, the sign of subsidence can be identified in time, early warning can be carried out in advance, and the timeliness and accuracy of monitoring are obviously improved.

The invention relates to the technical field of coal mining equipment, and discloses a mining roadway stability real-time monitoring and early warning system which comprises the following steps: S1, multi-source sensor network deployment, S2, data transmission and preprocessing, S3, stability index dynamic calculation, S4, fusion early warning model construction and S5, graded early warning triggering. Roadway surrounding rock deformation, stress, vibration and environmental parameters are collected in real time through a multi-source sensing network, efficient data transmission and preprocessing are achieved in combination with an industrial looped network, surrounding rock strain energy density, displacement convergence rate, support failure coefficient and other key indexes are dynamically calculated, a fusion early warning model is constructed based on machine learning, and the early warning accuracy is improved. According to the method, accurate evaluation of the stability level is achieved, grading alarm and emergency control are automatically triggered when a threshold value is reached, a'perception-analysis-decision-response 'closed loop is formed through the design, the real-time performance of roadway stability monitoring and the early warning reliability are remarkably improved, and accidents such as roof fall and wall caving are effectively prevented.

The invention discloses a carbon storage space construction method for an artificial reconstruction plugging key layer, and the method comprises the following steps: S1, carrying out geological exploration, and determining the thickness and lithology of each overlying rock stratum; s2, determining the height of a gas guide fissure zone generated after the coal seam is mined by filling based on theoretical analysis and actual measurement data; s3, on the basis of geological data and the height of the gas-conducting fissure zone, the position of an artificial reconstruction plugging key layer and the position of a grouting layer are determined; s4, filling mining is carried out, grouting is carried out on overlying strata to reconstruct and block a key layer, and a carbon storage space is formed; and S5, carbon dioxide gas is injected into the goaf through a pipeline, carbon dioxide concentration monitoring is conducted on the working face while negative carbon filling is conducted, earth surface rock movement monitoring is conducted on the earth surface, and the negative carbon filling effect is judged. According to the method, the carbon storage space is formed by manually rebuilding and blocking the key layer while the gangue is filled, the space after coal mining can be effectively utilized for storing carbon dioxide, and emission of greenhouse gas is effectively reduced.

The invention provides a modified coal gangue-based large-flow-state grouting and water plugging material and a preparation method thereof. Comprising 80-90 parts of a coal gangue sample, 1-5 parts of Portland cement, 1-5 parts of sulphoaluminate cement, 0.51-3 parts of a polycarboxylic acid water reducing agent, 1-4 parts of cellulose ether with the viscosity of 200w, 0.1-5 parts of a calcium oxide expanding agent, 0.5-5 parts of a plastic expanding agent, 0.5-1 part of redispersible latex powder, 0.5-5 parts of polyacrylamide with the molecular weight of 1000 and water, and the water-material ratio is 0.4. According to the modified coal gangue-based large-flow-state grouting and water plugging material and the preparation method thereof, the cement consumption can be remarkably reduced, the cost is reduced, the utilization rate of solid wastes (such as coal gangue) is increased, and the material has good flow-state performance and adjustable setting time; the method is suitable for deep and large shaft surrounding rock water seepage treatment in coal mining and other mine engineering.

The invention discloses a real-time back break control method of a heading machine based on visual association and digital twinning, which relates to the technical field of intelligent control of coal mining equipment, and comprises the following four steps: processing binocular visual data through a double-domain double-branch Transformer model, extracting coal rock and roadway structure characteristics and outputting cutting head offset; a GCN-LSTM model is adopted to fuse visual, laser radar and fiber-optic gyroscope data, and dynamic calibration and output of a three-dimensional pose are carried out; a roadway three-dimensional model is constructed based on the SLAM technology, and real-time updating of a digital twin model is achieved through edge-cloud collaboration; and in combination with a reinforcement learning strategy, generating a cutting parameter adjustment instruction according to the deviation of the digital twin model, and correcting model parameters through error feedback. The method solves the problems of low visual recognition precision, sensor data drift, digital twinning update lag and the like in an underground complex environment, improves the back break control precision, tunneling efficiency and equipment stability, and is suitable for tunneling operation under complex geological conditions.

The invention belongs to the technical field of coal cutter maintenance, and particularly relates to laser cutting equipment for coal cutter maintenance, the laser cutting equipment comprises a mounting seat and a control panel arranged on the upper side wall of the mounting seat, the upper side wall of the mounting seat is fixedly connected with a PLC, and the upper side wall of the mounting seat is fixedly connected with a fixing frame; the side wall of the fixing frame is fixedly connected with a vertical electric push rod, and the moving end of the vertical electric push rod penetrates through the fixing frame. In the process of cutting and maintaining the coal mining machine by the laser cutting equipment, dust particles attached to an optical component can be automatically cleaned after the optical component of the laser cutting equipment is detected to be blocked by the dust particles, so that the dust particles are prevented from blocking and scattering part of laser beams, and the laser cutting equipment is prevented from being damaged. And meanwhile, the slag adhering phenomenon caused by blocking and scattering of laser beams on the surface of the part is automatically removed, and the appearance quality of the cut part is guaranteed.

The invention relates to an MT-InSAR self-adaptive fusion measurement method and device for long-term surface deformation of a coal mining subsidence area, and the method comprises the steps: obtaining surface deformation monitoring data in a plurality of modes, and carrying out the at least one of time-space alignment, noise removal and error correction of the surface deformation monitoring data, so as to obtain surface deformation data; calculating coherence indexes of the earth surface deformation data; generating a space adjustment coefficient by using a double-peak Gaussian function model constructed based on a coal mining subsidence area deformation rule; constructing an adaptive weighting method based on the coherence index and the spatial adjustment coefficient of the earth surface deformation data to calculate the weight of the multi-source InSAR data; and performing weighted fusion on the surface deformation monitoring data by using the weight of the multi-source InSAR data to obtain a final surface deformation result. Therefore, the problems of insufficient monitoring precision, incomplete coverage, poor adaptability and the like due to the fact that a single InSAR technology is difficult to comprehensively reflect spatio-temporal evolution characteristics of long-term surface deformation of the wide-area coal mining subsidence area are solved.

The invention discloses an anti-jamming coal mining drilling machine with drilling and multidirectional impacting functions and a using method thereof.The anti-jamming coal mining drilling machine comprises a drilling machine body, a high-pressure driving mechanism is arranged on the drilling machine body through a multidirectional guide rail mechanism, and a drilling assembly is connected with the high-pressure driving mechanism; when the drilling machine works, the high-pressure driving mechanism drives the drill rod and the drill bit to conduct rotary drilling, the high-frequency transverse vibration mechanism synchronously generates transverse high-frequency vibration, the high-pressure driving mechanism drives the drill rod and the drill bit to conduct rotary drilling, and the high-frequency transverse vibration mechanism drives the drill rod and the drill bit to conduct rotary drilling. The friction force between the drill bit and rock is reduced, debris accumulation is prevented, efficient deslagging is achieved, when hard rock or drill jamming occurs, the longitudinal vibration impact mechanism triggers longitudinal vibration, impact and drill jamming prevention functions are achieved through cooperative work of transverse vibration and longitudinal vibration, the drill jamming problem under the complex geological condition is effectively solved, the drilling efficiency and equipment reliability are improved, and the drilling cost is reduced. The device is suitable for drilling operation of mining roofs and baseplates, sides and the like.

The invention belongs to the technical field of belt conveyor maintenance, and particularly relates to a belt conveyor carrier roller disassembly and assembly auxiliary operation robot for a coal mine. Comprising a walking part, a power assembly, a carrier roller replacement box, a cab, an auxiliary operation platform and a lifting mechanism, the auxiliary operation platform comprises a posture adjusting platform capable of adjusting the direction, the inclination angle and the height; two groups of sliding telescopic mechanisms with the same telescopic direction are carried on the posture adjusting platform, and are respectively a left sliding telescopic mechanism and a right sliding telescopic mechanism; an action terminal of the left sliding telescopic mechanism carries a belt lifting supporting mechanism, and an action terminal of the right sliding telescopic mechanism carries a multi-degree-of-freedom disassembly and assembly manipulator; the auxiliary operation robot for disassembling and assembling the carrier roller can realize mechanical carrier roller replacement operation under the non-stop state of the belt conveyor, improve the operation efficiency, reduce the operation intensity, ensure the continuity of the coal mining process and ensure the safety and reliability of the carrier roller replacement process.