3970results about "Tunnel/mines ventillation" patented technology

The invention discloses a coal mine ventilation system intelligent regulation and control method based on environmental perception, and relates to the technical field of coal mine ventilation system intelligent regulation and control, and the method comprises the following steps: collecting environmental data of different areas of a mine, including gas concentration, temperature and humidity, air velocity and oxygen content, and monitoring the operation state of ventilation equipment in real time; data of all the sensors are synchronously processed through the data fusion technology, and a unified environment sensing model is generated. According to the invention, through cooperative work of the expert system and deep learning, real-time monitoring and emergency plan execution under extreme working conditions are realized, and the response speed and decision accuracy are improved. A reinforcement learning algorithm is adopted to optimize ventilation line switching, the adaptive capacity and redundancy guarantee of the system are enhanced, and it is ensured that airflow is not interrupted at the critical moment. Through abnormality comparison of the knowledge base and the rule base, false alarm and misjudgment are reduced, system efficiency is improved, operation burden is relieved, and safety and stable operation of mine personnel are guaranteed to the maximum extent.

The invention relates to the technical field of mine ventilation, in particular to a mine ventilation dynamic regulation and control method and system based on a space-time diagram convolutional network, and the regulation and control method comprises the following steps: 1, carrying out the modeling and data collection of a ventilation system; step 2, modeling and anomaly prediction of the graph convolutional network; step 3, generation and execution of a ventilation equipment coordinated regulation and control strategy; step 4, edge node calibration and model optimization; and 5, performing full-process control and emergency response. A ventilation network topological structure and multi-modal time series data are fused through a space-time diagram convolutional network, a joint model containing spatial feature extraction and time series modeling is constructed, 30-minute early warning of ventilation abnormity and propagation path prediction are achieved, the lag response limitation that a traditional system only depends on a single parameter threshold value is broken through, and the risk pre-judgment capability is improved.

The invention discloses a tunnel segmented exhaust method and system based on train working conditions, a medium and a product, and relates to the technical field of ventilation. The method comprises the steps that a target tunnel is divided into a plurality of control sections according to fan installation configuration of the target tunnel; acquiring train passing data and train configuration information of the control section, and calculating a flue gas growth value of the control section in a preset time period; collecting flue gas concentration data of the control section, and calculating a ventilation demand index of the control section in combination with the flue gas growth value; collecting wind direction parameters of the control sections, determining a ventilation control relationship between the adjacent control sections based on the ventilation demand indexes and the wind direction parameters, and generating a ventilation cooperation scheme; according to the ventilation cooperation scheme, operation parameters of the tunnel fans in all the control sections are calculated, and control instructions corresponding to the operation parameters are sent to the tunnel fans. By implementing the application, the fan operation can be adjusted according to the actual train operation condition, and the ventilation effect is optimized.

The invention provides a tunnel fan group cooperative control dynamic optimization method and system. According to the method, dynamic data of vehicles in a tunnel are tracked through the Leiyu fusion technology, and a multi-dimensional game parameter set is constructed in combination with edge computing node analysis data and environment monitoring indexes. Based on a dynamic game theory model, fan cooperative response intensity is dynamically adjusted, smoke exhaust efficiency and evacuation channel wind speed constraint are balanced, fan control priority is calculated, differential rotating speed and deflection angle control is driven, and game strategy weight is iteratively optimized after environment feedback data is generated. And realizing rolling time domain control until the vehicle movement and the environment index reach a stable interval. According to the technical scheme provided by the invention, dynamic collaborative optimization of tunnel smoke exhaust and evacuation safety is realized, and the ventilation response efficiency and the evacuation channel safety in an emergency scene are improved.

The invention discloses a management system for real-time monitoring and early warning of mine coal and gas outburst parameters, and belongs to the field of safety production, and the management system specifically comprises the steps: collecting gas and ground stress data in a mine in real time through a gas sensor and a microseismic sensor, and carrying out the real-time monitoring and early warning of the mine coal and gas outburst parameters through a time sequence analysis and spatial data mining technology and a multi-scale coupling strategy; identifying the change rule and potential correlation of the crustal stress and the gas parameters; a comprehensive outburst analysis and prediction model is established, the coal and gas outburst risk level is evaluated, and a three-level early warning mechanism and an emergency plan are designed; the method can be flexibly adjusted according to actual conditions of a mine, coal and gas outburst accidents are effectively prevented and controlled, and the safety of the mine is improved.

The invention discloses a coal mine ventilation optimization and air quality regulation and control method based on adaptive learning, and relates to the technical field of coal mine ventilation optimization, and the method comprises the following steps: arranging a plurality of sensors in a mine, carrying out the real-time collection and monitoring of key environment parameters, and uploading the collected data to a central control system; and comparing the collected real-time data with historical data, and dividing the collected real-time data into conventional working condition data and abnormal working condition data according to environment states. Through real-time monitoring of various sensors and a deep learning algorithm, accurate ventilation control is achieved, a problem area is rapidly positioned in an emergency, airflow is dynamically adjusted, and safety of miners is guaranteed. According to the system, an LSTM model is adopted to predict an event trend in advance, preventive regulation and control measures are taken in time, real-time adjustment is supported, and the strain capacity is improved. Through a multi-stage ventilation mode, the system optimizes energy consumption and equipment operation efficiency, reduces unnecessary energy waste and maintenance cost, and realizes balance between safety and economy.

The invention discloses a tunnel fan energy-saving control method and system, a storage medium and a program product, and relates to the field of general control or regulation systems.The method comprises the steps that historical train flow data are obtained, and the predicted train flow of the next time period is obtained through calculation according to the historical train flow data; collecting real-time gas concentration data and wind speed and direction data; calculating a theoretical gas concentration increment based on an aerodynamic model, the predicted train flow, the real-time gas concentration data and the wind speed and direction data; calculating according to the theoretical gas concentration increment and a pollutant diffusion model to obtain a pollutant diffusion trend; determining a target section according to the pollutant diffusion trend and a preset gas concentration threshold value; according to the position information of the target section and the pollutant diffusion trend, the minimum starting number of tunnel fans and the corresponding minimum rotating speed are obtained through calculation; and generating a fan control instruction according to the minimum number of started fans and the minimum rotating speed. According to the method, the effect of reducing the energy consumption of the tunnel fan while the ventilation effect of the tunnel is maintained is achieved.

The invention relates to the technical field of tunnel ventilation control, in particular to a tunnel fan energy-saving control system which comprises a multi-parameter sensing module, an intelligent evaluation module, a dynamic prediction module, an energy-saving optimization module, a frequency conversion control module and an alarm emergency module. Wherein the multi-parameter sensing module is used for monitoring various environmental parameters in a tunnel in real time; the intelligent evaluation module is used for calculating the current ventilation demand; the dynamic prediction module is used for predicting the ventilation demand in a period of time in the future; the energy-saving optimization module is used for generating an optimal energy-saving control instruction; the frequency conversion control module is used for adjusting the operation frequency and speed of the fan according to the instruction; and the alarm emergency module is used for sending an alarm signal when an abnormal condition is detected. According to the invention, environmental parameters in the tunnel are monitored and intelligently managed in real time, a fan operation strategy is dynamically optimized, and the system has emergency response capability, so that the ventilation efficiency is remarkably improved, the energy consumption is reduced, and the construction safety is guaranteed.

The invention relates to the technical field of mine mining, and discloses an underground multi-parameter environment monitoring method, which comprises the following steps of: acquiring equipment pose, vibration spectrum and environment parameters in real time through a multi-source sensor, performing space-time alignment, filtering noise reduction and feature extraction on original data, outputting a standardized state vector, and performing data processing on the standardized state vector; fusing the pose data, the vibration signals and the environmental parameters under a unified space-time reference to construct a multi-dimensional feature matrix; and carrying out dimension reduction and redundant information elimination by adopting principal component analysis, and outputting a fused equipment state vector. According to the method, through real-time fusion of the equipment pose and the airflow dynamic state, the ventilation equipment is cooperatively regulated and controlled, the interference of mechanical vibration on the gas monitoring precision is eliminated and the reliability of gas concentration detection is guaranteed based on coupling modeling of vibration spectrum and pose drift and intelligent compensation of sensor reading errors, and through space correlation analysis and dynamic air volume optimization, the gas concentration detection accuracy is improved. Wind speed sudden drop caused by tramcar passing is actively eliminated, and roadway global continuous monitoring is achieved.

The invention discloses a coal mine ventilation and heat reduction integrated control method based on intelligent scheduling, and relates to the technical field of coal mine ventilation and heat reduction control, and the method comprises the following steps: arranging a plurality of monitoring devices on a ventilation path and a standby ventilation path of a mine, and collecting temperature, humidity, gas concentration and wind speed and volume data; the central control system gathers monitoring data in real time, analyzes the ventilation condition in the air duct and identifies whether abnormal changes exist or not. Continuous ventilation is ensured through multi-path redundancy and dynamic switching, risks of gas explosion and the like are reduced, early warning is performed by means of the airflow simulation model, and safety of miners is guaranteed. And in combination with a reinforcement learning algorithm and a simulation model, quick response and self-adaptive adjustment are realized, air distribution is optimized, shutdown is avoided, and economic benefits are improved. Meanwhile, by intelligently planning a ventilation path and dynamically adjusting the fan load, energy consumption and maintenance cost are reduced, the service life of equipment is prolonged, and sustainable operation of a mine is promoted.

The invention discloses an intelligent regulation and control method and system for dust removal and air control of an underground high-gas heading face, and relates to the field of intelligent control. Firstly, an environment parameter set and an equipment parameter set are obtained in real time; constructing a digital twinborn model of the tunneling face and the ventilation system based on the environmental parameter set and the equipment parameter set, and simulating gas concentration and dust concentration under different working conditions; the prediction model predicts the gas emission amount trend and the dust concentration trend; and inputting the environment parameter set, the equipment parameter set and the risk level into an optimization model, and generating a target decision instruction by the optimization model. The operation parameters in the ventilation system can be timely regulated and controlled in real time based on the monitored environment parameter set of the tunneling face and the equipment parameter set in the ventilation system, so that the ventilation and dust removal efficiency of the ventilation system is improved. Moreover, the decision instruction is generated by referring to the trend of the gas emission amount and the dust concentration in the future, so that the accuracy of the decision instruction of the ventilation system is further improved.

The invention relates to the field of mine ventilation, in particular to an intelligent adjusting method and system for mine ventilation. The method comprises the following steps: constructing a dynamic topology model taking a roadway as an edge and taking a fan and an air door as nodes based on a mine CAD drawing; acquiring the actual wind pressure and the actual wind volume of each roadway branch in real time, performing inversion to obtain the current wind resistance, and updating the wind resistance attribute of the edge in the dynamic topology model by using the current wind resistance; calculating the optimal air volume of the roadway branch by using the updated dynamic topology model; based on the optimal air volume, target regulation and control parameters of the draught fan and the air door are obtained through solving by means of a particle swarm algorithm; and according to the target regulation and control parameters, the fan and the air door are adjusted through a fuzzy PID algorithm. The problem that in the prior art, mine ventilation adjustment is not intelligent and safe enough is solved, the theoretical optimal air volume is obtained through deep analysis of the mine, then ventilation adjustment is conducted step by step, and the scientificity and efficiency of ventilation adjustment are improved.

The invention relates to the technical field of mine ventilation control, in particular to a mine fan ventilation control method and system based on digital twinning. The method comprises the following steps: carrying out data preprocessing on acquired mine monitoring data; performing feature extraction on the preprocessed mine monitoring data; utilizing a random forest algorithm to predict the relationship between the data characteristics and the fan air volume; a digital twinborn model is used for resolving the relation between the data characteristics and the fan air volume, and a fan ventilation control strategy is obtained; and generating a PLC control instruction based on the fan ventilation control strategy. And through multi-source data fusion and deep analysis, the real-time ventilation requirement of the mine can be accurately grasped. Based on random forest algorithm prediction and digital twinborn model calculation, dynamic and accurate adjustment of the air volume of the draught fan is achieved, it is ensured that the concentration of harmful gas in all underground areas is maintained within a safety threshold value, the oxygen content is sufficient, an ideal environment is created for personnel operation and equipment operation, and the safety and reliability of a ventilation system are remarkably improved.

The invention discloses a tunnel traffic control method and system for multi-mode traffic variable analysis, and relates to the field of general control or regulation systems, and the method comprises the steps: obtaining vehicle operation state information and pollutant concentration distribution data, determining a pollutant generation region based on a vehicle state, and calculating a concentration gradient value and a diffusion rate value. And analyzing the concentration change trend according to the spatial-temporal distribution relationship, and dividing a vertical control region. And setting initial operation parameters of the jet fan in a preset adjustment range and a step length according to the pollutant distribution characteristics of each area. And monitoring area concentration distribution in real time, when a target area exceeds the standard, dynamically adjusting fan parameters of the area and an adjacent area to preset values, and setting illumination parameters of illumination equipment in the vertical control area according to pollutant concentration distribution characteristics. By implementing the method, the accuracy of tunnel partition environment parameter adjustment can be improved.

The invention relates to a dynamic regulation and control method and system for mine ventilation. The method comprises the following steps: acquiring multi-source data in a mine, and preprocessing the multi-source data to obtain a standardized data set; calculating the risk of each region in the mine based on the standardized data set to obtain a risk prediction matrix; based on the standardized data set and the risk prediction matrix, the air volume demand of each area is calculated, and an air volume demand table is obtained; based on the air volume demand table, an optimization proposition corresponding to the air volume demand is constructed and solved, and a solution set of the optimization proposition is obtained; mapping the solution set based on a preset rule to obtain a feasible allocation scheme; and based on the feasible allocation scheme, generating an equipment cooperation instruction, and obtaining a security instruction set. According to the method, dynamic factors can be considered, the air volume is dynamically adjusted, multi-fan cooperation is achieved, and the effects of real-time sensing and autonomous dynamic decision making of mine ventilation are achieved.

The invention relates to the technical field of deep learning, in particular to an air speed regulation and control method and system for a tunnel air supply outlet based on deep learning. The method comprises the following steps: acquiring environmental parameter data at different time points in a tunnel; preprocessing the acquired environment parameter data; performing data set division based on the environmental parameter data to obtain a training set and a test set; constructing an air speed regulation and control model for the tunnel air supply outlet based on deep learning; performing feature extraction on the data set by using a wind speed regulation and control model for the tunnel air supply outlet; predicting the extracted features by using a long-short-term memory network to obtain a prediction result; and performing wind speed regulation and control according to a prediction result. The wind speed regulation and control model for the tunnel air supply outlet is constructed based on deep learning, and the complex non-linear relation between the environment parameters and the wind speed can be effectively captured.

The invention relates to the technical field of mine environment control, and discloses an intelligent environment monitoring and control method in a mine laneway. The method comprises the steps that a real-time environment parameter set of a mine laneway is collected, the set contains gas concentration data, dust concentration data and temperature and humidity data, and real-time capture of laneway environment multi-dimensional parameters is achieved; then, based on the collected real-time environment parameter set, calculating an environment safety evaluation index so as to scientifically and objectively reflect the roadway environment safety condition; a dynamic control strategy is generated according to the environmental safety evaluation indexes, and the strategy comprises ventilation equipment regulation and control parameters and early warning level parameters and can be flexibly adjusted according to environmental changes; and finally, the ventilation equipment regulation and control parameters are sent to a mine ventilation system, and roadway environment regulation and control are executed. According to the method, environmental parameters can be comprehensively monitored, safety risks can be accurately evaluated, ventilation equipment can be flexibly regulated and controlled, the early warning function can be perfected, energy waste can be reduced, labor intensity can be reduced, and underground operation safety and mining efficiency can be guaranteed.

The invention relates to the technical field of underground operation safety and ventilation, and discloses an intelligent ventilation safety system suitable for underground operation, which comprises a data acquisition and transmission module used for acquiring underground environment data in real time and transmitting the underground environment data to a control center; the intelligent control module is used for dynamically adjusting the wind speed according to the real-time data so as to ensure that the gas concentration is within a safe range; the optimization decision module is used for calculating and generating an optimal wind speed regulation scheme through an optimization algorithm; the execution feedback module is used for adjusting the wind speed of an underground fan and a ventilation pipeline according to the instruction of the optimization decision module; and the safety early warning module is used for monitoring the change of the gas concentration in the underground environment in real time and sending out an alarm signal when detecting that the gas concentration exceeds the standard. Through intelligent wind speed adjustment and ventilation pipeline control, in combination with real-time data collection and optimization decision, accurate adjustment of the underground environment is achieved, safety and energy efficiency are improved, and the problems of energy waste and inaccurate gas concentration control are avoided.

The invention belongs to the technical field of highway tunnel ventilation control, and provides a highway tunnel ventilation control method and system. The method comprises the following steps of multi-source heterogeneous data acquisition, multi-source data fusion, state estimation, traffic flow prediction, dynamic pollution index calculation and multi-target weight generation, rolling optimization with constraints, control execution, model updating and feedback correction. The state sensing precision is improved through multi-source data fusion, real-time accurate estimation and error reduction of a pollutant concentration field and a traffic flow state are realized through a heterogeneous sensor and a Rayleigh fusion technology, the problem of sensing deviation caused by single data in a traditional method is solved, future traffic flow is predicted based on a graph neural network, and the traffic flow sensing accuracy is improved. The fan power is optimized through model prediction control, the ventilation intensity is adjusted in advance, pollutants are prevented from exceeding the standard, the response speed is increased compared with threshold value control, and energy consumption is reduced.

The invention relates to the technical field of mine intelligent ventilation, and discloses a mine intelligent ventilation system which comprises a mine ventilation environment parameter monitoring system, an air door and air window automation and remote control system, a local ventilator intelligent control system, a main ventilator intelligent monitoring system and an analysis decision platform. In the mine ventilation environment parameter monitoring system, according to the principle of mine ventilation resistance measurement, a ventilation route of a mine is selected, multi-parameter sensors are arranged at nodes, air pressure, temperature, humidity, wind speed and wind quantity at the starting end and the tail end of each roadway of the mine are monitored in real time, and node air density is calculated. According to the intelligent ventilation system for the mine, real-time wind measurement improves the wind measurement precision and frequency of the mine and reduces the workload of manual wind quantity detection, meanwhile, the number of wind measurement staff can be properly reduced, manual inspection tour and unattended operation of wind measurement work are achieved, and therefore expenditure is reduced.

The invention discloses a tunnel ventilation control system and method based on artificial intelligence, and relates to the technical field of ventilation control, and the method comprises the steps: in a tunnel design stage, building an unsteady-state computational fluid dynamics model based on tunnel three-dimensional linear parameters, calculating turbulence structures under different traffic conditions through a large eddy simulation method, and calculating an unsteady-state computational fluid dynamics model; determining an optimal space configuration scheme of the fan group according to the distribution of the velocity field and the pressure field; in the tunnel construction stage, multiple types of sensor arrays are arranged along the vault and the side wall of a tunnel in a layered mode; in the tunnel operation stage, real-time vehicle tracks and speed distribution information of a traffic monitoring system are obtained; establishing a ventilation demand dynamic prediction model based on space-time correlation analysis, constructing a fan cooperative control model considering airflow organization optimization, and solving an optimal operation strategy by adopting a multi-target adaptive weight distribution algorithm; when a fire characteristic signal is monitored, the multiple sets of fans are coordinated to form a relay type smoke exhaust airflow organization.

The invention provides an underground heat supply system based on an air energy heat pump as a heat source and a remote monitoring method, and the system comprises a heat source dynamic tuning subsystem which carries out the dynamic parameter optimization processing of environment temperature and energy storage state data, and obtains an air energy heat pump operation instruction; first characteristic adjustment of air energy heat pump output is formed through an air energy heat pump operation instruction, and matching of the temperature of an energy storage water tank and an environment heat source is achieved. The underground hot air accurate adjusting subsystem obtains underground real-time temperature data, the underground real-time temperature data is subjected to spatial thermal field calculation processing to obtain air volume demand parameters, and dynamic balance between the air supply intensity and the underground thermal environment is formed; and the multi-stage cooperative control center subsystem performs three-stage logic verification processing on the signals of the air energy heat pump operation instruction and the fan frequency instruction to obtain an equipment regulation and control instruction set. The underground intelligent heat supply system of the air energy heat pump, which has the environment self-adaption capability, the dynamic balance capability of a thermal field and the remote monitoring characteristic, is constructed.

The embodiment of the invention discloses a mine gas regulation and control method and device based on multi-modal data and a medium, and relates to the technical field of gas regulation and control, and the method comprises the steps that multi-source real-time sensing data, roadway point cloud data and CFD airflow simulation grid data in a target mine roadway are obtained, space-time alignment is carried out to determine a real-time roadway data cube, and the real-time roadway data cube is obtained; determining gas concentration field distribution and causal contribution popularity data in a preset future time window through a multi-mode depth causal model and the real-time roadway data cube; generating a risk field gradient feature vector based on gas concentration field distribution and causal contribution popularity data, and matching a decision path according to the risk field gradient feature vector; and when the decision path is a causal decision path, a fan / air door adjusting target point is determined, the fan / air door adjusting target point is simulated to determine a dynamic safety constraint boundary, a preset optimization objective function is solved to generate a fan rotating speed adjusting instruction and an air door opening degree control instruction, and fan / air door control is achieved.

A coal and gas outburst monitoring device includes the insertion and anchoring assembly, and the pump drainage and monitoring mechanism; the insertion and anchoring assembly is vertically inserted and distributed on the sidewall of surrounding rock of coal mine roadway, and the insertion and anchoring assembly can monitor the stress change data in the sidewall of surrounding rock in real time; the pump drainage and monitoring mechanism is erected within the coal mine roadway, and the pump drainage and monitoring mechanism can cooperate with the insertion and anchoring assembly to perform the gas pump drainage monitoring for the sidewall of surrounding rock of goaf, and to obtain the gas seepage monitoring data in the surface layer and the inner layer of sidewall of surrounding rock. Thus, comparing with the database mechanism, the accurate and advanced predictions for the gas outburst can be made.

The invention discloses an integrated dedusting-cooling system and method for a high-temperature mining working face of a mine. The integrated dedusting-cooling system comprises a sensor monitoring device, a fuzzy PID control device and a dedusting-cooling device, after the compressed air injection unit of the dust removal and cooling device sucks high-temperature dust-containing airflow in the environment into the system, primary dust removal is performed in the humidification and growth unit firstly, then cold fog cooling and secondary dust removal are performed in the cold fog dust removal unit, and finally airflow purification and tertiary dust removal are performed in the dust filtration and fog dissipation unit. In addition, the sensor monitoring device is adopted to collect environmental monitoring data in real time and feed back the environmental monitoring data to the fuzzy PID control device for processing, when any monitoring data deviates from the environmental parameters set by the system, the working condition of the dust removal and cooling device can be adaptively regulated and controlled, and then continuous dust removal and cooling are conducted on the high-temperature mining working face under different environmental parameters. And efficient cooperative treatment of dust and heat damage on the high-temperature mining working face of the mine is realized. The device has the advantages of being small in dust escape amount, high in dust removal-cooling efficiency and low in energy consumption.

The invention relates to an intelligent ventilation system in a tunnel and a control method thereof, and belongs to the technical field of tunnel ventilation. The intelligent ventilation system in the tunnel comprises a data acquisition unit, a ventilation unit, a control unit, a data storage unit and a data analysis unit, wherein the data acquisition units are mounted in detection sections in a tunnel, and each data acquisition unit comprises a COVI detector, a wind speed and direction detector and a traffic flow detection module; when the CO concentration and the VI exceed threshold values, the ventilation unit is controlled to enter a corresponding working mode; the data analysis unit is used for generating an early warning model according to the data of the data storage unit, and the early warning model is used for obtaining CO concentration and VI data in the future # imgabs0 # time according to the wind speed and wind direction data, the traffic flow, the vehicle type, the fuel oil type data, the CO concentration and the VI change. According to the ventilation system, intervention can be conducted before the pollution concentration is increased, the period of insufficient ventilation is effectively avoided, and it is guaranteed that good air quality is always kept in the tunnel.

The invention relates to the technical field of mine intelligent ventilation and poison filtration, and discloses a mine intelligent ventilation and poison filtration dynamic regulation and control method and system.The mine intelligent ventilation and poison filtration dynamic regulation and control method comprises the steps that a neural physical hybrid model is constructed, physical constraint conditions are combined with a deep neural network, and mine airflow field distribution is predicted; decomposing the neural physical hybrid model into three hierarchical sub-models, and deploying the three hierarchical sub-models to corresponding computing nodes to realize a hierarchical computing architecture; establishing a multi-level cooperation mechanism based on federal learning, and realizing distributed model training and optimization; constructing a task allocation decision model, and dynamically determining an optimal execution hierarchy of an airflow field calculation task according to task characteristics, resource states and real-time requirements; dynamically adjusting the precision and performance balance of airflow field calculation; according to the method, the key technical problems in the mine ventilation and poison filtration system are solved through the neural physical hybrid model, the multi-level distributed computing architecture and the federal learning collaboration mechanism.

The invention discloses a tunnel fire non-equilibrium control-smoke exhaust automatic adjustment control system and method, and belongs to the field of frequency conversion fan technology and tunnel fire control-smoke exhaust ventilation. The system comprises a data acquisition module, a data transmission module, a data processing and control algorithm module, a fan driving module and an emergency disposal module. The system dynamically and automatically controls the operation state of the smoke exhaust fan according to real-time fire smoke in the tunnel, and the exhaust air rate is reasonably adjusted. The abnormal environment parameters of the tunnel ceiling are collected through the sensing equipment, so that the approximate position of a fire in the tunnel and the real-time dynamic state of fire smoke spreading are obtained. And parameters such as the smoke front spreading speed and the smoke exhaust efficiency of the fan at the smoke exhaust port are obtained by applying an algorithm program to automatically control the start, stop and operation frequency of the fan. The interlocking arrangement of the emergency disposal module ensures that the other combinations are started under the condition that the exhaust air rate of one set of smoke exhaust port-smoke exhaust fan combination of the system is insufficient, fire smoke spreading is effectively controlled, and it is generally ensured that smoke is efficiently exhausted while the fire smoke is controlled within a safe range by the system.

The invention discloses an intelligent real-time monitoring regulation and control system for coal mine ventilation, and relates to the technical field of coal mine ventilation, through a ventilation duct layout analysis module, the system can construct pressure loss of each branch in a coal mine ventilation duct, and further analyze the relevance between the pressure loss and ventilation data information of a corresponding area; the analysis provides detailed air flow distribution and ventilation duct pressure loss data, accurate decisions can be made on layout optimization, pressure regulation and air flow distribution of the mine ventilation duct, and stability of air flow and balance of pressure in the mine are ensured. And dynamic prediction and evaluation of a mine stability index: the system fits and outputs the mine stability index through a mine performance analysis module in combination with the trained ventilation stability prediction model, and compares the mine stability index with a set stability threshold value to evaluate the stability of the mine in real time. When the mine ventilation system faces an unstable risk, the system can give out early warning in time.

The present invention provides an automated control system and method for a mine ventilation system. The system comprises a precision sensor for key tunnel ventilation parameters, an automatic analysis and adjustment system for mine ventilation conditions, and a control feedback system for mine ventilation structures. The precision sensor for key tunnel ventilation parameters is used for real-time acquisition of key tunnel ventilation parameters and structure ventilation parameters of the mine ventilation system; a network solution simulation module is used for performing network solution on a three-dimensional dynamic visualization model to obtain the solved ventilation parameters; a scheme optimization decision module is used for determining an initial control scheme based on key tunnel ventilation parameters, structure ventilation parameters, and connection tunnel ventilation parameters; and based on the optimized three-dimensional dynamic visualization model, the initial control scheme is optimized to obtain a control decision scheme; and a mine ventilation structure control feedback system is used for receiving the control decision scheme and controlling ventilation equipment to perform ventilation adjustment.