89 results about "Deep mining" patented technology

The invention discloses a new energy intelligent operation and maintenance system based on AI and digital twinning, and relates to the technical field of photovoltaic power generation and energy storage, and the system comprises a sensing and control layer which is disposed at the site of an optical storage power station. Power station equipment and environment data are collected in real time through the sensing and control layer, the data collection and edge calculation layer completes preliminary analysis and quick response locally, the timeliness of fault processing is effectively improved, the cloud platform conducts deep mining and model training on mass data through an AI analysis engine, the system performance is continuously optimized, and the fault processing efficiency is improved. And the digital twinning and decision visualization module realizes holographic mirroring and dynamic deduction of the operation state of the power station and assists management personnel in accurate decision making and predictive maintenance, and the system finally forms a continuously evolved closed-loop intelligent operation and maintenance system, so that the operation and maintenance efficiency of the power station is improved. And the energy utilization efficiency, the equipment reliability and the operation and maintenance automation level are obviously improved.

The invention is suitable for the field of geological disasters, and discloses a photovoltaic station geological disaster key influence factor analysis and induction mining method, system and device and a medium, and the method comprises the steps: obtaining influence factors of geological disaster development, and carrying out the preprocessing; spatial distribution and types of geological disaster points are obtained through historical data and field investigation, and danger levels of the geological disaster points are obtained through an expert scoring method; based on the spatial distribution, the type and the danger level, adopting an MDLP algorithm to construct a geological disaster database; based on the geological disaster database, performing evaluation factor correlation analysis through RC table chi-square test to obtain an optimized geological disaster database; based on the optimized geological disaster database, confidence and support are introduced, and an Apriori algorithm is adopted to obtain a strong association rule; through combination of a strong association rule and geodynamics, a core causal chain is extracted, deep mining of a geological disaster induction mechanism is realized, and a direct and reliable decision basis is effectively provided for accurate disaster prevention and control and the like of a photovoltaic field station.

The invention discloses an underground mine deep mining rockburst monitoring and early warning system, which relates to the technical field of mining, and comprises a sensing module, the output end of the sensing module is communicated with the input end of a wireless network module, the output end of the wireless network module is communicated with the input end of a data acquisition module, and the output end of the data acquisition module is communicated with the input end of a data processing module. The output end of the data acquisition module is communicated with the input end of the Ethernet module, and the output end of the Ethernet module is respectively communicated with the input ends of the terminal display module, the communication module and the early warning decision module. According to the invention, through the sensing module, the data acquisition module and the early warning decision module, real-time acquisition of rock mass multi-dimensional parameters, adaptive coverage monitoring and interference signal filtering are realized, rock burst precursor features are accurately identified, the problems of many monitoring blind areas, large data interference and low identification precision of a traditional fixed sensor network are effectively solved, and the method is suitable for popularization and application. And the real-time performance and the accuracy of deep mining rock burst early warning are obviously improved.

The utility model relates to a metal surface mine large dip angle belt conveyor transportation system which comprises a coarse crushing station system, a first transfer station, a second transfer station and a third transfer station. The first transfer station is connected with the second transfer station through a belt conveyor, and the second transfer station is connected with the third transfer station through a large-dip-angle belt conveyor; the inclination angle of the large-inclination-angle belt conveyor is larger than 15 degrees and smaller than 35 degrees. Compared with the prior art, the large-dip-angle belt conveyor has the advantages that by applying the large-dip-angle belt conveyor technology, the capital construction investment of a mine can be greatly reduced; the capital construction time is shortened, the metal surface mine deep mining transportation distance is shortened, and the mine transportation cost is saved; and meanwhile, the routing length is shortened through the routing arrangement of the large-dip-angle belt conveyor, side slopes under unfavorable geological conditions are effectively avoided, and the safety and reliability of the system are improved.

The invention relates to the technical field of data processing, and provides a reservoir bank landslide soil body shear strength parameter inversion method, device and equipment and a storage medium, the effective value range of soil body shear strength parameters is determined by obtaining a target safety coefficient, a training sample set is generated in the effective value range through numerical simulation, and according to the training sample set, the reservoir bank landslide soil body shear strength parameter inversion method and device are obtained. And constructing a safety coefficient prediction model through a machine learning method, searching in an effective value range according to the safety coefficient prediction model and the target safety coefficient, and determining a soil shear strength parameter inversion result matched with the target safety coefficient. According to the method, accurate acquisition of the shear strength parameters of the reservoir bank landslide soil body is achieved, meanwhile, more data values are released through existing information in the deep excavation exploration stage, automation and high efficiency of the inversion process are achieved, dependence on manual experience trial calculation is thoroughly eliminated, and the method is suitable for large-scale popularization and application. And finally, a scientific basis is provided for engineering design optimization and disaster prevention and control decision making of reservoir bank landslide.

The invention discloses a deep mining and storage space rock mass damage evolution and long-term stability prediction system and method, and the system is characterized in that a long-term monitoring module comprises an embedded fiber grating strain sensor array, a resistivity CT imaging unit, a chamber convergence laser range finder and a rock sound wave testing unit, and is used for collecting multi-source monitoring data; the data preprocessing module is used for preprocessing the multi-source monitoring data; the aging analysis module is used for predicting the remaining service life based on the multi-source monitoring data; and the operation and maintenance decision module is used for generating a maintenance strategy and risk prompt based on the residual service life prediction result. The method comprises the following steps: arranging the long-acting monitoring module on site; collecting multi-source monitoring data; de-noising the multi-source monitoring data, and extracting a long-term trend term and a short-term fluctuation term; predicting the remaining service life; and performing stability grading and operation and maintenance decision according to the remaining service time. The system and the method can efficiently and accurately realize quantitative evaluation of the long-term stability of the rock mass.

The invention discloses a method for judging the grouting effect of a coal mine tunnel bottom plate, and belongs to the technical field of coal mine tunnel safety control. The technical problem that in the prior art, the grouting effect of a coal mine roadway bottom plate is not accurate is solved. The method comprises the following steps: determining an evaluation index according to a main control factor of a coal mine tunnel floor grouting effect; standardizing the plurality of groups of evaluation index data by using MATLAB (Matrix Laboratory); a CRITIC method is used for giving weights to the evaluation indexes, a CRITIC-CEO-KMeans grouting effect prediction model is constructed, an evaluation database of the coal mine tunnel floor aquifer grouting effect is constructed, evaluation index data of a to-be-evaluated sample is input into the evaluation database, a prediction result is output, and grouting effect grades are divided. According to the method, the prediction accuracy of the coal mine tunnel floor grouting effect can be improved, and technical guidance is provided for improving the mine deep mining safety.

The application provides a super-large three-dimensional deep metal mine intelligent ventilation simulation system, and relates to the technical field of deep metal mine ventilation. The system comprises a deep metal mine complex ventilation roadway and stope structure simulation module for simulating underground roadway, stope and heading face of a deep metal mine; a roadway constant temperature control module for simulating preset rock temperature of a roadway and regulating temperature of a simulated roadway test section; an adjustable air source input control module for providing an air source meeting preset temperature, humidity and flow rate for the underground roadway and stope of a mine; a pollutant stable release module for simulating preset concentration release of dust, gun smoke and multi-component pollutant gas in deep mining operation; a particle image velocimetry module for realizing fluid dynamics measurement of multi-phase and multi-component air flow of the simulated roadway test section and stope; and an intelligent ventilation control module for realizing monitoring, calculation and automatic control of multi-element air flow information in the simulated roadway and stope and ventilation facilities.

The present application relates to a kind of triaxial coupling test active deformation testing device and testing method, the device includes rack, two cylindrical test cylinders are symmetrically arranged on the rack, confining pressure power mechanism and hydraulic pump station, the two ends of test cylinder are respectively provided with flange, two test cylinders are detachably connected by flange, two test cylinders form closed complete test cylinder after butt joint, displacement pressure mechanism is provided at one end of test cylinder.The testing device provided by the present application meets the current deep mining conditions: different confining pressure conditions, different moisture content conditions, different media, active deformation test device of interactive filling.By active deformation test, the fiber-soil coupling deformation mechanics characterization under the condition of multiple media replacement interaction is researched.

The application discloses a ground pressure management system suitable for deep mining of underground mines, and relates to the technical field of mine safety monitoring and intelligent control, comprising a perception and collection layer, a transmission and communication layer, a data processing and analysis layer, a risk assessment and early warning layer and a linkage control layer; by arranging multiple types of monitoring units at key parts of the stope, roadway and support, multi-source data such as surrounding rock stress, deformation, dynamic response, support state and environmental disturbance are obtained, and after unified processing by an edge gateway, the data are transmitted to the analysis layer for fusion modeling and abnormality identification. Based on multiple indexes, a comprehensive risk evaluation system is constructed, and dynamic weights are used to realize risk grading and trend prediction, and generate early warning information. The system further links pressure relief, support, mining adjustment and personnel and equipment control measures, and realizes parameter self-adaptive correction through a feedback mechanism, forming a closed-loop management. The system improves the ground pressure monitoring precision, early warning accuracy and disposal efficiency of deep mines.

The invention provides a goods-carrying person recommendation method and device, electronic equipment and a medium, and relates to the technical field of big data processing, and the method comprises the steps: obtaining the commodity information of a to-be-promoted commodity and the user portrait data of at least one goods-carrying person; performing feature extraction on the commodity information of the to-be-promoted commodity, and obtaining commodity feature data of each preset dimension of the to-be-promoted commodity; the preset dimension comprises at least one of a commodity content attribute dimension, a commodity commercial attribute dimension and a commodity target audience dimension; according to the user feature data corresponding to the commodity feature data of each preset dimension in the user portrait data of the cargo-carrying person, determining the matching degree of the cargo-carrying person and the to-be-popularized commodity in each preset dimension; and determining at least one target cargo-carrying person from the at least one cargo-carrying person according to the matching degree of the cargo-carrying person and the to-be-popularized commodity on each preset dimension. According to the method, multi-dimensional deep mining is realized, and the objectivity and accuracy of matching of the commodity and the commodity-carrying person are improved.

The invention discloses a coal seam floor water guide crack identification method based on micro-seismic Krauklis waves, and belongs to the technical field of coal seam floor water disaster detection.The method comprises the steps that firstly, micro-seismic original signals are collected and segmented, and continuous wavelet transformation and time-frequency domain conversion are sequentially carried out on each signal segment to obtain a time-frequency spectrogram; according to the time-frequency spectrogram, separating and extracting the time-frequency characteristics of the Krauklis waves; for each frequency, determining an energy extreme point corresponding to the frequency and Krauklis wave energy packet arrival time; a frequency dispersion curve is obtained by calculating the phase velocity of each frequency, and the slopes of different positions of the frequency dispersion curve are obtained through calculation; establishing a quantitative mapping model between the crack opening and the frequency dispersion curve slope on the basis of the propagation theory of Krauklis waves in the slab crack; and the slope is substituted into the quantitative mapping model for inversion, so that the average opening degree of the water guiding crack in the current detection area is accurately obtained, and data support is provided for accurate monitoring and early warning of water inrush of a deep mining coal seam floor.

The invention provides an intelligent rail smoothness adjusting method and system based on dynamic detection and big data analysis, and belongs to the technical field of railway engineering maintenance. The method comprises the steps that track geometric data, vehicle dynamics response data and environment data are collected in real time through a multi-dimensional sensor array installed on an operating train; uploading the data to a cloud big data platform for fusion and deep mining, constructing a track state degradation prediction model by using a machine learning algorithm, and accurately predicting the development trend of track irregularity; and based on the prediction result, automatically generating a targeted track fine adjustment scheme, and issuing the scheme to an intelligent maintenance robot deployed on the line or guiding a manual maintenance team. The system comprises a data acquisition layer, a cloud analysis layer and an intelligent execution layer. According to the method, the change of the track state from'regular maintenance 'to'predictive maintenance' is realized, the maintenance efficiency, the precision and the line smoothness are remarkably improved, and the maintenance cost of the whole life cycle is reduced.

The invention discloses a power grid customer appeal mining method and system, and the method integrates regional meteorology, customer service data and geographic information, constructs a'micrometeorology-regional customer-microtopography 'coupled space-time dynamic model, and achieves the precise early warning of regional power supply service risks in extreme weather. The method comprises the following steps: constructing an electric power emergency dynamic knowledge graph by utilizing a natural language processing technology, performing semantic analysis and structured storage on unstructured laws and regulations, plans and cases, and establishing a dynamic updating mechanism; according to the method, an emergency response agent based on a generative large model is constructed, context perception and deep mining are carried out on customer complaints and appeals through a retrieval enhancement generation technology, and accurate, professional and personalized reply content is automatically generated. According to the method, the problems that the existing power customer service technology knowledge is lagged in updating, is disjointed with real-time business data, and is weak in complex context understanding capability are effectively solved, and the intelligent level and the operation efficiency of the power grid customer service are remarkably improved.

The invention relates to the technical field of coal mine simulation tests, in particular to a gas and underground water simulation test device and method.The gas and underground water simulation test device under coal mine fault disturbance comprises a vibration box and an installation box arranged on one side of the vibration box, and a servo driving assembly is arranged in the installation box; the servo driving assembly is connected with a vibration arm capable of knocking the vibration box periodically. The fault simulation unit has a fault closed state and a fault extension state, and when the driving piece drives the fault simulation unit to be converted from the fault closed state to the fault extension state through the pushing plate, liquid in the water tank is sprayed outwards through the spraying shaft to simulate underground water seepage. Meanwhile, the airflow generating plate sprays air outwards to simulate gas seepage, and the technical problem that an existing testing device cannot synchronously simulate the fault slippage and catastrophe process induced by dynamic disturbance and multi-physical field dynamic coupling in coal mine deep mining is solved.

The invention discloses a grouping, zoning and staggered bidirectional continuous collaborative mining process for large and small stopes, and relates to the technical field of underground mining of metal ore deposits. The method comprises the following steps: S1, mining area division: dividing an ore body into a plurality of mining stages in the vertical direction, and dividing a plurality of stoping unit combinations along the trend of the ore body in two adjacent stages; wherein each stoping unit combination comprises a large stope located at the current stage and two small stopes located at the corresponding positions of the current stage and the upper stage correspondingly. According to the mining method, pillar-free safe and efficient mining is achieved, and the resource recovery rate is remarkably increased. Through the combination of the large stopes and the small stopes and the time-staggered cooperation sequence from bottom to top and from small to large, a high-strength filling supporting body is constructed in the vertical direction, continuous backward-return mining is achieved in the horizontal direction, and a two-way continuous operation mode is formed. The rock drilling chamber is dual-purpose, the mining and cutting work amount is greatly reduced, the ground pressure is effectively controlled through active supporting of the high-strength filling body, and deep mining safety is guaranteed.

The invention relates to the technical field of steel and iron material research and development, in particular to an intelligent steel and iron material research and development system and method, and the system comprises a high-throughput calculation data module, a laboratory data module, a machine learning model training module, a material performance prediction module and a multi-objective optimization module. By integrating multi-source data of the whole life cycle of steel and iron material research and development, production and application, information islands are eliminated, comprehensive display and comprehensive analysis of steel and iron material research and development data are achieved, deep mining and application are conducted on the data through a machine learning algorithm, the efficiency and accuracy of new steel grade research and development are improved, a multi-target optimization function is provided, and the research and development efficiency is improved. Various performance indexes of the material can be optimized at the same time, the requirements of complex application scenes are met, a large model auxiliary research and development function is provided, help and guidance can be provided at any time in the steel material data analysis and component process design process by research and development personnel, and the material development process is accelerated.

The invention discloses a multi-modal tunnel construction risk assessment method and system, and belongs to the field of construction risk assessment, and the method comprises the steps: carrying out the preprocessing of collected tunnel construction multi-modal data, and integrating the multi-modal data into a cloud multi-modal database; performing data fusion processing on the data of the multi-modal database through a gating multi-modal fusion method to obtain a fusion feature containing a plurality of physical parameters; mapping the fusion features into specific physical parameters through a physical parameter decoder, and performing risk assessment through a multi-environmental factor risk assessment model in combination with the physical parameters; and importing a risk assessment result into the BIM model, and displaying current and future risk areas, risk levels and potential risk types in the tunnel construction process. According to the method, the multi-physical field control equation set, the inter-field coupling mechanism and the risk prediction model are combined, and deep mining and intelligent analysis of multi-modal data are achieved.

The invention relates to a gob-side roadway rock burst prevention and control method of a directional powder punching drilling pre-splitting coal body, and belongs to the technical field of coal mine rock burst prevention and control. The method comprises the following steps: determining a pressure peak position and delimiting a drill hole presplitting pressure relief boundary by acquiring lateral bearing pressure distribution data of a goaf; determining a drilling parameter group according to the boundary position relationship, wherein the drilling parameter group comprises drilling diameter, spacing, length and angle; a directional drilling machine is arranged in the preparation roadway, directional powder flushing drilling holes are formed through construction, and the coal powder is flushed out to increase the deformation space through the high-pressure water powder flushing technology; and the pressure relief effect is monitored through the stress detection device. According to the method, accurate positioning pressure relief, differential parameter design and advanced pressure relief area formation are achieved, the problems that a traditional method is high in risk, low in speed and poor in effect are effectively solved, the safety and efficiency of gob-side roadway rock burst prevention and control are remarkably improved, and scientific and reliable technical guarantee is provided for deep mining of a coal mine.

The invention relates to the technical field of electric power informatization, in particular to a deep mining and structured intelligent auditing method and system oriented to high and low voltage electric power user address data and a computer readable storage medium. Address standardization is achieved through multi-source data cleaning and duplicate removal, electric power exclusive unified coding formulation and three-level restoration of regular fuzzy matching, alias mapping conversion and hierarchical membership completion; an address feature-voltage class rule base is established, and association between addresses and voltage classes is established through forward and reverse verification; intelligent monitoring and closed-loop optimization are realized by combining scenarized hierarchical verification and business system coupling. The method improves the qualified rate of the address data, reduces the labor cost, and achieves the collaborative optimization of data management and business application.

The invention discloses strip mine transportation equipment based on a large dip angle, and belongs to the field of surface mine production. The strip mine transportation equipment comprises a crawler belt and a U-shaped bucket arranged on the crawler belt; the crawler belt is fixed on the ground through a support, and one end of the crawler belt is provided with a hopper for filling materials. By means of the core structure design of the crawler belt and the U-shaped bucket, the climbing capacity of the crawler belt can reach 30-45 degrees (the climbing capacity can be higher under part of special configuration), the crawler belt can stably run along the final slope angle of the strip mine by combining the arc-shaped anti-skid line crawler belt and the carbon steel U-shaped bucket in rigid connection, and the service life of the crawler belt is prolonged. The industrial pain point that traditional rubber belt conveying equipment cannot climb up at a large dip angle and cannot convey materials is thoroughly solved, the rubber belt conveying equipment can adapt to modern strip mine scenes with deep mining and steep slopes, additional slope leveling or gentle slope road laying for the adaptive equipment is not needed, and the mine site transformation cost is greatly reduced.

The ultra-deep large-aperture comprehensive drainage device comprises a segmented drainage mechanism and a direct drainage mechanism, the segmented drainage mechanism comprises a first-stage drainage component and a second-stage drainage component, the first-stage drainage component is located at the bottom of a well, the second-stage drainage component is located above the first-stage drainage component, and the direct drainage mechanism is located above the second-stage drainage component. The direct drainage mechanism comprises a direct drainage pump, a direct drainage bin and a direct drainage hole, the direct drainage bin is used for being communicated with a drainage hole connecting lane at the bottom of the well, a water inlet pipe of the direct drainage pump is connected with the direct drainage bin, and a water outlet pipe of the direct drainage pump is connected with the direct drainage hole. And the direct drainage holes are vertically formed and extend upwards from the well bottom to the ground surface. The segmented drainage mechanism and the direct drainage mechanism are combined, the overall drainage amount is increased, the requirement for ultra-deep mining drainage is met, when one drainage mechanism breaks down, the other drainage mechanism can continue to drain water, it is guaranteed that underground water is drained in time, and normal production of a mine and underground safety are guaranteed.

The application discloses a kind of electrostatic dust concentration measurement method and system based on spectrum analysis, belong to dust concentration measurement technical field, the present application is based on traditional electrostatic induction measurement method, by deep mining spectrum information, electrode pollution spectrum diagnosis and self-healing are realized, quantitative evaluation pollution index and realize signal reconstruction, non-steady-state condition adaptive measurement, dynamic adjustment analysis window and directly output mass flow, life cycle management, measurement precision is significantly improved.

The utility model provides a ventilation structure for downward horizontal layered drift filling mining of a deep metal mine, and belongs to the field of deep mining of metal mines. Comprising a plurality of subsection transportation roadways, a lower subsection connection roadway used for communicating an access stope with a mine hanging wall and a mine footwall, and a ventilation inclined shaft used for communicating an upper subsection connection roadway with the lower subsection connection roadway; the ventilation inclined shaft is arranged in a filling body near footwall surrounding rock, the extending direction of the ventilation inclined shaft is parallel to the contact face of the footwall surrounding rock and the filling body, and the ventilation inclined shaft is formed by splicing a plurality of hard pipe fittings. A first air duct extending to the tunnel face of the access stope along the roadway and a first fan connected with the first air duct are arranged in the lower section connection roadway; and a second air duct which extends to the communication part of the second section transportation roadway and the upper section connection roadway along the roadway and a second fan which is connected with the second air duct are arranged in the upper section connection roadway. According to the structure, the air return path is shortened, the construction difficulty is remarkably reduced, and the construction cost is reduced.

The application discloses an electric automation production process data acquisition and analysis system and method, aiming at solving the problems of incomplete data acquisition, insufficient accuracy, unstable transmission, single analysis dimension, lagging early warning and disconnection between analysis and control in the prior art. The system comprises a multi-source heterogeneous data acquisition module, a dynamic adaptive transmission module, a hierarchical progressive analysis module, a closed-loop feedback control module and a data storage encryption module. The method realizes the steps of multi-source data acquisition and calibration, dynamic transmission adaptation, hierarchical progressive analysis, closed-loop feedback control and data storage encryption. The scheme realizes full-dimensional production data acquisition, efficient and stable transmission and deep mining, accurately predicts fault hidden dangers, realizes closed-loop linkage of analysis and control, improves the stability, energy efficiency and intelligent level of electric automation production, and the terms correspond to the claims without abbreviations, which is suitable for various electric automation production scenes and has outstanding creativity and practical value.

The present application belongs to the field of coal mining, and particularly relates to a coal mining-filling working face layout method based on surface subsidence control requirements. First, the minefield is divided based on surface subsidence control requirements of different regions, and the coal mining-filling working face is arranged in the minefield region without surface subsidence control requirements. Then, for the region with surface subsidence control requirements, it is judged in turn whether the coal mining-filling working face is suitable to be arranged, whether only the filling working face is suitable to be arranged, whether the strip mining working face is suitable to be arranged, and whether the overburden separation grouting working face is suitable to be arranged, and the mining parameters can be adjusted appropriately. The present application coordinates the layout of the underground coal mining-filling working face based on the surface subsidence control requirements, fully develops the advantages of the two types of mining processes, reduces the land resource damage and ecological environment deterioration caused by coal mining, improves the coal recovery rate, provides a reference for the planning and layout of the underground coal mining-filling working face and dynamic adjustment, and is beneficial to the safe, efficient and green mining of the deep mining and selection integrated mine.

The invention relates to the technical field of shale oil and gas drilling intellectualization, in particular to a drilling benchmark library management method and system based on a big data analysis technology. According to the method, a dynamic benchmark library of multi-dimensional drilling index data is constructed by performing intelligent analysis on massive drilling historical data, and an optimal drill bit model, an optimal drilling tool combination and optimal drilling parameters considering geological conditions are automatically pushed based on an auxiliary model selection decision optimization model, so that'data-model-decision 'closed-loop management is formed; according to the method, comprehensive analysis and deep mining of the drilling historical data are realized, the potential value of the data is brought into full play, the value conversion efficiency of the drilling data is improved, an innovative technical solution is provided for intelligent decision making, efficiency improvement and cost control of the whole process of drilling engineering, and the method is worthy of popularization and application. The method effectively promotes transformation of drilling engineering from traditional experience decision to data-driven scientific decision, is suitable for the field of drilling of different types of shale oil and gas, and has wide applicability and popularization value.

The application relates to an intelligent factory management and control platform system, and relates to the technical field of industrial automation.The system comprises a data acquisition module, which is used for collecting state data and production environment parameters of production equipment in real time through a plurality of Internet of Things sensors arranged on a production line.The state data comprises temperature, pressure and vibration frequency.In the application, firstly, massive raw data are subjected to localized real-time processing and feature extraction through an edge computing node, so that the load pressure of a network and a central server is significantly reduced, and millisecond-level rapid response to equipment emergency abnormalities is realized;secondly, an artificial intelligence analysis engine integrated in the central server is used for deep mining and predictive analysis of the simplified data, so that a leap from passive alarm to active prediction is realized, potential equipment faults and production abnormality trends are accurately identified;and thirdly, the system is further combined with intelligent visual monitoring, so that real-time compliance detection of personnel operation and material state is realized.

The present application provides a mine rock stratum displacement deformation detection method and system for deep mining, relates to the technical field of mine detection, and comprises the following steps: obtaining rock stratum multidimensional physical field data through a detection sensor, performing spatial discretization processing, identifying a stress gradient abnormal area, establishing a correlation between the stress gradient abnormal area and a displacement field direction feature, calculating a rock stratum residual bearing capacity, and generating safety margin distribution data. The present application can accurately identify rock stratum damage precursors, provide a scientific basis for pressure relief measures, and improve deep mining safety.

This invention provides a method and system for deep mining of job-seeking dialogue intent applied to college student employment guidance. First, it acquires a set of dialogue data of target users in a job-seeking guidance scenario. This set of data contains multiple dialogue sequences arranged chronologically. Next, it extracts features from the dialogue data set to generate semantic association features and interactive behavior features. Then, based on a preset intent recognition network, it performs intent recognition on the semantic association features and interactive behavior features, generating a set of intent classification tags to indicate the distribution priority of users' potential job-seeking needs. Finally, it constructs an intent optimization strategy based on the intent classification tag set and feeds it back to the dialogue service module of the job-seeking guidance system to adjust the response content generation rules, thereby improving the service quality of the guidance system.