Double-induction controlled wind dust reduction linkage control method based on dust monitoring at fully-mechanized excavation face of coal mine

Abstract

The application discloses a double-injection control wind dust reduction linkage control method based on dust monitoring of a fully-mechanized excavation face of a coal mine, relates to the technical field of coal mine ventilation and dust removal control, and comprises the following steps: S1, constructing a dynamic mapping model of a wind flow disturbance area and a dust high-incidence area based on the spatial layout of the fully-mechanized excavation face and a dust diffusion trend, extracting a settling inertia threshold required for water mist particle settling under different wind speed conditions, and setting initial parameters of water mist particle size and spraying strategy.The application constructs dynamic mapping of the wind flow disturbance area and the dust high-incidence area, scientifically sets water mist particle size and spraying strategy, cooperates with multi-stage adjustable spraying and gradient fog field, and improves water mist retention and dust covering effect.Combining with wind and fog flow guiding and slow-release flow area, dust space is stabilized, and water mist deviation and dust re-diffusion are prevented.Relying on a three-field linkage model and a parameter self-correction algorithm, dynamic optimization of spraying and injection is realized, dust removal system is ensured to be always optimal, and dust removal efficiency and environmental safety are improved.

Description

Technical Field

[0001] This invention relates to the field of coal mine ventilation and dust control technology, specifically to a dual-jet ventilation and dust suppression linkage control method based on dust monitoring in coal mine tunneling faces. Background Technology

[0002] The dual-ejector dust suppression and ventilation linkage control system based on dust monitoring in coal mine tunneling faces refers to the deployment of online dust monitoring devices in the tunneling area of ​​a coal mine to sense the dynamic changes in dust concentration in the air at the working face in real time. Based on the monitoring results, the system intelligently adjusts the working status of the dual-ejector devices to achieve directional airflow injection and airflow pressurization, thereby precisely controlling the airflow distribution and velocity at the working face. Simultaneously, combined with a spray dust suppression system, based on early warnings of excessive dust concentration, the system dynamically activates or adjusts the spray intensity and airflow injection rate to synergistically improve dust dilution and settling efficiency. This method, through a closed-loop linkage of "monitoring-wind control-dust suppression," not only effectively reduces dust concentration at the working face, improves the working environment, and enhances the intelligence level of ventilation and dust removal, but also reduces energy consumption and human intervention, achieving dynamic and precise control of dust management at coal mine tunneling faces.

[0003] The existing technology has the following shortcomings: In existing technologies, spray dust suppression and jet ventilation are often combined for dust control at coal mine tunneling faces. However, in actual joint control processes, there is a problem of incoordination between the spray and jet flow field mechanisms. Especially under strong jet airflow conditions, the water mist particles released by the spray system are small in size and are abnormally entrained and pulled by the high-speed airflow, resulting in the water mist failing to form sufficient dispersion and coverage in the dust source area. The dust-suppressing water mist is prematurely carried away from the dust source area. During this process, the water mist and dust at the working face form uneven mixing under the action of the jet airflow. This mixture is prone to abnormal accumulation in areas such as tunneling heads and roadway bends where the airflow is turbulent, velocity is attenuated, or there is local backflow, forming high-humidity, viscous dust clouds. These clouds not only reduce dust settling efficiency but also, due to the adhesion and deposition of water-containing dust, easily cause mud accumulation on equipment surfaces, blockage of ventilation ducts or spray devices, and even short circuits and corrosion hazards around high-temperature or electrical equipment. In addition, the continuous accumulation of local dust clouds may also mask the monitoring results of the true dust concentration, triggering secondary disasters such as dust explosions and high incidence of pneumoconiosis, seriously threatening the safety of the working environment and the health of personnel.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a dual-ejector dust suppression linkage control method based on dust monitoring in coal mine tunneling faces. This method involves constructing a dynamic mapping between airflow disturbance zones and high-dust-occurrence areas, scientifically setting water mist particle size and spraying strategies, and combining multi-level adjustable spraying and gradient fog fields to improve water mist retention and dust coverage. By combining wind-mist guiding and slow-release flow zones, the dust suppression space is stabilized, preventing water mist deviation and dust re-diffusion. Relying on a three-field linkage model and parameter self-correction algorithm, dynamic optimization of spraying and ejection is achieved, ensuring the dust suppression system remains optimal, improving dust suppression efficiency and environmental safety, thereby solving the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a dual-ejector dust suppression linkage control method based on dust monitoring for coal mine fully mechanized tunneling faces, comprising the following steps: S1. Based on the spatial layout of the tunneling face and the dust diffusion trend, a dynamic mapping model of the airflow disturbance zone and the dust high-incidence zone is constructed. The settling inertia threshold required for water mist particle settling under different wind speed conditions is extracted, and the initial parameters of water mist particle size and spray strategy are set. S2, based on the settling inertia threshold, adjust the atomization structure and mist output parameters of the spray device to achieve multi-level adjustable water mist particle size, and configure differentiated spray devices at the airflow disturbance boundary to form a gradient fog field and improve the directional retention performance of water mist; S3, based on gradient fog field, sets up wind and fog guiding structure unit, and forms slow release flow zone in dust source area through weak wind control mechanism, enhances the suspension coverage time of water mist particles, and stabilizes the spatial distribution of dust. S4. Deploy micro-environmental detection units in the slow-release flow zone to collect dust concentration, wind speed vector and water mist density data, establish a three-field linkage model of wind flow field, water mist field and dust field, and evaluate the local adaptability and disturbance suppression effect of the dust suppression system. S5, based on the response index of the three-field linkage model, dynamically adjusts the spray volume and the ejector wind speed of the dual ejector device to maintain the coordinated change of water mist particle size and airflow energy, forming a coupled response mechanism of wind control and dust suppression, so as to achieve precise water mist coverage, stable airflow guidance and minimize dust disturbance. S6, based on the coupled response mechanism of wind control and dust suppression, combined with periodically collected multi-source monitoring data, applies a parameter self-correction algorithm to continuously optimize water mist particle size, spray device layout and ejection intensity, and establishes a full-cycle intelligent control and strategy iteration mechanism to dynamically maintain the optimal level of dust reduction efficiency and working environment safety.

[0007] Preferably, step S1 includes: Based on the three-dimensional spatial model of the tunneling face, computational fluid dynamics simulation method is used to simulate the airflow field and dust diffusion path under different tunneling stages, ventilation configurations and wind speeds, and to identify airflow disturbance zones and dust high-incidence zones. The Lagrange particle tracking method was used to calculate the motion trajectory and sedimentation process of water mist particles of different sizes in the wind-induced disturbance zone, and the minimum sedimentation inertia threshold required for the sedimentation of water mist particles was extracted. Based on the settling inertia threshold, the water mist particle size, spray pressure, nozzle orifice diameter, spray angle, and spray speed are set to form a spray strategy initialization parameter set; The water mist particle size and spray strategy initialization parameters are integrated into the dust suppression control command system, and the spray parameters are dynamically adjusted based on real-time monitoring signals.

[0008] Preferably, step S2 includes: Based on the settling inertia threshold required for water mist particles to settle in the dust source area, the water mist particle size distribution range is determined and multi-level particle size ranges are divided. By adjusting the nozzle diameter, number of nozzles, spray angle, and the multi-stage compression structure of the internal atomization chamber of the spray device, multi-stage adjustable control of water mist particle size can be achieved. Differentiated spray devices are configured at the wind disturbance boundary based on wind speed and dust characteristics to form a spatially continuous gradient fog field; Based on real-time monitoring of wind speed, wind pressure, and dust concentration data, the spray pressure, spray flow rate, and spray angle are dynamically adjusted to achieve directional retention of water mist in different airflow energy zones.

[0009] Preferably, step S3 includes: A wind and mist guiding structure unit consisting of multi-plate guide vanes, annular diverter tubes and lateral flow restrictors is set up in front of and on both sides of the dust source to form a buffer zone where the airflow energy is controlled to be below 3 meters per second. Within the buffer zone, a miniature low-speed air supply device is used to control the air outlet speed to 0.5 to 1.5 meters per second, creating a local wind direction disturbance that is opposite to or perpendicular to the main airflow, thus establishing a slow-release flow zone. Directional spraying devices with a particle size of 20 to 30 micrometers are arranged above and to the side of the dust source area to form a three-dimensional dust-falling mist layer covering the dust source. Based on real-time monitoring of dust concentration, wind speed and water mist density, the air supply rate and spray flow rate are dynamically adjusted to achieve continuous and stable optimization of the slow-release flow zone.

[0010] Preferably, step S4 includes: Miniature environmental detection units integrating high-precision laser dust concentration sensors, three-dimensional ultrasonic wind speed sensors, and light scattering water mist density sensors are deployed in the upstream, middle, and downstream areas of the slow-release flow zone. Dynamic data of dust concentration, wind speed vector and water mist density were collected. Based on mathematical modeling and numerical analysis, a three-field linkage model of wind flow field, water mist field and dust field was established. Based on the three-field linkage model and combined with real-time data feedback, the local adaptability of the dust suppression system and its effect on suppressing airflow disturbance are evaluated, and intervention signals are output. Based on long-term monitoring data, the parameters and structure of the three-field linkage model are periodically adaptively corrected and upgraded.

[0011] Preferably, step S5 includes: Based on the response index output by the three-field linkage model of airflow field, water mist field and dust field, the spray volume and spray pressure are dynamically adjusted to generate water mist particle size that matches the airflow intensity. Based on the real-time changes in the airflow field, the ejector velocity, inlet airflow, and throttling ratio of the ejector channel of the dual ejector device are adjusted synchronously to control the airflow guiding capability. The adjustment parameters of spray volume and ejector wind speed, along with dust changes and airflow conditions, are fed back to the three-field linkage model to continuously optimize the model's prediction and control accuracy, thereby realizing a coupled response mechanism for wind control and dust suppression.

[0012] Preferably, step S6 includes: Based on periodically collected multi-source monitoring data such as dust concentration, wind speed and direction, water mist density, water mist particle size and ejector wind speed, a parameter self-correction algorithm is applied to establish a coupling relationship model between the airflow field, water mist field and dust field. Based on the model evaluation results, the optimal adjustment parameters for water mist particle size, spray device arrangement, and ejection intensity of the dual ejector device are dynamically calculated; Based on the optimal adjustment parameters, adjust the nozzle diameter, spray angle, spray pressure, and spray flow rate of the spray device, as well as the ejector wind speed, airflow rate, and throttling ratio of the dual ejector device; The optimization results are fed back to the three-field linkage model of airflow field, water mist field and dust field to update the model parameters and control strategy library, so as to realize full-cycle intelligent regulation and strategy iteration.

[0013] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention achieves scientific setting of water mist particle size and spray strategy by constructing a dynamic mapping model between the airflow disturbance zone and the dust-prone zone, ensuring that the water mist has optimal settling inertia and coverage effect under different wind speeds and airflow energy. Through the construction of multi-level adjustable spraying and gradient fog fields, the directional retention and dust source coverage capabilities of the water mist in complex airflow environments are effectively enhanced. The introduction of wind-mist guiding and slow-release flow zone design stabilizes the spatial distribution of dust settling and suppresses water mist particle deviation and dust re-diffusion. Combined with a three-field linkage model and parameter self-correction algorithm, dynamic adaptive optimization of spray and ejector parameters is achieved, ensuring that the dust suppression system is always in optimal control state under different tunneling stages and ventilation conditions, avoiding safety hazards such as dust clouds, equipment mudding, and monitoring distortion. Overall, this solution effectively solves the problem of uncoordinated wind control between spraying and ejector, improves dust collection and settling efficiency, reduces energy consumption and human adjustment burden, and comprehensively ensures the safety, stability, and green sustainability of the working environment in coal mine tunneling faces. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0015] Figure 1 This is a flowchart of the method for the dust suppression and dust control linkage method based on dust monitoring in a coal mine fully mechanized tunneling face according to the present invention. Detailed Implementation

[0016] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0017] This invention provides, for example Figure 1 The method for joint dust control based on dust monitoring in a fully mechanized coal mine tunneling face, as shown, includes the following steps: S1. Based on the spatial layout of the coal mine tunneling face and the dust diffusion trend, a dynamic mapping model of the airflow disturbance zone and the dust high-incidence zone is constructed. Based on the dust diffusion behavior under different wind speed conditions, the settling inertia threshold required for water mist particles to settle in the dust source area is extracted, and the initial parameters of water mist particle size and spray strategy are set based on the settling inertia threshold. Based on the spatial layout and dust diffusion trend of the coal mine tunneling face, a dynamic mapping model between the airflow disturbance zone and the dust-prone zone is constructed. Based on the dust diffusion behavior under different wind speed conditions, the settling inertia threshold required for water mist particles to settle in the dust source area is extracted. Based on this settling inertia threshold, the initial parameters of the water mist particle size and spray strategy are set, specifically including the following steps: Based on the actual geology and construction layout of the fully mechanized tunneling face in the coal mine, a three-dimensional spatial model of the face is constructed to obtain the accurate spatial distribution of facilities such as the tunneling head, ventilation roadways, transportation channels, return air channels, tunneling machines, conveying equipment, and support structures. By establishing the three-dimensional model of the face and combining historical data on wind speed, wind pressure, airflow patterns, and dust concentration collected during previous tunneling operations, computational fluid dynamics (CFD) simulation methods are used to simulate the airflow field distribution and dust diffusion paths under different tunneling stages, ventilation configurations, and airflow rates. Through simulation calculations, spatial regions where airflow disturbance, turbulence, and backflow occur within the fully mechanized tunneling face under different wind speeds and pressures, as well as high-dust-concentration areas where dust continuously accumulates, are identified. Combining the operating frequency of tunneling equipment within the face, the location of coal and rock fractures, and the distribution of dust generation sources, a dynamic spatial mapping relationship between airflow disturbance zones and high-dust-concentration zones is established, forming a dynamically updatable spatial positioning and dust distribution model during the tunneling process.

[0018] Computational fluid dynamics (CFD) simulation methods utilize numerical computation techniques and fluid mechanics theory. Based on the governing equations of continuous media, such as the Navier-Stokes equations, mass conservation equations, and energy conservation equations, it simulates and predicts the flow behavior of gases or liquids in complex spaces by numerically discretizing and solving for the changes in physical parameters such as velocity, pressure, temperature, and concentration. In this step, the role of CFD simulation is to input the geometric features of all entities, including the tunnel face, roadway, ventilation ducts, support structures, and tunneling machine, into the simulation software based on a three-dimensional spatial model of the coal mine tunneling face. Combined with historical data on wind speed, wind pressure, airflow patterns, and dust concentration collected during tunneling operations, different tunneling stages, ventilation configurations, and wind speed and pressure conditions are set. The specific steps are as follows: Construct a complete three-dimensional geometric model of the working surface and mark the locations of all air sources, return air vents, and equipment. Set boundary and initial conditions, including fan air volume, duct cross-sectional velocity, working face air pressure, dust source generation intensity and particle size distribution; Turbulence models (such as the k-ε model or large eddy simulation) are used to solve for the velocity vector, pressure distribution and eddy formation of the airflow field. Furthermore, the diffusion, transport and sedimentation paths of dust particles in the airflow are simulated using the Lagrange method or the Eulerian method to obtain a spatial distribution map of dust migration, deposition and accumulation with the airflow. Based on simulation results, the specific locations and evolution trends of airflow disturbance zones, turbulence zones, local recirculation zones, and high-dust zones are identified, enabling accurate prediction and dynamic visualization of airflow and dust behavior under different tunneling stages and ventilation conditions. This provides a scientific basis for subsequent dust reduction parameter setting and wind control and dust reduction linkage strategies.

[0019] Based on the constructed spatial dynamic mapping model, and combined with the dynamic simulation results of dust particle size distribution, diffusion path, and residence time under different wind speeds and pressures, the inertial impact, turbulent diffusion, and gravity settling behavior of dust particles under different flow velocities and directions are analyzed. The Lagrange particle tracking method is used to calculate the trajectory and settling process of water mist particles of different sizes within the airflow disturbance zone, quantifying the minimum settling inertia threshold required for water mist particles to reach the dust source area, achieve effective encapsulation, and complete settling under different wind speeds. This threshold is calculated by comprehensively considering the particle response coefficient, airflow shear rate, and Stokes number of the water mist particles, determining the minimum kinetic characteristics required for water mist particles to overcome airflow entrainment and effectively capture dust under different airflow kinetic energies.

[0020] The Lagrange particle tracking method is a particle dynamics calculation method based on the Lagrange coordinate system. It involves tracking the motion path of each individual particle in a flow field, dynamically calculating the changes in the particle's velocity, position, and forces within the airflow, reflecting the interaction between particles and fluids and the entire process of their migration, diffusion, and sedimentation. In this invention, this method is used to accurately simulate the trajectory, velocity changes, and sedimentation behavior of water mist particles of different sizes in the airflow disturbance zone of a coal mine tunneling face. This allows for the assessment of the minimum sedimentation inertia threshold required for water mist to reach the dust source area, coat the dust, and complete sedimentation under different wind speed conditions. The specific steps are as follows: Using the wind flow field data obtained through computational fluid dynamics simulation as the background flow field input, the spatial distribution basis of airflow velocity, pressure, vorticity, etc. in the wind flow disturbance zone is established. Water mist particles of different sizes are released sequentially in the flow field. Based on Newton's second law, the gravity, buoyancy, aerodynamic force, drag and turbulence acting on the particles are comprehensively considered. By solving the particle dynamics equations, the real-time position, velocity and acceleration of each particle are tracked, and its complete migration and sedimentation path is recorded. For each size of water mist particle, the residence time, retention space range and settling ratio in the dust source area are statistically analyzed under different wind speeds. The Stokes number and Reynolds number are calculated to determine whether the particles have sufficient inertia to penetrate the airflow and achieve the encapsulation and settling of the dust source. Based on the settling and retention effects of particles of different sizes, the minimum settling inertia threshold that water mist particles must reach under different wind speeds can be deduced. This is the minimum dynamic performance standard that particles must meet to overcome wind interference and achieve dust capture, providing a quantitative basis for the scientific setting of spray particle size and the precise control of spray parameters.

[0021] Based on the aforementioned settling inertia threshold, the optimal particle size distribution range for water mist particles is determined, along with the corresponding physical parameters such as spray pressure, nozzle orifice diameter, spray angle, and spray velocity. By comparing and analyzing the particle size control capabilities of water mist particles generated under different spray device structures and mist output parameters, a nozzle with multi-stage atomization capability is selected, and a corresponding high-pressure water pump and pressure-stabilizing water supply device are configured to ensure that the spray system can automatically adjust the water mist particle size according to the settling inertia threshold of the dust source area under different dust source intensities and airflow variations, achieving precise coverage and settling of the dust source area. During this process, by combining real-time monitoring data of the working face wind speed and the dynamic changes in dust generation intensity, a correspondence between spray parameters and airflow conditions and dust source intensity is established, forming the initial parameter set for the spray strategy.

[0022] The determined water mist particle size range and initialization parameters of the spray strategy are used as the basic configuration for dust suppression control, integrated into the dust suppression control command system, and a parameter calling mechanism is set up to be triggered by monitoring signals such as working face wind speed and dust concentration. Whenever the environmental parameters of the tunneling face change, such as ventilation adjustment, tunneling speed change, or dust generation fluctuation, the dust suppression control dynamically selects or adjusts the corresponding water mist particle size, spray pressure, spray angle, and spray time according to the preset settling inertia threshold, thereby ensuring that the spray coverage of the dust source area is always in the optimal state.

[0023] This step aims to provide scientific and quantitative basic parameters to support precise dust control in coal mine tunneling faces, addressing the problem of insufficient dust suppression efficiency caused by the incoordination between water mist dust suppression and airflow entrainment. Due to the complex spatial layout, frequent operation of tunneling equipment, and diverse arrangements of ventilation ducts and equipment in coal mine tunneling faces, the airflow field exhibits significant disturbances, turbulence, and local backflow phenomena, resulting in highly uneven diffusion and accumulation of dust in different areas. Without a dynamic understanding of the airflow field and dust diffusion paths, water mist spraying may be prematurely carried away by the airflow and deviate from the dust source due to particle size mismatch or improper spraying strategies, failing to effectively capture dust. This step, based on the spatial structure and dust diffusion trends of the tunneling face, first constructs a dynamic mapping model between airflow disturbance zones and high-dust-occurrence zones, achieving precise spatial positioning of the airflow-dust coupling behavior within the working face. Secondly, based on the dust diffusion dynamics under different wind speeds, the key parameter for dust capture—the minimum settling inertia threshold required for water mist particles to settle in the dust source area—is extracted. This threshold quantifies the dynamic capabilities required of water mist particles, enabling them to penetrate the flow field and stably settle into the dust source area despite airflow disturbances. Finally, this inertia threshold is used as the basis for setting parameters such as water mist particle size, spray pressure, and spray angle, forming the initial configuration of spray strategies for different working conditions, ensuring precise coordination of subsequent wind control and dust suppression measures. This step effectively improves the accuracy and sustainability of dust suppression, avoids resource waste and safety hazards in the dust suppression process, and lays a data foundation and control reference for dynamic linkage control.

[0024] S2, based on the settling inertia threshold, by adjusting the atomization structure and mist output parameters of the spray device, multi-level adjustable control of water mist particle size is formed, and differentiated spray devices are configured in the wind disturbance boundary area to generate a spatially continuous gradient fog field, so as to improve the directional retention performance of water mist in different airflow energy zones. By adjusting the atomization structure and mist output parameters of the spray device, multi-level adjustable control of water mist particle size is achieved. Differential spray devices are configured in the airflow disturbance boundary region to generate a spatially continuous gradient fog field, thereby improving the directional retention performance of water mist in different airflow energy zones. Specifically, the following steps are included: Based on the previously extracted settling inertia threshold required for water mist particles to settle in the dust source area, the optimal water mist particle size distribution range was determined, and this range was further divided into multiple particle size ranges, each corresponding to a specific wind speed, wind pressure, and dust distribution characteristic. Based on this, the atomization structure of the spray device was designed specifically, including the nozzle orifice diameter, number of orifices, nozzle spray angle, and the multi-stage compression structure of the internal atomization chamber. By controlling the diameter and number of orifices, combined with the dual effects of hydraulic and pneumatic pressure applied during spraying, fine gradation of the atomization process was achieved. This ensured that the sprayed water mist particles could cover a particle size range from 5 micrometers to 50 micrometers under different operating modes, guaranteeing that the water mist particles possessed the kinetic characteristics to meet the settling inertia threshold under different airflow rates. This ensured that the particles could resist airflow traction while guaranteeing sufficient coverage and retention in the dust source area.

[0025] By designing the atomization structure of the spray device specifically, precise control and multi-level adjustment of water mist particle size can be achieved to adapt to the dust suppression needs of different airflow energy zones. The nozzle orifice diameter refers to the diameter of the nozzle holes, which directly determines the degree of atomization and the final water mist particle size during spraying. Smaller orifice diameters result in finer water mist with smaller particle sizes, suitable for retention in low-wind-speed, low-energy zones; larger orifice diameters result in larger water droplet sizes with stronger inertia, suitable for penetrating high-speed airflows directly to the dust source. The number of nozzle holes refers to the total number of holes on the nozzle head. A larger number of holes results in a larger total amount of water mist sprayed per unit time, with a wider coverage area. The density of the local mist field can be adjusted by changing the number of holes. The nozzle spray angle determines the spatial diffusion range and spray coverage width of the water mist. Smaller spray angles can form concentrated, long-range water mist jets, suitable for targeted coverage of dust source areas; larger spray angles can form large-area, uniformly diffused water mist clouds, suitable for diffuse dust suppression. The multi-stage compression structure of the internal atomization chamber refers to the high-energy atomization effect achieved by the water flow inside the nozzle after passing through a series of progressively contracting, pressurizing, and turbulent channels. This structure can flexibly adjust the flow rate and turbulence intensity of the water under different pressure conditions, ensuring that the water is fully atomized and classified into particles before being sprayed out. This allows for dynamic adaptation to water mist particle size and efficient dust suppression under different airflow environments. The combined design of these structural parameters enables the spray device to flexibly adjust the particle size, density, and coverage of the water mist according to the dynamic changes in wind speed, wind pressure, and dust distribution at the tunneling face, achieving precise and stable control of complex and variable dust environments.

[0026] Based on the spatial distribution patterns of airflow disturbance zones, turbulent zones, and main airflow channels in the tunneling face, a differentiated spray device deployment strategy was developed, taking into account previous simulation and field measurement results. At airflow disturbance boundaries, abrupt changes in wind speed gradients, and locations with severe airflow turbulence, spray devices capable of generating medium-sized (20-30 micrometers) water mist were prioritized to achieve stable suspension and localized humidification of the water mist in the airflow energy transition zone. In the main airflow channel and high-speed airflow zones, spray devices generating large-sized (30-50 micrometers) water mist were configured to enhance the inertia of the water mist particles, improve their ability to penetrate the airflow, and ensure that the water mist particles are not prematurely carried away by the airflow. In areas with slow airflow, backflow, or localized low speeds, spray devices capable of spraying small-sized (5-15 micrometers) water mist were installed to enhance the dispersion and coverage of water mist particles near the dust source. Through the rational configuration of differentiated spray devices, precise matching of spray particle size and airflow energy zones was achieved, forming a spatially continuous and layered gradient fog field.

[0027] Based on the differentiated spray device configuration, the mist output parameters of the spray device are further dynamically adjusted. According to real-time monitoring data of wind speed, wind pressure, and dust concentration, the spray pressure, spray flow rate, and spray angle are automatically adjusted to adapt to the dust suppression needs of different areas and working conditions in the tunneling face. For example, when an increase in wind speed is detected in the main airflow channel, the spray pressure is automatically increased to enlarge the water mist particle size, ensuring that the inertia of the water mist particles meets the settling requirements. When the wind speed decreases or the dust concentration increases in the airflow disturbance zone, the spray angle and flow rate are adjusted to enhance the retention and coverage of the water mist. Through this dynamic parameter adjustment, the stability and continuity of the gradient fog field in both time and space are ensured, enabling the water mist to achieve directional retention and dust capture in different airflow energy zones.

[0028] To continuously optimize the directional retention performance of water mist in different airflow energy zones, the atomization structure parameters and mist output parameters of the spray device are coded one-to-one with the spatial location of the airflow disturbance zone, establishing a mapping database for spray layout and adjustment. Through continuous data accumulation and iterative optimization, based on feedback results from different tunneling stages, different ventilation configurations, and different dust distributions, the layout position of the spray device, the spray particle size combination, and the injection strategy are continuously adjusted to achieve dynamic reconstruction and optimal control of the gradient fog field.

[0029] The purpose of this step is to achieve multi-level adjustable water mist particle size through precise control of the atomization structure and mist output parameters of the spray device. This adapts to the dust suppression requirements of different airflow energy environments within the coal mine tunneling face, such as the airflow disturbance zone, the main airflow zone, and the low-speed return flow zone. This improves the directional retention performance of the water mist in each area, ensuring effective coverage of the dust source and its diffusion path. Due to the complex airflow field within the tunneling face, with high-speed airflow, turbulence, and return flow coexisting, if the water mist particle size does not match the airflow energy level, water mist with too small a particle size is easily carried away from the dust source by the high-speed airflow, while water mist with too large a particle size, although possessing inertia, lacks sufficient dispersion and is difficult to cover the dust diffusion area. Therefore, by designing the atomization structure of the spray device (such as nozzle diameter, number, spray angle, and internal multi-stage compression channels) and mist output parameters (such as spray pressure and flow rate) based on the previously calculated settling inertia threshold, the orderly output of water mist with different particle sizes can be achieved, forming a multi-level particle size mist field. Furthermore, by configuring differentiated spray devices at the boundary of airflow disturbance, small-diameter, medium-diameter, and large-diameter spray devices are arranged according to the wind speed and dust characteristics of each area, forming a gradient fog field that combines particle size gradient with spatial continuity. This gradient fog field can not only form large-diameter droplets with high inertia and high penetration in high-speed airflow areas to ensure direct dust settling at dust sources, but also form fine water mist in low-speed, backflow, or turbulent areas to enhance dust capture and settling effects. Through this precise matching of particle size and arrangement, the residence time and coverage density of water mist in different airflow energy zones are significantly improved, achieving directional, continuous, and efficient dust settling. This effectively overcomes the problems of dust settling failure and water waste caused by traditional single spray strategies, while providing a physical basis for subsequent coordinated wind control and dynamic spray regulation.

[0030] S3, based on the retention characteristics of gradient fog field, sets up wind and fog guiding structure unit, and forms slow release flow zone in dust source area through weak wind control mechanism, enhances the suspension coverage time of water mist particles in dust source area, suppresses the phenomenon of water mist particles being entrained and deflected by the main wind flow, and stabilizes the distribution of dust falling space. Based on the retention characteristics of gradient fog fields, a slow-release flow zone is formed in the dust source area by setting up wind-fog guiding structure units and adopting a weak wind control mechanism. This enhances the suspension and coverage time of water mist particles in the dust source area, suppresses the phenomenon of water mist particles being entrained and deflected by the main airflow, and stabilizes the distribution of dust settling space. Specifically, the steps include: Based on the spatial distribution pattern of the gradient fog field established in the early stage within the tunneling face, and considering the boundary characteristics between the airflow disturbance zone and the dust source area, a wind-fog guiding structure unit was designed and installed. This wind-fog guiding structure consists of a combination of multi-plate guide plates at fixed angles, an annular flow divider, and lateral flow-limiting grids. It is arranged in front of and to both sides of the dust source according to the wind speed distribution at the tunneling face, the direction of the main airflow, and the relative position of the high-dust-occurrence area. The tilt angle of the guide plates was precisely calculated to disperse the kinetic energy of the main airflow, weakening its entrainment effect on water mist particles, while also guiding part of the main airflow around it, thus forming a buffer zone with lower airflow kinetic energy around the dust source area. This buffer zone lays the foundation for the subsequent slow-release flow zone, preventing water mist particles from being carried away from the dust source area by the strong airflow before settling.

[0031] Within the buffer zone created by the wind-mist guiding structure unit, a weak wind direction control mechanism is further employed. Miniature low-speed air supply devices are introduced into the dust source area. These devices are arranged along the dust source area, delivering low-speed, directional micro-winds to create localized wind interference that is opposite to or perpendicular to the main airflow. By precisely controlling the air supply speed between 0.5 and 1.5 meters per second, this weak wind ensures that it does not disrupt the overall flow field stability of the ventilation system. Simultaneously, it creates localized turbulence and deceleration zones in the dust source area, reducing the velocity of water mist particles and significantly increasing their suspension time and spatial retention density. This establishes a protective barrier for the dust source area, ensuring sufficient contact and coverage between water mist and dust.

[0032] To enhance the stability of the slow-release flow zone and the uniformity of dust distribution, a directional spraying device is deployed above and to the sides of the dust source area, in conjunction with a weak wind control mechanism and a wind-mist guiding structure. This device specifically sprays medium-sized water mist, with a particle size controlled between 20 and 30 micrometers, using an upward or side spraying mode. This allows the water mist cover layer to work synergistically with the low-speed wind to form a stable three-dimensional dust-falling mist layer. Assisted by the low-speed airflow, this mist layer continuously covers the dust source, creating a dynamically stable dust-falling space. This effectively controls the rise, drift, and diffusion of dust, while simultaneously suppressing the displacement or annihilation of the water mist due to the shearing effect of the main airflow.

[0033] To respond to and regulate dynamic changes in the slow-release flow zone, the dust concentration, wind speed, and water mist density in the dust source area are monitored in real time. Feedback is used to control the outlet air velocity and direction of the air supply equipment, while simultaneously adjusting the spray intensity and angle of the directional spray device. When monitoring data indicates an increase in the main airflow intensity or a rise in dust concentration, the wind speed and spray flow rate of the micro-air supply are automatically increased to enhance the protective capability of the slow-release flow zone; conversely, energy consumption is appropriately reduced to maintain a balance between dust suppression efficiency and energy consumption.

[0034] This step aims to address the issues of unstable dust suppression, insufficient water mist retention, and susceptibility to being carried away by the main airflow in coal mine tunneling face dust source areas. It ensures that water mist particles can form a continuous and effective dust suppression barrier in and around the dust source area. Due to the complex airflow disturbances and variable airflow energy distribution at the tunneling face, traditional spraying methods, after release, easily cause water mist particles, especially smaller droplets, to be entrained and deflected to non-dust source areas under high-speed or turbulent airflow conditions. This results in inconsistent or even ineffective dust suppression in the dust source area, and insufficient contact time between the water mist and dust, leading to low collection and settling efficiency. Therefore, this step utilizes the retention characteristics of gradient fog fields, designs a wind-mist guiding structure, and rationally adjusts the path and kinetic energy of the main airflow to create a buffer and redistribution of airflow, reducing the direct impact and interference of the main airflow on the water mist. Simultaneously, through a weak wind direction control mechanism, a slow-release flow zone with low velocity and stable direction is formed locally in the dust source area. This slow-release flow zone significantly prolongs the suspension and coverage time of water mist particles at dust sources, promoting sufficient physical contact and adhesion between water mist and dust, thereby improving dust coverage and settling efficiency. Furthermore, through the synergistic effect of wind-mist guidance and weak wind direction control, the water mist distribution in the dust source area can be stabilized, preventing water mist particles from accumulating in high-risk areas such as tunneling heads, turns, or areas with poor return airflow due to flow field disturbances. This prevents the formation of localized high-humidity dust clouds and the resulting safety hazards such as equipment corrosion and ventilation blockage. Therefore, this step has irreplaceable key value for achieving stable and uniform dust distribution, ensuring continuous and efficient dust control, and improving the working environment. It also provides the necessary flow field and mist field basis for the dynamic adjustment of subsequent intelligent wind control and dust suppression strategies.

[0035] S4. Miniature environmental detection units are deployed in the slow-release flow zone to collect real-time dust concentration, wind speed vector and water mist density data. Based on the collected data, a three-field linkage model of wind flow field, water mist field and dust field is established to continuously evaluate the local adaptability of the dust suppression system and the suppression effect of wind flow disturbance. Miniature environmental detection units are deployed within the slow-release flow zone to collect real-time dust concentration, wind speed vector, and water mist density data. Based on the collected data, a three-field linkage model of the airflow field, water mist field, and dust field is established to continuously evaluate the local adaptability of the dust suppression system and its effect on suppressing airflow disturbance. The specific steps include: Based on the spatial characteristics of the slow-release flow zone already formed in the tunneling face, and considering the distribution of airflow disturbances, the concentration areas of dust sources, and the key locations of water mist retention, the deployment location and density of micro-environmental detection units were precisely planned. The detection units were arranged to cover the upstream, middle, and downstream parts of the slow-release flow zone, ensuring full-process sensing of the spatial changes in local airflow, dust, and water mist. Each detection unit integrates a high-precision laser dust concentration sensor, a three-dimensional ultrasonic anemometer, and a light-scattering water mist density sensor, enabling simultaneous sensing of changes in dust concentration, wind speed and direction vectors, as well as the spatial density and particle size changes of water mist in the microenvironment. All detection units are connected to the data acquisition device via wired or wireless communication networks, ensuring real-time and continuous data acquisition.

[0036] Dynamic data on dust concentration, wind speed vector, and water mist density collected by a micro-environmental detection unit are integrated and processed to construct a multi-dimensional time-series dataset. Feature extraction and dynamic modeling are then performed on this dataset. Based on the spatial distribution of the wind speed vector field, the airflow field within the slow-release flow zone is reconstructed, clarifying the airflow direction, velocity distribution, and vortex location. Based on the spatial variation of dust concentration, the concentration distribution and migration trend of the dust field are plotted. Through spatial analysis of water mist density and particle size, a model of the water mist field's coverage density and particle size distribution is established. These three types of data are then used for mathematical modeling and numerical analysis, employing a multi-field coupling modeling method to form a three-field linkage model of the airflow field, water mist field, and dust field. The model incorporates a coupling mechanism between fluid dynamics and particle dynamics to achieve a dynamic description of the interactions between the three media.

[0037] Based on a three-field linkage model and combined with real-time data feedback, the local adaptability and airflow disturbance suppression effect of the dust suppression system are continuously evaluated at different time points and operating conditions. By comparing model predictions with actual monitoring data, the stability of the airflow field, the retention effect of the water mist field, and the diffusion trend of the dust field are assessed to determine whether the preset dust suppression targets have been achieved. When the model detects intensified airflow disturbance, decreased water mist density, or abnormally high local dust concentration, the model can promptly output intervention signals, providing quantitative basis for adjusting spray intensity, ejector velocity, or weak wind control direction, ensuring that the dust suppression system always operates in the optimal dust suppression state.

[0038] To achieve dynamic iteration and continuous optimization of the model, the parameters and structure of the three-field linkage model are periodically adaptively corrected and upgraded based on long-term monitoring data of the detection unit. Machine learning algorithms are used to perform deep learning and prediction on the spatiotemporal evolution of airflow disturbance, water mist attenuation and dust accumulation, thereby improving the model's response and adaptability to changes in complex working conditions at the working face.

[0039] The purpose of this step is to achieve real-time dynamic monitoring of the three media states—dust, airflow, and water mist—by deploying micro-environmental detection units within the slow-release flow zone. Based on the monitoring data, a three-field linkage model of the airflow field, water mist field, and dust field is established, thereby comprehensively understanding the local adaptability of the dust suppression system and its effectiveness in suppressing airflow disturbances in the actual working environment. Due to the complex airflow field at coal mine tunneling faces, there are uncertain changes in wind speed, wind direction, turbulence intensity, and local backflow. Dust concentration and diffusion paths exhibit dynamic fluctuations, and the coverage density and particle size distribution of water mist also change with airflow and spray conditions. Without real-time monitoring and analysis of these variable factors, the adjustment measures of the dust suppression system often lag behind, leading to unstable dust suppression effects or even local failures, resulting in safety hazards such as excessive dust levels and dust cloud accumulation. Therefore, by deploying micro-environmental detection units capable of simultaneously measuring dust concentration, wind speed vector, and water mist density, a dense sensing network can be formed within the slow-release flow zone, accurately capturing changes in the local microenvironment. Based on this multi-source data, a three-field linkage model is established to digitally and dynamically describe and evaluate the entire process of airflow pulling and distributing water mist, water mist encapsulating and settling dust, and dust diffusion and resuspension. This model not only reflects the real-time operating status of the dust suppression system but also continuously assesses and predicts key indicators such as whether airflow disturbances are effectively suppressed, whether dust suppression measures adequately cover the dust source area, and whether there is abnormal accumulation of local dust. This step provides a scientific basis for the intelligent adjustment of the dust suppression system and the dynamic optimization of spray intensity and airflow entrainment, achieving precise, stable, and efficient dust control, and greatly improving the safety of the working environment and the level of dust control in coal mine tunneling faces.

[0040] S5, based on the response index output by the three-field linkage model of airflow field, water mist field and dust field, dynamically adjusts the spray volume and the ejection wind speed of the dual ejector device, maintains the coordinated change of water mist particle size distribution and airflow energy, forms a coupled response mechanism of wind control and dust suppression, and achieves precise distribution of water mist coverage, stability of airflow guidance and minimization of dust disturbance. Based on the response indicators output by the three-field linkage model of airflow field, water mist field, and dust field, the spray volume and the ejector wind speed of the dual ejector device are dynamically adjusted to maintain the coordinated change of water mist particle size distribution and airflow energy, forming a coupled response mechanism for wind control and dust suppression. This achieves precise distribution of water mist coverage, stability of airflow guidance, and minimization of dust disturbance. Specifically, the following steps are included: Based on the previously established three-field linkage model of airflow, water mist, and dust, the system receives real-time dynamic data such as dust concentration, wind speed vector, and water mist density from micro-environmental detection units deployed in the slow-release flow zone and other key areas of the tunneling face. Through model calculation and analysis, it outputs response indicators for the current working environment, including local airflow intensity, wind speed gradient, dust concentration change rate, and water mist particle size and density suitability evaluation indicators. These response indicators comprehensively reflect the wind control and dust suppression effects of the current dust suppression system and determine whether the existing adjustment state matches the dynamic operating conditions, providing a quantitative basis for subsequent adjustment actions.

[0041] Based on the response indicators output by the three-field linkage model, the spray volume and spray pressure of the spray device are dynamically adjusted. When the model determines that the current airflow intensity is high, the dust diffusion trend is enhanced, and the water mist particle size is insufficient for stable settling, the spray volume is automatically increased. By increasing the spray flow rate and pressure, larger-diameter water mist particles are generated to enhance inertia and improve the coverage and coating effect on the dust source area. When the airflow weakens or the dust concentration decreases, the spray flow rate and pressure are appropriately reduced to avoid excessive spraying causing local water accumulation or wet dust buildup. At the same time, the precise matching of spray particle size is maintained to ensure a balance between dust suppression effect and energy saving.

[0042] The dynamic adjustment and synchronous control of the ejector speed of the dual ejector device based on spray parameters precisely adjusts the inlet airflow and the throttling ratio of the ejector channel according to real-time changes in the airflow field. When turbulent airflow or insufficient local wind speed is detected, the ejector speed is appropriately increased to enhance airflow guidance capability, stabilize the flow state and direction of the airflow channel, and prevent dust accumulation due to unstable flow field. When the local wind speed is too high and the risk of water mist deviation in the dust source area increases, the ejector speed is reduced to avoid the entrainment effect of the main airflow on the water mist, maintain the suspension and retention of water mist in the dust source area, and ensure sufficient contact and capture of water mist and dust through coordinated control of airflow and water mist.

[0043] By coordinating the spray volume and ejector velocity as described above, a coupled response mechanism for wind control and dust suppression is formed. Real-time adjustment parameters, dust changes, and airflow status are fed back to the three-field linkage model, continuously optimizing the model's prediction and control accuracy. This coupled response mechanism can dynamically adapt to the spatiotemporal changes in airflow, dust, and water mist at the tunneling face, ensuring precise distribution of water mist coverage, stable airflow guidance, and minimal dust disturbance under different tunneling speeds, ventilation adjustments, or dust outbreaks. Ultimately, this achieves intelligent, dynamic, and efficient dust control at the tunneling face, comprehensively improving the safety of the working environment and the level of intelligent ventilation and dust removal.

[0044] The purpose of this step is to achieve coordinated changes between water mist particle size distribution and airflow energy by dynamically adjusting the spray volume and the ejector wind speed of the dual ejector device. This forms a coupled response mechanism for wind control and dust suppression, addressing the complex environment of dynamically changing airflow, dust, and water mist at the coal mine tunneling face, and achieving precise and efficient dust control. At the tunneling face, due to the influence of various factors such as tunneling speed, ventilation adjustments, and equipment operation, the airflow intensity, wind direction, dust concentration, and spatial distribution of water mist are constantly changing. If the spray and ejector parameters are not adjusted according to real-time environmental changes, it can easily lead to a mismatch between water mist particle size and airflow energy. This can result in problems such as water mist particles that are too small being drawn in and deflected by the main airflow, water mist particles that are too large and not retained sufficiently, excessively strong airflow disrupting water mist distribution, or insufficiently strong airflow causing poor dust diffusion. This reduces overall dust suppression efficiency and may even induce localized dust accumulation, posing a safety hazard. This step dynamically adjusts the spray volume to control the particle size and density of the water mist based on the response indicators output by a three-field linkage model of the airflow field, water mist field, and dust field. Simultaneously, it adjusts the ejector wind speed of the dual ejector device to precisely control the energy and direction of the airflow. This allows the water mist to form a uniformly covered and appropriately dense dust-suppressing barrier in the dust source area and its diffusion path, enhancing the airflow guidance effect and effectively suppressing dust migration and disturbance caused by the airflow. This mechanism achieves deep linkage and dynamic response between wind control and dust suppression at the strategy and execution levels. It not only improves the precise coverage and capture effect of the water mist on the dust source area but also ensures the stability and order of the airflow, avoiding dust suppression failure or secondary dust generation caused by turbulent flow fields. Ultimately, it achieves continuous, safe, and intelligent control of dust management at the tunnel boring machine face.

[0045] S6, based on the stable operation of the wind control and dust suppression coupled response mechanism, combined with periodically collected multi-source monitoring data, applies a parameter self-correction algorithm to continuously optimize the water mist particle size, spray device layout and the ejection intensity of the dual ejector device, establishes a complete full-cycle intelligent control and strategy iteration mechanism, and dynamically maintains the optimal level of dust reduction efficiency and working environment safety in coal mine tunneling faces. Based on the stable operation of the coupled response mechanism of wind control and dust suppression, combined with periodically collected multi-source monitoring data, and applying a parameter self-correction algorithm, the water mist particle size, spray device layout, and ejection intensity of the dual ejector device are continuously optimized. A complete full-cycle intelligent control and strategy iteration mechanism is established to dynamically maintain the optimal level of dust reduction efficiency and working environment safety in coal mine tunneling faces. Specifically, the following steps are included: Based on the stable operation of the wind control and dust suppression coupled response mechanism, multi-source monitoring data within the tunneling face are systematically collected through pre-deployed micro-environmental detection units at a set periodic acquisition frequency. The collected data covers dust concentration, wind speed and direction vectors, water mist density, water mist particle size distribution, airflow disturbance level, dust diffusion path, and real-time operating parameters of the spray and ejector devices. All data is transmitted to the data processing center through a unified digital interface, forming a continuous, time-series multi-dimensional dataset, providing comprehensive basic data support for subsequent parameter self-correction and strategy optimization.

[0046] Based on the collected data, a parameter self-correction algorithm was applied to dynamically calculate and optimize the water mist particle size, the layout of the spray device, and the ejection intensity of the dual ejector device. The parameter self-correction algorithm, based on machine learning and big data analysis methods, first extracts features from key influencing factors in historical and real-time data to form a coupling relationship model among airflow, water mist, and dust. This model adaptively adjusts weights and parameters to continuously evaluate the adaptability of current dust suppression measures under different operational stages, ventilation conditions, and tunneling speeds. It automatically identifies potential problems such as decreased dust suppression efficiency, excessive energy consumption, or localized dust concentration rebound, and calculates the optimal water mist particle size adjustment range, recommended spatial rearrangement of the spray device, and dynamic adjustment value for the ejection intensity.

[0047] Parameter self-adjustment algorithms, based on machine learning and big data analytics, utilize machine learning models to extract features, recognize patterns, and model causal relationships from key influencing factors (such as dust concentration, wind speed, wind direction, water mist density, water mist particle size, and ejector wind speed) in large amounts of historical and real-time monitoring data. This dynamically establishes the coupling relationship between airflow, water mist, and dust, and continuously adjusts and updates control parameters (such as spray particle size, spray flow rate, and ejector wind speed) based on feedback from actual dust reduction effects. Commonly used parameter self-adjustment algorithms include supervised learning-based random forest regression, gradient boosting tree (GBDT), and support vector regression (SVR). These algorithms excel at uncovering complex mapping relationships between parameters and dust reduction effects from nonlinear, high-dimensional features. Neural network models (such as LSTM or GRU) can also be used to process time-series data, capturing the dynamic characteristics of airflow, water mist, and dust over time. Furthermore, reinforcement learning-based methods, such as deep deterministic policy gradient (DDPG) or proximal policy optimization (PPO), can also achieve adaptive optimization of control parameters in continuously changing environments. Through training and iteration of these algorithms, the parameter self-correction algorithm can achieve real-time adjustment, strategy optimization and continuous evolution of the dust suppression system, ensuring that dust suppression efficiency and energy consumption control are always at the optimal level.

[0048] Based on the optimization results output by the parameter self-correction algorithm, the working mode of the spray device is dynamically adjusted, including adjusting the nozzle orifice diameter, spray angle, spray pressure, and flow rate to ensure that the water mist particle size is always precisely matched with the current airflow energy level. Simultaneously, according to the optimized layout, the spatial position and spray direction of the spray device within the working surface are adjusted to ensure optimal water mist coverage in the dust source area and its diffusion channels. Furthermore, the ejector wind speed, inlet airflow, and throttling ratio of the dual ejector device are precisely controlled to ensure that the guiding effect of the airflow is always synchronized and coordinated with the water mist coverage, preventing water mist particles from being excessively pulled or deflected by the main airflow, thus improving the stability and continuity of dust suppression.

[0049] Through continuous optimization and dynamic adjustment, a complete full-cycle intelligent control and strategy iteration mechanism is established. The optimization results are integrated with the three-field linkage model to form a closed-loop feedback loop. After each optimization, the model parameters and control strategy library are automatically updated, forming a self-learning and evolutionary capability. This mechanism not only dynamically responds to environmental changes during operation, ensuring the dust suppression system always operates at its optimal state, but also quickly adapts and reconstructs the optimal dust suppression strategy after changes in the working conditions of the tunneling face, the introduction of new equipment, or adjustments to the ventilation system. This achieves full-cycle, full-process dynamic optimal control of dust suppression efficiency and operational environmental safety, ensuring safe, green, and efficient management of the coal mine tunneling face during long-term operations.

[0050] The purpose of this step is to continuously and dynamically optimize the core control parameters of the dust suppression system, such as water mist particle size, spray device layout, and the ejection intensity of the dual ejector device, through stable operation based on the coupled response mechanism of wind control and dust suppression, combined with periodically collected multi-source monitoring data, and by applying a parameter self-correction algorithm. This achieves optimal maintenance of dust suppression efficiency and working environment safety throughout the entire lifecycle of the coal mine tunneling face. In the tunneling face, with the continuous changes in tunneling speed, ventilation conditions, equipment operating status, and dust source intensity, the original dust control parameter configuration is difficult to adapt to the actual working conditions in the long term. If the spray particle size, spray coverage layout, and airflow ejection intensity are not adjusted in time, it can easily lead to a decrease in dust suppression efficiency, a rebound in dust concentration, increased airflow disturbance, and even the safety hazard of local dust accumulation. Through this step, the periodic monitoring data can comprehensively reflect the current airflow status, water mist distribution, and dust dynamics of the working face. Based on this dynamic data, the parameter self-correction algorithm continuously trains and updates the coupled model, accurately identifies deficiencies and potential deviations in the dust suppression effect, and automatically calculates and pushes the optimal parameter adjustment scheme. This mechanism not only enables dynamic adaptive adjustment of control parameters but also continuously iterates and optimizes dust suppression strategies, giving the system the self-learning and evolutionary capabilities for long-term stable operation. Therefore, the dust suppression system can maintain optimal dust control at different tunneling stages, under different ventilation modes, and even in cases of sudden dust exceedances, balancing dust suppression effectiveness, energy consumption, and environmental safety, thus achieving intelligent, dynamic, and precise control of dust management at the tunneling face.

[0051] The aforementioned dual-ejector dust suppression linkage control method based on dust monitoring enables dynamic and precise regulation and intelligent optimization of dust control at coal mine tunneling faces, significantly improving the adaptability, responsiveness, and control effectiveness of the dust suppression system. This method constructs a dynamic mapping model between the airflow disturbance zone and the high-dust-occurrence zone, scientifically setting the water mist particle size and spray strategy to ensure optimal settling inertia and coverage under different wind speeds and airflow energies. The construction of multi-level adjustable spraying and gradient fog fields effectively enhances the directional retention of water mist and its dust source coverage in complex airflow environments. The introduction of wind-mist guiding and slow-release flow zone design stabilizes the spatial distribution of dust suppression, suppressing water mist particle shift and dust re-diffusion. Combined with a three-field linkage model and parameter self-correction algorithm, dynamic adaptive optimization of spray and ejector parameters is achieved, ensuring the dust suppression system remains in optimal control under different tunneling stages and ventilation conditions, avoiding safety hazards such as dust clouds, equipment mud formation, and monitoring distortion. Overall, the solution effectively solves the problem of incoordination between spray and ejector ventilation, improves dust collection and settling efficiency, reduces energy consumption and human intervention burden, and comprehensively ensures the safety, stability and green sustainability of the working environment in coal mine tunneling faces.

[0052] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0053] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely to distinguish one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0054] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0055] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0056] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0057] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0058] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0059] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0060] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for joint control of dust suppression using dual-jet ventilation based on dust monitoring in fully mechanized coal mine tunneling faces, characterized in that... Includes the following steps: S1. Based on the spatial layout of the tunneling face and the dust diffusion trend, a dynamic mapping model of the airflow disturbance zone and the dust high-incidence zone is constructed. The settling inertia threshold required for water mist particle settling under different wind speed conditions is extracted, and the initial parameters of water mist particle size and spray strategy are set. S2, based on the settling inertia threshold, adjust the atomization structure and mist output parameters of the spray device to achieve multi-level adjustable water mist particle size, and configure differentiated spray devices at the airflow disturbance boundary to form a gradient fog field and improve the directional retention performance of water mist; S3, based on gradient fog field, sets up wind and fog guiding structure unit, and forms slow release flow zone in dust source area through weak wind control mechanism, enhances the suspension coverage time of water mist particles, and stabilizes the spatial distribution of dust. S4. Deploy micro-environmental detection units in the slow-release flow zone to collect dust concentration, wind speed vector and water mist density data, establish a three-field linkage model of wind flow field, water mist field and dust field, and evaluate the local adaptability and disturbance suppression effect of the dust suppression system. S5, based on the response index of the three-field linkage model, dynamically adjusts the spray volume and the ejector wind speed of the dual ejector device to maintain the coordinated change of water mist particle size and airflow energy, forming a coupled response mechanism of wind control and dust suppression, so as to achieve precise water mist coverage, stable airflow guidance and minimize dust disturbance. S6, based on the coupled response mechanism of wind control and dust suppression, combined with periodically collected multi-source monitoring data, applies a parameter self-correction algorithm to continuously optimize water mist particle size, spray device layout and ejection intensity, and establishes a full-cycle intelligent control and strategy iteration mechanism to dynamically maintain the optimal level of dust reduction efficiency and working environment safety.

2. The method for joint control of dust suppression based on dust monitoring in fully mechanized coal mine tunneling faces according to claim 1, characterized in that, Step S1 includes: Based on the three-dimensional spatial model of the tunneling face, computational fluid dynamics simulation method is used to simulate the airflow field and dust diffusion path under different tunneling stages, ventilation configurations and wind speeds, and to identify airflow disturbance zones and dust high-incidence zones. The Lagrange particle tracking method was used to calculate the motion trajectory and sedimentation process of water mist particles of different sizes in the wind-induced disturbance zone, and the minimum sedimentation inertia threshold required for the sedimentation of water mist particles was extracted. Based on the settling inertia threshold, the water mist particle size, spray pressure, nozzle orifice diameter, spray angle, and spray speed are set to form a spray strategy initialization parameter set; The water mist particle size and spray strategy initialization parameters are integrated into the dust suppression control command system, and the spray parameters are dynamically adjusted based on real-time monitoring signals.

3. The method for joint control of dust suppression based on dust monitoring in fully mechanized coal mine tunneling faces according to claim 1, characterized in that, Step S2 includes: Based on the settling inertia threshold required for water mist particles to settle in the dust source area, the water mist particle size distribution range is determined and multi-level particle size ranges are divided. By adjusting the nozzle diameter, number of nozzles, spray angle, and the multi-stage compression structure of the internal atomization chamber of the spray device, multi-stage adjustable control of water mist particle size can be achieved. Differentiated spray devices are configured at the wind disturbance boundary based on wind speed and dust characteristics to form a spatially continuous gradient fog field; Based on real-time monitoring of wind speed, wind pressure, and dust concentration data, the spray pressure, spray flow rate, and spray angle are dynamically adjusted to achieve directional retention of water mist in different airflow energy zones.

4. The method for joint control of dust suppression based on dust monitoring in a fully mechanized coal mine tunneling face according to claim 1, characterized in that, Step S3 includes: A wind and mist guiding structure unit consisting of multi-plate guide vanes, annular diverter tubes and lateral flow restrictors is set up in front of and on both sides of the dust source to form a buffer zone where the airflow energy is controlled to be below 3 meters per second. Within the buffer zone, a miniature low-speed air supply device is used to control the air outlet speed to 0.5 to 1.5 meters per second, creating a local wind direction disturbance that is opposite to or perpendicular to the main airflow, thus establishing a slow-release flow zone. Directional spraying devices with a particle size of 20 to 30 micrometers are arranged above and to the side of the dust source area to form a three-dimensional dust-falling mist layer covering the dust source. Based on real-time monitoring of dust concentration, wind speed and water mist density, the air supply rate and spray flow rate are dynamically adjusted to achieve continuous and stable optimization of the slow-release flow zone.

5. The method for joint control of dust suppression based on dust monitoring in a fully mechanized coal mine tunneling face according to claim 1, characterized in that, Step S4 includes: Miniature environmental detection units integrating high-precision laser dust concentration sensors, three-dimensional ultrasonic wind speed sensors, and light scattering water mist density sensors are deployed in the upstream, middle, and downstream areas of the slow-release flow zone. Dynamic data of dust concentration, wind speed vector and water mist density were collected. Based on mathematical modeling and numerical analysis, a three-field linkage model of wind flow field, water mist field and dust field was established. Based on the three-field linkage model and combined with real-time data feedback, the local adaptability of the dust suppression system and its effect on suppressing airflow disturbance are evaluated, and intervention signals are output. Based on long-term monitoring data, the parameters and structure of the three-field linkage model are periodically adaptively corrected and upgraded.

6. The method for joint control of dust suppression based on dust monitoring in a fully mechanized coal mine tunneling face according to claim 1, characterized in that, Step S5 includes: Based on the response index output by the three-field linkage model of airflow field, water mist field and dust field, the spray volume and spray pressure are dynamically adjusted to generate water mist particle size that matches the airflow intensity. Based on the real-time changes in the airflow field, the ejector velocity, inlet airflow, and throttling ratio of the ejector channel of the dual ejector device are adjusted synchronously to control the airflow guiding capability. The adjustment parameters of spray volume and ejector wind speed, along with dust changes and airflow conditions, are fed back to the three-field linkage model to continuously optimize the model's prediction and control accuracy, thereby realizing a coupled response mechanism for wind control and dust suppression.

7. The method for joint control of dust suppression based on dust monitoring in a fully mechanized coal mine tunneling face according to claim 1, characterized in that, Step S6 includes: Based on periodically collected multi-source monitoring data such as dust concentration, wind speed and direction, water mist density, water mist particle size and ejector wind speed, a parameter self-correction algorithm is applied to establish a coupling relationship model between the airflow field, water mist field and dust field. Based on the model evaluation results, the optimal adjustment parameters for water mist particle size, spray device arrangement, and ejection intensity of the dual ejector device are dynamically calculated; Based on the optimal adjustment parameters, adjust the nozzle diameter, spray angle, spray pressure, and spray flow rate of the spray device, as well as the ejector wind speed, airflow rate, and throttling ratio of the dual ejector device; The optimization results are fed back to the three-field linkage model of airflow field, water mist field and dust field to update the model parameters and control strategy library, so as to realize full-cycle intelligent regulation and strategy iteration.

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