269 results about "Mine site" patented technology

The invention provides an ultra-deep high-pressure gas well variable-flow-state sand-carrying capacity evaluation method, and relates to the technical field of oil-gas exploration, and the method comprises the steps: collecting well logging data of a target gas well, constructing a gas-liquid two-phase flow parameter expression, and carrying out the quantitative analysis of key flow characteristics such as the gas content and the speed; a mathematical model is established by applying an H-K flow state judgment criterion, and numerical simulation is performed in combination with fluid dynamics simulation software, so that the flow state in the shaft is accurately identified and distinguished; then, according to high-temperature and high-pressure characteristics under actual working conditions and sand shape information monitored in a mine field, carrying out secondary correction on the resistance coefficient CD so as to improve a sand-carrying capacity prediction model; and finally, the critical sand-carrying flow velocity and yield are calculated based on the corrected model, and a scientific basis is provided for setting the sand-carrying capacity and reasonable production parameters of the gas well in different flow states. Safe and efficient development of a gas reservoir is guided, production parameter setting is optimized, and long-term stable and efficient operation of a gas well is ensured.

The invention belongs to the technical field of trajectory planning, and provides an electric shovel unmanned mining method and system based on digital twinning in order to solve the problem that the design of an electric shovel unmanned mining trajectory is difficult to deal with a complex heap surface, and the method comprises the following steps: obtaining sensing data, a historical mining trajectory and historical heap surface point cloud data; an electric shovel unmanned mining digital twin system is constructed based on the sensing data; uploading the historical mining trajectory and the historical heap surface point cloud data to a central database, and training by using generative artificial intelligence to obtain prediction trajectories suitable for different mine fields; constructing an agent model by using a neural network, calculating to obtain a predicted fullness rate, and performing simulated excavation according to the predicted fullness rate and the predicted trajectory to obtain electric shovel excavation control data; according to the method, deep reinforcement learning is utilized, the electric shovel unmanned excavation track is generated based on the electric shovel excavation control data, the electric shovel is controlled to conduct unmanned excavation in real time, the safety of the excavation process is guaranteed, and the track control precision of the electric shovel is also improved.

The invention discloses a mining area methane emission inversion method based on satellite observation and a Gaussian plume model. The method comprises the following steps: S1, acquiring a satellite inversion XCH4 data set, meteorological data, emission list data and global energy monitoring data; s2, determining a methane emission source and a research area in a geographic map by using the emission list data and the global energy monitoring data; s3, obtaining methane background concentration and XCH4 enhancement in the geographic map by using an atmospheric background concentration calculation method; s4, combining XCH4 enhanced spatial distribution and meteorological data in a geographic map to identify a methane enhanced plume of a methane emission source in the research area; and S5, performing Gaussian plume flow field simulation inversion of the methane emission source through the Gaussian plume model, and outputting the methane emission rate of the methane emission source at the current time through inversion of the Gaussian plume model. According to the method, the methane emission and the time sequence data of the methane emission can be obtained through accurate inversion, the frequency of obtaining the methane emission is improved, and the methane emission can be obtained according to time scale accumulation.

The invention relates to the field of mine intelligent management, and discloses an artificial intelligence autonomous identification model, which comprises a data acquisition module used for acquiring visual data, infrared data, audio data and environmental data from a coal mine site; the data preprocessing module is used for carrying out scale normalization, data enhancement, short-time Fourier transform, Mel frequency cepstrum coefficient extraction and normalization processing on the collected data; and the feature extraction module is used for extracting features from the visual data, the infrared data, the audio data and the environment data through a deep neural network. And through a multi-modal information fusion technology, the adaptability to a complex environment in mine operation is improved, the complementarity of different modal data is fully mined, and the recognition precision and robustness are remarkably improved. And an introduced feedback and self-learning optimization mechanism enables the model to be automatically adjusted according to real-time data, so that the stability and adaptability in a mine environment are enhanced.

The invention discloses a strip mine blasting numerical simulation analysis method based on an RHT constitutive model, and the method comprises the following steps: S1, building a strip mine blasting model: building a three-dimensional model through ANSYS software according to the actual geological conditions and blasting design requirements of a strip mine, and determining the geometric dimension of the model, the arrangement of blast holes, and the parameters of a charging structure; s2, determining material parameters: performing sampling and physical and mechanical property testing on field rocks of the strip mine to obtain rock parameters, determining rock material parameters in combination with an RHT constitutive model, determining explosive material parameters according to types of explosives used on site, and determining parameters of other related materials such as air and filling materials. According to the method, the RHT constitutive model is adopted, so that the accuracy of numerical simulation is improved; a more reliable basis is provided for blasting engineering design; the method has obvious economic benefits and social benefits; and powerful technical support is provided for the development of the strip mine blasting technology.

A facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, comprising a server comprising communications module configured to receive data and to transmit load management instructions; plurality of electrical charging stations; plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

The invention relates to the technical field of image processing, and discloses a mine personnel behavior recognition method and system based on YOLOv5. The method comprises the following steps: acquiring a video frame sequence of a mine site, extracting an environment interference vector from the video frame sequence, and optimizing the video frame sequence based on the environment interference vector to obtain a clear frame sequence; human body key point coordinates and posture vectors are extracted from the clear frame sequence, and time sequence changes of the key point coordinates are analyzed to obtain preliminary action features; calculating a similarity score between the preliminary action feature and a preset standard template, and refining the preliminary action feature based on the similarity score to obtain a refined action component vector; and matching the refined action component vector from a preset action library to obtain an action recognition result, and generating corresponding action response output based on the action recognition result. According to the invention, the accuracy of personnel action recognition in a complex mine environment is improved.

The invention relates to the technical field of slope monitoring, in particular to a mine field slope instability trend-based radar monitoring and early warning method and system, and the method comprises the following steps: recognizing a slope region with an instability risk on a geological image through a pre-trained Fast R CNN model, and taking the slope region as an instability risk region; scanning the instability risk area in real time through a slope radar to obtain a radar image sequence of the instability risk area; and acquiring a geological image sequence of the instability risk area with the same time sequence as the radar image sequence, determining an instability trend of the instability risk area based on the radar image sequence and the geological image sequence, and then allocating an early warning level according to the instability trend. According to the method, locking of instability factors in advance is realized on the basis of the Fast R CNN model, falling rock and soil loosening sliding track trends are quickly analyzed in real time on the actual falling rock and soil loosening track obtained through multi-modal data solution on the basis of the LSTM network, and thus integrated display, focusing monitoring and graded early warning of mining area risk points are realized.

The invention discloses a shale gas gathering and transportation station yard blockage and high-low pressure gathering and transportation interference diagnosis optimization method, and belongs to the field of natural gas mine field gathering and transportation. According to the method, the judgment method of the blockage site of the pipeline in the station and the calculation method of the blockage degree are determined by checking the friction resistance of the whole-station pipe fitting of the shale gas station and calculating the pressure drop of the pipeline in the station, and a solution is provided for the problem of gathering and transportation interference in the high-pressure well mine field and the low-pressure well mine field. The method is suitable for shale gas gathering and transportation stations in the middle and later periods of development, can assist in making of equipment overhaul and production parameter optimization schemes, further improves the operation efficiency of a pipe network, and has wide application prospects.

The invention discloses a mineral resource prediction model construction method based on a complex geological background, and relates to the technical field of mineral resource prediction, a three-dimensional ideal geological background field without mineralization interference is constructed based on the geological background of an unknown mining area, and the three-dimensional ideal geological background field is used for displaying the mining field of a non-mineralization area; constructing a three-dimensional real geological field based on the exploration data, and comparing the three-dimensional real geological field with the three-dimensional ideal geological background field to obtain first difference distribution data; extracting geologic features of the known mineralization area, and generating interference factors based on the geologic features; introducing the interference factor into the ideal geological background field to generate an interference coupling background field, and extracting the difference between the interference coupling background field and the ideal geological background field as second difference distribution data; the mineral resource prediction model is constructed based on the first difference distribution data and the second difference distribution data, the method can adapt to prediction requirements of different geological backgrounds, and the intelligent level and application flexibility of a mineral resource prediction system are remarkably improved.

The invention relates to the technical field of vehicle automatic driving, and discloses a multi-vehicle joint trajectory prediction method based on self-vehicle fusion and related equipment. The method comprises the steps of collecting multi-vehicle state data and mine field environment data in a target mine field, and performing preprocessing and lane changing behavior calibration to generate a standard multi-vehicle motion data set; carrying out intention extraction on own vehicle planning intention information through own vehicle planning tracks and operation task information, and carrying out mine field environment feature extraction and vehicle dynamic distribution on a standard multi-vehicle motion data set to construct mine field scene context representation; attention weight calculation and feature fusion are carried out through operation task features in the self-vehicle planning intention information and vehicle interaction features in the mine scene context representation, intention enhancement scene representation is generated, and a multi-modal query result is constructed; and through multi-vehicle collaborative prediction, path conflict detection and collaborative optimization scheduling, a multi-vehicle collaborative operation scheme is generated. The accuracy of mine field multi-vehicle trajectory prediction and the safety of collaborative operation are improved.

The invention belongs to the technical field of trackless mining preparation drift type filling mining, and discloses a steeply inclined thin ore body segmentation-free roadway mining method, which comprises the following steps of space partitioning and foundation engineering construction; stoping and filling in layers; a slope coping channel for trackless mining and transportation equipment to pass through is formed on an upward layered bottom plate on the top of the connection roadway of the lower stope through the blasting technology, the slope coping channel communicates with the segmented winze through the short connection roadway, and ore removal is conducted through the segmented winze; and entering the previous layer through the coping channel, and repeating the steps of stoping and filling the layer and constructing the coping channel until the mining is finished. A slope channel is formed by blasting at the top of a layered stope joint roadway, an upper layer of mine field is communicated with a draw shaft and a ventilation shaft of an upper section, and the sectional draw shafts are combined with the collaborative layout of top and bottom stage haulage drifts and ore loading transverse drifts, so that the beneficial effect that the whole accurate mining work amount is obviously reduced is achieved.

The invention relates to the technical field of coal rock failure early warning, in particular to a multi-parameter combined impact coal rock instability failure early warning method, which comprises the following steps of: firstly, carrying out engineering geology investigation on a mine site, collecting a coal rock sample and testing ground stress distribution; secondly, preparing a standard coal rock test piece in a laboratory, and performing nondestructive testing; then, determining a loading and unloading path according to numerical simulation, and designing a graded loading and unloading path of the coal rock test pieces of the roof group and the laneway side group; then, loading and unloading the test piece by using a true triaxial loading testing machine, and synchronously acquiring electromagnetic radiation and acoustic emission data; and finally, by calculating the acoustic emission energy, the fractal dimension and the joint fractal dimension, dividing the grading early warning critical value of each index, and constructing a three-level early warning model for the coal rock impact instability. According to the method, the coal rock impact instability risk can be effectively identified, graded early warning is provided, corresponding safety measures are guided to be taken on site, and safe production of a mine is guaranteed.

The present invention relates to the field of slope monitoring technology, and more specifically to a radar monitoring and early warning method and system based on the instability trend of mine slopes. The method comprises the following steps: using a pre-trained Fast R-CNN model to identify slope areas at risk of instability on a geological image as instability risk areas; using a slope radar to scan the instability risk areas in real time to obtain a radar image sequence of the instability risk areas; obtaining a geological image sequence of the instability risk areas that is co-sequential with the radar image sequence, and determining the instability trend of the instability risk areas based on the radar image sequence and the geological image sequence, and then assigning an early warning level based on the instability trend. The present invention uses the Fast R-CNN model to achieve early locking of instability factors, and based on the LSTM network, quickly and in real time analyzes the sliding trajectory trends of falling rocks and loose soil based on the actual trajectory of falling rocks and loose soil obtained by solving multimodal data, thereby achieving integrated display of risk points in the mining area, focused monitoring, and graded early warning.

The invention relates to a CLXRLMSE model method for predicting mine field gas concentration in multiple time steps, and belongs to the field of coal mine safety monitoring. The method comprises the following steps: realizing data denoising and stabilization processing through dynamic window moving average and stable wavelet transform; extracting gas concentration space correlation characteristics by adopting a multi-branch CNN (3 * 3 standard convolution, 5 * 5 cavity convolution and 1 * 1 compression convolution); constructing an LSTDM network, and synchronously capturing short-term fluctuation and long-term trend through double memory units; designing a risk-sensitive weighted loss function to strengthen high-risk missing report penalty; and XGBoost residual error correction and PSO hyper-parameter optimization are combined, so that the prediction error is reduced by 57%. Experiments show that the RMSE predicted by the method within 12 hours is smaller than or equal to 0.15%, the early warning response time is prolonged by 150%, and the occurrence rate of gas accidents is effectively reduced.

A hydraulic side dumping type mine car for a mine field comprises a chassis and a compartment body, a bearing frame is fixed to the chassis, a round groove is formed in the top of the bearing frame, a round bottom is connected to the bottom of the compartment body and placed on the round groove, a first rotating shaft is arranged in the middle of the top of the compartment body, two side doors are rotationally arranged on the first rotating shaft, and cantilevers are connected to the side doors. The cantilever is rotationally arranged on the first rotating shaft, the end of the cantilever is rotationally connected with a first connecting rod, and the round bottom end is rotationally connected with the end of the first connecting rod through a second connecting rod; a shaft seat is arranged on the chassis, a locking mechanism is arranged on the shaft seat, and the rotating positions of the first connecting rod and the second connecting rod are positioned on the shaft seat. According to the hydraulic side dumping type mine car, the side door on any side can be opened for unloading; a discharging plate is carried on the mine car, and during discharging, the discharging plate on the discharging side guides mineral aggregate to be away from the track.

The invention discloses a material grabbing machine with continuous transportation capacity, relates to the field of engineering machinery, and is suitable for bulk material loading and unloading scenes such as ports and mine fields. Aiming at the problems of low efficiency, easiness in structure damage, poor adaptability in narrow places and the like in the process of'grabbing-rotating-discharging 'of a traditional material grabbing machine, the material grabbing machine comprises a material grabbing machine main body, a shell hopper, a hopper system fixed on a base and an inclined belt conveyor system, a hopper inclination angle control system is additionally arranged, and the operation process is optimized to be'grabbing-discharging'; during operation, the shell hopper grabs bulk materials and then moves to the position above the hopper system for discharging, the angle of the hopper is adjusted through the inclination angle control system, the bulk materials are guided to the conveyor system and directionally conveyed to a transport tool, and a machine body does not need to rotate. The operation efficiency is improved, the structural stress of equipment is reduced, the service life is prolonged, the device is suitable for narrow sites, and secondary transfer is not needed.

The invention provides an open pit coal mine safety management and control method and device, electronic equipment and a storage medium, and relates to the technical field of mine field safety protection. The position of a key person is obtained in real time, whether the key person enters a corresponding operation area or not is verified, associated video monitoring is automatically triggered according to the in-place state of the person, safety measure execution is verified through real-time mapping of a video stream and an operation process state, and early warning is conducted when the safety measure execution is abnormal. The problems that in the prior art, due to the fact that a'process-position-video 'triple closed-loop verification mechanism is not formed and multi-source data space-time alignment and dynamic verification are not achieved, the security measure execution rate is insufficient, supervision lags behind, positioning data staticization is caused, video coverage is not matched, approval information is delayed, and data errors exist can be solved.

The invention provides a tramcar obstacle avoidance method and system based on a vehicle-mounted flat panel, and the method comprises the steps: a vehicle-road cooperation server detects the change of the load state of a target tramcar, and calls a mine field image cache library of a mine field; querying a target image set in a mine field image cache library based on the equipment identifier of the target mine car; determining actual compartment size information of the target mine car according to the target image set; updating the actual compartment size information to a mine car size configuration table; and sending a mine car size configuration table to the vehicle-mounted flat plate in each mine car, wherein the mine car size configuration table is used for each mine car to execute obstacle avoidance operation. The tramcar can be effectively supported to accurately avoid obstacles, and the operation safety and efficiency of the tramcar are improved.

The embodiment of the invention provides a mine field early warning area division method and related equipment, and the method comprises the steps: obtaining monitoring data at a plurality of preset monitoring points, the monitoring data comprising position data and corresponding physical monitoring data; constructing a spatial distribution diagram based on the position data on the plurality of preset monitoring point positions and the corresponding physical monitoring data; identifying a plurality of abnormal monitoring points in the spatial distribution diagram through an early warning safety model; determining an early warning area boundary based on the plurality of abnormal monitoring points; and generating a corresponding visual partition result in the spatial distribution diagram based on the early warning region boundary. Through the steps of the method, the areas with risks in the mine field can be identified based on the three-dimensional space information and the physical monitoring data of the monitoring points, dynamic early warning division of area levels is realized, the space distribution condition of the mine field risks is reflected, and the safety management efficiency of the mine is improved.

The invention relates to the field of emergency route planning, in particular to a coal mine accident emergency route automatic planning method which comprises the following steps: S1, acquiring first position information of each worker in a coal mine and mine tunnel information of a mine field in real time; s2, calculating a first escape route of each worker according to the first position information and the mine tunnel information; s3, judging whether congestion occurs or not according to the first escape route of each staff; if yes, entering the step S4; if not, marking the first escape route as a second escape route, and entering the step S5; s4, the congestion position is marked, and a second escape route is generated; according to the method, the phenomena that escape routes are overlapped when all the staff escape at the same time, the width in the mine tunnel is limited, congestion is likely to occur, and trampling is caused are considered, compared with a common escape route planning method, on the premise that it is guaranteed that all the staff escape to the safe position in the shortest time, the safety of the staff is guaranteed, and the safety of the staff is guaranteed. And the possibility of extra casualties is reduced.

The present invention provides a coal mine production process control system, which relates to the field of process management technology and includes: a data acquisition module for acquiring data of each production process in a mine in real time and outputting initial data; a preprocessing module for preprocessing the initial data to obtain data to be analyzed; a model training module for training a model to be trained selected from a model database in combination with preset data resources, outputting an alternative model, and outputting an alternative model that meets preset performance conditions as an analysis model; a data analysis module for analyzing the data to be analyzed based on the analysis model, outputting process analysis results, and updating parameters and optimizing performance of the analysis model in combination with preset data resources and cloud data. The present invention can monitor the data of each production process in a mine in real time, promptly discover potential risks of each production process, continuously update parameters and optimize performance of the model, and ensure the real-time and accuracy of the process analysis results.

The invention provides a three-dimensional lithium battery mine visualization system based on digital twinning, and the system comprises a physical sensing layer which is disposed at a lithium battery mine site, and comprises a plurality of sensor networks used for collecting geologic bodies, production equipment, environment parameters, personnel positions, and vehicle states; and the data interaction layer comprises a data integration platform and an edge computing node, and is used for carrying out cleaning, fusion, protocol conversion and edge side preliminary analysis on the multi-source heterogeneous data uploaded by the physical sensing layer, and uploading the multi-source heterogeneous data to a cloud. By integrating the slope monitoring sensor and the professional analysis model, real-time evaluation and advanced early warning of the slope stability and the tailing pond safety are achieved, major accidents such as collapse and dam break are effectively prevented, meanwhile, the harmful element diffusion model is utilized, and the safety of the tailing pond is improved. Migration paths of fluoride dust, radioactive substances and potential leakage pollutants in the atmosphere and the water system are dynamically simulated, accurate decision support is provided for environmental risk emergency response, and the influence on surrounding ecology is reduced to the maximum extent.

Methods and systems for mining, for example a mining operation including: a surface mine site including a processing site situated remotely from a blast site within the mine site and coupled by a network of roads, wherein a first proportion of the roads are sealed and a second proportion of the roads have a maximum width in the range of 3 to 12 metres; a fleet of autonomous material handling units located at the surface mine site, each autonomous material handling unit including a wireless transceiver for coupling to a communications network. The autonomous material handling units include a plurality of small capacity haulage vehicles, each having a maximum payload capacity of 80 tonnes or less. The autonomous material handling units are configured to be controlled by a control centre via the communications network.

A modular structure supports elevated rail segments for delivering electrical power to a moving work machine, such as a hauler at a mining site. Opposite ends of a roadside barrier contain complementary tubular couplers arranged vertically. A lower end of a dielectric post positioned in one of the tubular couplers has opposing dielectric plates at an upper end. A top edge of each plate has a creepage concavity between a pair of rail recesses. Another dielectric post of similar configuration is positioned in the other of the tubular couplers. Holes within the couplers and the posts ensure alignment of respective rail recesses in which conductive rails are placed. Dielectric inserts frictionally lock the rails into the rail recesses.

The present application provides a kind of unmanned mine car state monitoring method, comprising: planning vehicle fleet travel path, marking dangerous area of travel path;Different mine car dangerous area travel state data and non-dangerous area travel state data are monitored;Different mine car passes through cooperative monitoring and determines abnormal mine car in dangerous area and non-dangerous area;Vehicle fleet cooperatively controls abnormal mine car and normal mine car, ensures mine car safety;Based on the vehicle fleet after cooperative control, different vehicle fleet collision possibility is judged and adjusted, the threat of abnormal mine car to normal mine car is reduced, and the normal mine car in mine field is ensured orderly work.

The invention discloses a multi-view video data generation method for an unstructured mining area scene, and relates to the technical field of automatic driving. The method comprises the following steps: firstly, constructing BEV expression fusing mine terrain geometry and semantics, and generating a dangerous area mask and a scene graph; secondly, converting a test requirement into a parameterized scene script; then, training a semantic terrain world model which takes a Diffusion Transform as a backbone and introduces a dangerous area priority mask mechanism; and finally, generating a semantic topography BEV of a time sequence and an equipment track by using the world model under the driving of a scene script, and further synthesizing a multi-view and geometrically consistent mining area driving video sequence which conforms to safety constraints. According to the method, the problems of lack of unstructured mining area scene training data, high acquisition cost and high risk are solved, high-quality video data covering long-tail dangerous working conditions can be efficiently and controllably generated, and the perceptual generalization ability and safety of a mining area automatic driving system are remarkably improved.

Mine sites are known to include a variety of vehicles of various different types and ages. Such a variety increase the difficulty of the dispatcher's job of allocating the vehicles in a manner that optimizes production of material. In particular, different vehicles and different operators may be shown to handle route conditions, such as grade and curvature, at different speeds. A truck allocation system is able to provide suggestions for vehicle allocation based on the vehicles operating parameters and route geometry. Ideally, implementation of the suggestions for vehicle allocation act to increase production.

A modular structure supports elevated rail segments for delivering electrical power to a moving work machine, such as a hauler at a mining site. Opposite ends of a roadside barrier contain complementary tubular couplers arranged vertically. A lower end of a dielectric post positioned in one of the tubular couplers has opposing dielectric plates at an upper end. A top edge of each plate has a creepage concavity between a pair of rail recesses. Another dielectric post of similar configuration is positioned in the other of the tubular couplers. Holes within the couplers and the posts ensure alignment of respective rail recesses in which conductive rails are placed. Dielectric inserts frictionally lock the rails into the rail recesses.

This invention discloses a method for graded early warning of abnormal psychological states in miners. It extracts and filters features from three modal signals processed in the time domain, frequency domain, time-frequency domain, and spatial domain to obtain corresponding first target signal feature sets. Based on optimal transmission theory, the maximum mean difference algorithm, and a selected kernel function, the first target signal feature sets are aligned locally and globally to obtain second target signal feature sets. These second target signal feature sets are then mapped to a unified, preset-dimensional embedding space for comparative learning to obtain a third target signal feature set. The third target signal feature set is then weighted, summed, and input into a bidirectional long short-term memory network to obtain initial fused features. These features are then input into a GhostNet network to obtain fused features, which are then input into the psychological state recognition module of a psychological graded early warning model to determine the miner's psychological state. Finally, these features, combined with mine environment parameters, are input into the early warning grading module of the psychological graded early warning model to obtain early warning information.