356 results about "Ventilation control" patented technology

The invention provides a mobile henhouse ventilation regulation and control method and system based on an environment model, and relates to the technical field of intelligent breeding, and the method comprises the steps: obtaining original temperature data, original humidity data, a three-dimensional space wind speed component, an opening geometric distribution data set, and original latitude and longitude coordinate data and time data; calculating a dynamic environment weight coefficient matrix according to the original latitude and longitude coordinate sequence and the time data; generating a self-adaptive heat exchange flow field according to the dynamic environment weight coefficient matrix, the original temperature data and the original humidity data; according to the self-adaptive heat exchange flow field and the trepanning geometric distribution data set, a ventilation compensation amount demand curve is obtained through calculation; generating a ventilation intensity adjusting instruction set according to the ventilation compensation amount demand curve; and according to the ventilation intensity adjusting instruction set, outputting an optimal ventilation control parameter. According to the method, ventilation response self-adaptive accurate matching, airflow dead zone self-suppression and energy consumption-effect dynamic balance under the moving sudden change working condition are achieved.

The invention discloses an energy-saving control method based on a building group spatial form, which relates to the technical field of energy-saving control, and comprises the following steps: constructing an airflow track analysis region based on a region with hot pressure difference direction change in a spatial pressure covering sensing matrix, and collecting continuous wind direction and wind speed data; judging whether the airflow direction is abnormal or not according to the change of the flow direction consistency entropy; performing spatial coincidence processing on the spatial pressure shielding sensing matrix and the airflow direction abnormal region, and generating an air outlet ventilation and heat extraction efficiency evaluation index based on the heat conduction rate in the coincidence region and the stability of an airflow output path; and on the basis of the ventilation and heat removal efficiency evaluation index of the exhaust outlet, an exhaust response condition matrix containing a space pressure shielding parameter, an airflow disturbance level and a heat retention level is constructed, and a ventilation control judgment sequence is generated. According to the method, the problem of air exhaust failure under pressure shielding interference is solved, ventilation efficiency accurate judgment and energy-saving regulation and control optimization are achieved, and the ventilation stability and the energy utilization efficiency of the building group are guaranteed.

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 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 relates to the technical field of medical care informatics, and discloses a laryngeal mask ventilation control method suitable for outpatient anesthesia, which comprises the following steps: before core analysis, injecting and monitoring a high-frequency signal to confirm the integrity of an original breathing waveform data stream; constructing a real-time ventilation waveform trajectory in a differential phase space only on the premise that a data stream is complete, and performing morphological comparison with an individualized baseline template; meanwhile, when a parameter adjustment event of the respirator is monitored, the baseline template is automatically re-calibrated, a collaborative analysis framework with front information source quality inspection and dynamic reference self-adaption capabilities is constructed, ventilation monitoring is converted from passive response to an isolated peak point into active insight to a system dynamics evolution trajectory, and the system dynamics evolution trajectory is optimized. Therefore, the risk of gradual deterioration of the ventilation state caused by tiny air leakage of the laryngeal mask or secretion accumulation can be clinically recognized in an early stage, and intervention time is won for anesthetists.

The invention discloses an outdoor workstation air quality monitoring and intelligent ventilation system and method, and belongs to the technical field of environment monitoring and intelligent ventilation control. The system is composed of an environment sensing module, an intelligent control unit and a ventilation execution device. And the environment sensing module realizes pollutant concentration field reconstruction through a multi-dimensional data fusion algorithm. The intelligent control unit constructs a dynamic ventilation model based on an improved fuzzy PID algorithm, and generates an optimal ventilation strategy in combination with meteorological prediction data and workstation structure parameters. And the ventilation execution device adopts a modular design to realize directional air supply and pollutant blocking. The method comprises four steps of real-time environment data acquisition, dynamic risk assessment, ventilation parameter optimization and execution mechanism linkage control, and remote intelligent regulation and control are realized through cooperation of edge computing and a cloud platform. According to the scheme, a passive response mode of a traditional ventilation system is broken through, and the technical advantages of accurate pollutant tracing, dynamic optimization of ventilation efficiency and intelligent adjustment of equipment energy consumption are achieved.

The invention relates to a tunnel ventilation system parameter optimization method based on neural network model driving, and the method comprises the steps: dividing a tunnel into a plurality of irregular grid nodes according to the three-dimensional geometrical characteristics, aerodynamic characteristics and pollutant distribution characteristics of the tunnel; constructing a nonlinear edge weight calculation function according to the spatial distribution data of the plurality of irregular grid nodes in combination with a pollutant diffusion coefficient, a real-time wind speed field and a spatial position relationship among the grid nodes, and generating an edge weight matrix representing interaction strength among the grid nodes; inputting the grid node information of the plurality of irregular grid nodes and the edge weight matrix into a space-time diagram neural network model to obtain multivariable space-time dynamic characteristics of the pollutants; according to the multivariable space-time dynamic characteristics, pollutant concentration overrun probabilities of the irregular grid nodes are determined; and according to the pollutant concentration overrun probability of the irregular grid nodes, ventilation regulation and control parameters of the tunnel ventilation system are optimized. The design of ventilation system parameters can be optimized.

The invention relates to a high-speed rail station building ventilation control method and system based on a physical information neural network, and the method specifically comprises the following steps: collecting related parameters of a high-speed rail station building, and carrying out the preprocessing; based on an electric field intensity theory, constructing a passenger space-time distribution function according to the preprocessed data to calculate dynamic heat source intensity; constructing a PINN model of 10 layers of MLP, and constructing a loss function according to physical constraints to train the PINN model; according to output of the PINN model, a control target is deduced in combination with ventilation parameters, and then ventilation of the high-speed rail station building is controlled; and comparing a derivation result with an actual condition, if the deviation is too large, performing fine adjustment on the PINN model, and correcting the output derivation result until the deviation is within a specified range. According to the method, related data are collected and converted into dynamic heat source items which can be identified by the PINN model, and the model is trained through physical constraints, so that the accuracy of a derivation result can be improved, and the ventilation control precision and the energy-saving effect of the high-speed rail station building are improved.

The invention discloses a green energy-saving curtain wall and a construction transformation method thereof, and relates to the technical field of building curtain walls, the green energy-saving curtain wall comprises a glass frame, two ventilation box bodies and a photovoltaic frame, the two ventilation box bodies are installed at the upper end and the lower end of the glass frame respectively, and the photovoltaic frame is fixedly installed on the side wall of the glass frame; a clamping and fixing structure is installed in the glass frame, ventilation control structures are installed in the two ventilation box bodies, connecting structures are installed on the outer sides of the two ventilation box bodies, and an extending control structure is installed on one side of the photovoltaic frame. According to the green energy-saving curtain wall, through multi-structure innovative cooperation and multi-structure collaborative design, functionality, installation efficiency and energy utilization efficiency are optimized, thin film photovoltaic glass and an adjustable photovoltaic panel are adopted for collaborative power generation, the thin film photovoltaic glass is embedded in a curtain wall body, and the angle-adjustable photovoltaic panel extending out of a frame is combined, so that the curtain wall is more energy-saving and environment-friendly. And a dual power generation structure is formed.

The invention relates to the technical field of ventilation control, in particular to a multi-parameter real-time monitoring system of an indoor large ventilation system. The system uses a monitoring data acquisition module to acquire basic monitoring data. Kriging interpolation is carried out by using a spherical semi-variation function according to the collected temperature data to obtain an optimal unbiased estimated value under each coordinate, and an upflow tendency diagram is formed. And segmenting the real-time upflow tendency diagram to determine a plurality of connected domains, evaluating a pollution plume mode index of the current indoor environment by comparing particle concentration data and heat energy data, and further determining a control strategy mode. In each control strategy mode, regulation and control parameters can be determined according to the area of a connected domain or a pixel value in a real-time upflow tendency map. According to the embodiment of the invention, the real-time upflow tendency diagram is constructed through data monitoring and feature analysis, and indoor dynamic, low-disturbance and low-delay ventilation control of a large commercial room is realized.

The invention relates to the field of ventilation control, in particular to an intelligent ventilation control method and system based on an intelligent laboratory, and the method comprises the steps: obtaining a to-be-controlled air volume sequence and a multi-dimensional to-be-controlled turbulence characteristic sequence of any region in a preset sampling period, and calculating a turbulence compensation coefficient of a target dimension, the turbulence contribution degree of any region in the target dimension is calculated; calculating a comprehensive product, calculating a first difference value between the air volume at the marked moment and the comprehensive product, and taking a mean value of the first difference values of all dimensions as an air volume correction value of any region at the marked moment; and taking a result of weighted summation of the air volume correction values of all the areas as comprehensive air volume, and inputting the comprehensive air volume into a laboratory PID controller to complete ventilation control. According to the technical scheme, the precision and timeliness of the ventilation control result can be improved.

The invention belongs to the technical field of tunnel construction, and particularly relates to a tunnel construction ventilation intelligent regulation and control method based on electrical automation. Distributed sensor arrays are deployed on a tunnel driving working face, a haulage roadway and a fan station through a multi-source heterogeneous sensor network, ventilation loads, environmental parameters, equipment states and construction event signals are collected in real time, and real-time and accurate original data support is provided for the system; a three-dimensional fluid mechanics-particulate matter diffusion coupling simulation model of a tunnel ventilation system is constructed, then a digital twin is used as a virtual training environment, an optimization instruction is converted into an electrical control signal, and a closed-loop PID-fuzzy coincidence controller dynamically compensates execution delay, controls operation of a fan and an air valve, and finally performs dynamic simulation on the tunnel ventilation system. And an execution result is fed back to the digital twin body for model calibration, so that finer and more efficient ventilation control is realized, the use problem in a high-altitude and alpine region environment is solved, the continuous effectiveness of ventilation regulation and control is effectively guaranteed, and the overall performance is improved.

The invention provides a clean room pollutant concentration control method, equipment, a medium and a product, and relates to the technical field of clean room ventilation control. The method comprises the following steps: acquiring the real-time gaseous molecular pollutant AMC concentration of each region in a clean room according to the space region division result of the clean room; when the real-time AMC concentration of the target area is larger than or equal to a concentration threshold value, the target area serves as the center, and the wind speed correction value of the FFU of each area is adjusted according to the distance between the other areas and the target area; wherein the closer the distance to the target area is, the larger the corresponding wind speed correction value is; when the AMC concentration of the target area is smaller than a concentration threshold value, the current AMC concentration value of each area is obtained, and an FFU wind speed optimal solution is determined according to the current AMC concentration value of each area, clean room FFU layout information and a particle swarm optimization algorithm PSO; and adjusting the wind speed of each FFU according to the optimal solution of the wind speed of the FFU. According to the invention, global monitoring, dynamic optimization and accurate regulation and control of pollution concentration can be realized.

The invention relates to a reinforcement learning-based granary ventilation energy consumption optimization system and method, in particular to the field of granary ventilation energy consumption optimization, and can effectively improve the intelligent level of granary ventilation control by setting a data acquisition and fusion module, a state space construction module, a reinforcement learning training module and a real-time decision and feedback module. Accurate perception and decision-making of a dynamic environment are realized through cooperative work of multiple modules, the system adaptively optimizes a ventilation strategy by using a reinforcement learning technology, energy consumption is remarkably reduced, meanwhile, it is ensured that the temperature and humidity in a granary are stabilized in a safe range, the grain mildew or qualitative change risk is avoided, and the system has high practicability. The online learning ability of the method can continuously adapt to external weather changes and grain condition dynamic states, closed-loop optimization is formed, and finally energy consumption minimization is achieved on the premise that grain storage safety is guaranteed.

The invention discloses a linkage system of a roadway air distribution device and a dust removal device and a control method, and belongs to the technical field of safety and environmental protection of mine / tunnel construction. The system comprises a long-pressure air control system, a short air draft dust collection system and an intelligent control module, the long-pressure air control system forms an airflow air wall through a long-distance air distribution device to restrain dust diffusion, the short-air-draft dust collection system captures dust through a short-distance dust collection cover, and the intelligent control module dynamically adjusts operation parameters of the long-pressure air control system and the short-air-draft dust collection system based on parameters such as dust concentration and air speed. The control method comprises the stages of dust suppression, capture, weak wind area removal and intelligent adjustment, and efficient dust removal is achieved through airflow collaborative optimization and a self-adaptive control algorithm. The dust collecting rate can be increased by 50% or above, energy is comprehensively saved by 20% or above, potential safety hazards in weak wind areas are eliminated, and the device is suitable for dust-producing scenes such as driving working faces and belt conveying roadways and has the advantages of being efficient, safe, capable of saving energy and wide in applicability.

The invention belongs to the technical field of building ventilation, and particularly discloses an intelligent building ventilation energy-saving system based on AI dynamic adjustment, and the system is characterized in that the system comprises a sensing layer which is used for collecting indoor and outdoor environment parameters in real time; the data transmission layer transmits various data acquired by the sensing layer to a central control system in real time through an Internet of Things communication technology, and is provided with a data caching mechanism; the central control system comprises a data processing module and is used for preprocessing the received data; the AI analysis module is used for establishing an indoor air quality prediction model, a personnel activity mode prediction model and a ventilation system energy consumption model by applying a machine learning algorithm; the control decision module generates an optimal ventilation control strategy; and the execution layer comprises a fresh air fan and an exhaust fan which adopt a frequency conversion technology, and an air supply outlet and an exhaust outlet which are provided with electric air valves, and further comprises a function of receiving a control instruction of the central control system and controlling ventilation equipment in real time.

The invention provides a control method and device for a fresh air system of a clean room, a medium and a computer program, and relates to the technical field of clean room ventilation control. The method comprises the steps that a system collects air quality data of different detection points of a clean room in real time, and an original data sequence is generated; key feature data is extracted from the original data sequence, and dimensionality reduction is performed on the key feature data by using PCA to form a dimensionality reduction feature matrix; respectively inputting the dimension reduction feature matrix into ARIMA and LSTM to obtain prediction results, and performing weighted fusion to obtain a fusion prediction result of the air quality; and based on the fusion prediction result and the detection point position, marking a potential pollution source position, obtaining a diffusion path simulation result according to the diffusion model, and based on the fusion prediction result, the potential pollution source position and the diffusion path simulation result, generating a real-time dynamic control strategy to control the operation state of the fresh air system. Efficient and energy-saving operation can be achieved while it is ensured that the air quality reaches the standard.

The invention discloses a method and system for adjusting the self-adaptive ventilation air volume of a factory building, and the method comprises the steps: carrying out the optimization of a quantization factor and a scaling factor of a ventilation PID controller through a parameter optimization algorithm, obtaining an optimal quantization factor and an optimal scaling factor, and carrying out the feedback adjustment of a ventilator based on the optimal quantization factor and the optimal scaling factor; therefore, compared with the traditional technology, the selection of the PID control parameters does not depend on artificial experience, the most reasonable control parameters can be optimized by utilizing an algorithm, and on this basis, the PID control precision can be improved, so that the adaptive adjustment of the air volume in each working area in the underground powerhouse can be more accurately realized, and the control precision of the underground powerhouse can be improved. And therefore, the dust removal effect on each working area in the plant is ensured.

The present invention discloses a green energy-saving curtain wall and a construction and renovation method thereof. The present invention relates to the field of building curtain wall technology, comprising a glass frame, two ventilation boxes and a photovoltaic frame, the two ventilation boxes being respectively installed at the upper end and the lower end of the glass frame, the photovoltaic frame being fixedly installed at the side wall of the glass frame, a clamping and fixing structure being installed inside the glass frame, a ventilation control structure being installed inside the two ventilation boxes, a connecting structure being installed outside the two ventilation boxes, and an extension control structure being installed on one side of the photovoltaic frame; the present invention provides a green energy-saving curtain wall, which optimizes functionality, installation efficiency and energy utilization efficiency through multi-structure innovation collaboration and multi-structure collaborative design, adopts thin-film photovoltaic glass and adjustable photovoltaic panels for collaborative power generation, the curtain wall main body is embedded with thin-film photovoltaic glass, and combined with the angle-adjustable photovoltaic panels in the extension frame, a dual power generation structure is formed.

The invention discloses a coal mine underground environment intelligent sensing and dynamic ventilation linkage control system and method, and is applied to the technical field of coal mine ventilation. The system comprises an environment intelligent sensing module used for collecting environment data of an underground coal mine; the data transmission module is used for realizing data transmission among different modules; the underground data processing module is used for processing and analyzing the environmental data, and performing real-time ventilation early warning and real-time ventilation equipment regulation and control based on the environmental data; the ground linkage control module is used for predicting environment data of a future time node and setting a preset scheduling scheme of ventilation equipment in combination with a ventilation network model simulation result and an underground operation plan; and the dynamic ventilation regulation module is used for regulating the ventilation condition of the underground coal mine based on the preset scheduling scheme and the real-time regulation and control scheme. According to the method, prediction is carried out by collecting the environment data of the underground coal mine, the scheduling scheme is generated in advance according to the operation plan, and the hysteresis problem of a real-time ventilation regulation and control scheme is avoided.

The invention discloses a new energy automobile charging pile high-low voltage power distribution cabinet and a ventilation control method thereof. The new energy automobile charging pile high-low voltage power distribution cabinet comprises a cabinet body and electrical elements installed in the cabinet body. A left air chamber and a right air chamber are respectively mounted on the left side and the right side of the cabinet body; the left air chamber and the right air chamber are the same in structure, and the internal structure of the left air chamber and the internal structure of the right air chamber are symmetrically distributed on the two sides of the cabinet body. Each of the left air chamber and the right air chamber comprises a shell, a fan partition plate, a drying filter plate and a water curtain; a ventilation opening opposite to the cabinet body is formed in the side wall of the shell, the fan partition plate, the drying filter plate and the water curtain are sequentially and transversely installed in the shell from inside to outside, and a water storage pool right opposite to the water curtain is arranged below the shell. Air is evaporated and cooled through the water curtain and then is subjected to humidity reduction through the drying filter plate, so that the humidity of the air entering the cabinet body does not exceed a set humidity value, the problem that moisture affects electrical elements is solved, and water and electricity are mutually independent.

The invention relates to the technical field of medical equipment, in particular to an edge calculation respirator system and method for adaptive ventilation control, and the system comprises a respirator end which is provided with an edge calculation module and a local control model; the edge calculation module is used for collecting multi-modal physiological parameters of a patient and performing data preprocessing on the multi-modal physiological parameters of the patient to generate a multi-dimensional feature vector; the local control model carries out real-time self-adaptive adjustment on ventilation parameters of the breathing machine based on the multi-modal physiological parameters of the patient and the baseline characteristics of the patient; the cloud server is in communication connection with the respirator end and is configured with a global optimization model; and the cloud server receives historical ventilation data of the respirator end, and the global optimization model performs training based on the historical ventilation data to generate a personalized ventilation strategy, and issues the personalized ventilation strategy to the respirator end for correcting adjustment of the local control model. According to the invention, low latency and high reliability of bedside control are guaranteed through a side cloud collaborative architecture.

The invention relates to the technical field of ventilation control in a hydrogen fuel cell production process, in particular to a hydrogen leakage detection and ventilation control experimental device for a hydrogen fuel cell activation test process, which comprises a box body, a detection assembly is arranged in the box body, the detection assembly comprises a fixed frame, the fixed frame is fixedly connected to the inner wall of the box body, and the fixed frame is fixedly connected to the inner wall of the box body. And one side of the fixed frame is fixedly connected with an air inlet fan. According to the hydrogen leakage detection and ventilation control experimental device for the activation test process of the hydrogen fuel cell, an air inlet fan is started to blow air into the interior, an exhaust fan is started to extract air flow in the box body through an air collecting hood and exhaust the air flow into a groove, and then the air flow enters a ventilation groove through a communication groove; the hydrogen concentration sensor detects exhausted gas, the filter frame blocks metal chippings and dust in the gas, then the metal chippings and dust are exhausted through the air outlet, the gas in the box body is effectively circulated, hydrogen in the gas is detected through the hydrogen concentration sensor, the closing assembly is controlled in a linkage mode, and the safety of the device is improved. The detection efficiency of hydrogen leakage in the activation test is improved, the ventilation response time is shortened, and efficient and rapid safety linkage control is achieved.

The invention provides an underground coal mine ventilation control method and device, electronic equipment and a storage medium, and belongs to the technical field of mine ventilation. The method comprises the steps that the type and concentration characteristics of harmful gas in a target area are determined according to data collected by a biosensor array; determining time sequence data of the harmful gas according to the concentration of the harmful gas, and determining a target concentration change rate of the harmful gas according to the time sequence data; according to the concentration of the harmful gas, the target concentration change rate and the current underground acoustic wave characteristics of the coal mine, the target air volume of the target area is determined; according to the target air volume of the target area, the ventilation resistance of the target area and the current opening degree of the ventilation valve, the opening degree of the ventilation valve is controlled, and the ventilation air volume is determined. According to the coal mine underground ventilation control method and device, the electronic equipment and the storage medium, the ventilation quantity can be accurately and timely adjusted.

The invention discloses a tunnel intelligent ventilation control method and system based on the Internet of Things, electronic equipment and a storage medium, and the method comprises the steps: collecting environment parameters in a tunnel, and determining a difference distribution condition and a local ventilation demand of a local environment region in the tunnel; based on the difference distribution condition, dividing the tunnel space into a plurality of independent control units, and performing feature extraction on the environmental parameters of each independent control unit to obtain a ventilation demand priority; on the basis of the ventilation demand priority, a regulation and control rule base based on a fuzzy control algorithm is constructed, and an air volume distribution scheme of each independent control unit is determined in combination with the local ventilation demand; based on the air volume distribution scheme, the independent control units are controlled to conduct ventilation, airflow interaction information of the adjacent independent control units is collected, and an airflow dynamic balance adjustment scheme is generated based on the airflow interaction information; and dynamically correcting the air volume of each independent control unit based on the airflow dynamic balance adjustment scheme to complete tunnel ventilation control.

The invention relates to the technical field of coal mine ventilation control, and discloses a coal mine ventilation integrated control system based on intelligent scheduling. The system comprises an air door operation state monitoring module, a regional ventilation influence evaluation module and a global ventilation collaborative optimization module. The air door operation state monitoring module collects air door operation data such as air pressure, gas concentration, dust concentration, air speed and air door opening degree in real time through multi-source sensor arrays arranged on all air doors of a mine. The regional ventilation influence evaluation module performs abnormal influence quantitative evaluation on the independent ventilation region of the mine according to the real-time air door operation data to generate a regional influence identifier; and the global ventilation collaborative optimization module is combined with a mine topological structure, and performs global optimization calculation of a multi-air-door collaborative control strategy according to the regional influence identifier. The system achieves comprehensive perception, scientific evaluation and global cooperative control of the mine ventilation state, improves the operation efficiency of the ventilation system, guarantees the safety of underground operation of a coal mine, and is suitable for various coal mine ventilation scenes.

The invention discloses a tunnel intelligent ventilation control optimization method based on data fusion, and relates to the technical field of control optimization, and the method comprises the steps: collecting tunnel environment data of a plurality of sensing devices in a tunnel, carrying out the anti-noise sparse coding processing of the tunnel environment data, and obtaining a stable fusion environment sensing data set; loading the stable fusion environment perception data set into a preset fusion model pool for fusion reasoning and state calculation to obtain an environment state fusion data set; dynamically adjusting the weight distribution of each fusion model in the fusion model pool based on the environment state fusion data set, and obtaining an environment state evaluation result set; based on the sensing equipment operation feedback data, combining with the environment state evaluation result set, adjusting the weight and parameters of the fusion model through real-time control feedback, and generating a standardized control execution instruction set; through the synergistic effect, the ventilation control system continuously outputs an accurate environment state evaluation result and a standardized control instruction, and dynamic optimization regulation and control of ventilation parameters are realized.

The invention belongs to the technical field of mine ventilation management and control, and particularly relates to an intelligent mine ventilation management and control method and system, and the method comprises the following steps: S1, data perception and fusion: collecting multi-source heterogeneous data from a ventilation facility, an environment sensor and a personnel positioning system through a multi-protocol data gateway, and generating a standardized data flow; s2, constructing and updating a digital twinborn body: driving and constructing the digital twinborn body of the mine ventilation system based on the standardized data flow; s3, intelligent deduction and decision making; s4, strategy execution and closed-loop control are carried out; and S5, edge autonomy. The heterogeneous data is integrated through the multi-protocol data gateway, and the standardized data stream is generated, so that a unified and high-quality data basis is provided for subsequent analysis, and the problem of information islands is solved. And the digital twin is dynamically calibrated based on real-time and feedback data, so that the simulation precision is remarkably improved, and the underground ventilation condition can be reflected more truly.

The invention discloses a ventilation system for a broiler chicken hatching plant. A ventilation system for a broiler chicken hatching plant comprises a ventilation control box, a ventilation shield is installed above the ventilation control box, a waterproof partition plate is fixed to the periphery of the ventilation control box, a box body is arranged in the ventilation control box, a driving controller box is installed on the outer wall of the box body, a driving gear is installed on the driving controller box, and an unpowered ventilator is installed in the box body. A plurality of groups of side supporting tables are arranged on the outer wall of the box body, and anti-deviation guide blocks are mounted on the plurality of groups of side supporting tables. According to the unpowered ventilator, the real-time wind direction is detected through the wind direction detector, when the wind direction is in the same direction as the arc-shaped protective cover, a driver in the driving controller box triggers and drives the rotating disc to rotate, so that reversing of the arc-shaped protective cover is achieved, the unpowered ventilator after reversing is not affected by wind bodies in the same direction, and the unpowered ventilator is safe and reliable. The situation that a wind body with sand and dust directly faces the unpowered ventilator, heat in the pipeline is retained, the temperature in the pipeline rises is avoided, and then the pumping and discharging efficiency of the ventilator is ensured.

The invention discloses an intelligent ventilation method for a high-gas tunnel, and relates to the technical field of tunnel construction ventilation, and the method comprises the steps: dividing the tunnel into ventilation control sub-sections with fixed lengths in the direction of a main shaft, recording the structured ventilation information of each ventilation control sub-section, and constructing a ventilation path map; ventilation state parameters of all the ventilation control sub-sections are collected, and ventilation risk factors of all the ventilation control sub-sections are calculated; calculating a target air supply amount based on the ventilation risk factor, selecting an air supply path according to the ventilation path map, and controlling a main fan and a jet fan to jointly operate; when abnormal conditions are detected in the sub-sections, a linkage ventilation protection mechanism is automatically triggered, a standby air source is started, and forced exhaust is executed; and periodically evaluating the ventilation efficiency of each ventilation control sub-section, and dynamically adjusting the weight parameter of the ventilation risk factor and the priority of the air supply path according to the ventilation efficiency.