A dynamic diffusion simulation system for rock cutting dust

Abstract

This application proposes a dynamic diffusion simulation system for rock cutting dust, and constructs a dynamic diffusion simulation system for rock cutting dust that includes a rock cutting and fragmentation module, a particle separation module, a dust diffusion module, a dust data acquisition module, and a data processing module. It can realize the dynamic simulation and real-time monitoring of the dust diffusion process, and then accurately evaluate the dust pollution situation and formulate effective control strategies to achieve the active regulation of dust diffusion.

Description

Technical Field

[0001] This application relates to the technical field of mine engineering, and particularly to a dynamic diffusion simulation system for rock cutting dust. Background Art

[0002] In rock cutting operations such as mine exploitation and tunnel excavation, the generation of dust is inevitable. Dust not only pollutes the working environment but also may pose serious hazards to the health of operators.

[0003] Most of the existing dust monitoring technologies rely on single dust concentration measurement, lacking dynamic simulation and real-time monitoring of the dust diffusion process, making it difficult to accurately evaluate the dust pollution situation and formulate effective control strategies. In addition, traditional dust monitoring systems are usually passive and cannot achieve active regulation of dust diffusion. Summary of the Invention

[0004] This application proposes a dynamic diffusion simulation system for rock cutting dust, which can solve one of the problems existing in the background art.

[0005] To achieve the above object, this application adopts the following technical solutions:

[0006] This application provides a dynamic diffusion simulation system for rock cutting dust, and the simulation system includes:

[0007] A cutting rock-breaking module for simulating the rock cutting process that generates dust;

[0008] A particle separation module disposed at the rear end of the cutting rock-breaking module for separating dust and impurities;

[0009] A dust diffusion module disposed at the rear end of the cutting rock-breaking module for dynamically diffusing the separated dust;

[0010] A dust data acquisition module disposed on one side of the dust diffusion module for real-time monitoring of the dust in the dust diffusion module to obtain real-time dust monitoring data; and

[0011] A data processing module electrically connected to the dust data acquisition module for analyzing and processing the real-time dust monitoring data.

[0012] Based on the above technical solutions, a dynamic diffusion simulation system for rock cutting dust including a cutting rock-breaking module, a particle separation module, a dust diffusion module, a dust data acquisition module, and a data processing module is constructed, which can achieve dynamic simulation and real-time monitoring of the dust diffusion process, and further can accurately evaluate the dust pollution situation and formulate effective control strategies to achieve active regulation of dust diffusion.

[0013] In a possible design method, the real-time dust monitoring data is a real-time dust diffusion image, and the data processing module is specifically configured to:

[0014] Perform grayscale conversion and binarization on the real-time dust diffusion image in sequence to obtain a binarized grayscale image;

[0015] Use an image processing algorithm to extract the real-time image feature values of the binarized grayscale image;

[0016] Based on the established first mapping relationship between the image feature values and the concentration values, obtain the real-time concentration value corresponding to the real-time image feature values; and

[0017] Based on the established second mapping relationship between the real-time concentration values and the adjustment amount of the cutting parameters of the cutting rock-breaking module, obtain the real-time adjustment amount of the cutting parameters,

[0018] The simulation system further includes:

[0019] A control module, electrically connected to the data processing module, for using the real-time adjustment amount of the cutting parameters to control the cutting rock-breaking module to adjust the cutting parameters.

[0020] In a possible design method, the first mapping relationship is specifically: ; where is the real-time concentration value, , is the proportional coefficient, b is the constant term, is the image feature value, i and j are the position markers of the image pixels; the cutting parameters include the cutting speed and the angle, and the second mapping relationship is specifically: ; where is the adjustment amount of the cutting speed or the adjustment amount of the cutting angle ; is the preset safety threshold; is the concentration deviation value, indicating the difference between the concentration value and the safety threshold; is the proportional coefficient, used to adjust the response speed and sensitivity of the system; is the integral coefficient, used to eliminate the steady-state error and ensure the stability of the system during long-term operation; is the differential coefficient, used to predict the future trend of the system and improve the stability of the control.

[0021] In a possible design method, the real-time dust monitoring data includes: the average dust concentration measured by the measuring instrument with time synchronization and the real-time dust diffusion image, and the data processing module is specifically further configured to:

[0022] Adjust the parameter values in the first mapping relationship by using the comparison result between the average dust concentration measured by the measuring instrument and the real-time concentration value.

[0023] In a possible design, the data processing module is further specifically configured to:

[0024] Extract the particle characteristics of the real-time dust diffusion image to obtain the spatio-temporal distribution characteristics of dust diffusion; and

[0025] Establish a dust diffusion model based on the spatio-temporal distribution characteristics by using numerical simulation methods.

[0026] In a possible design, the rock cutting and breaking module includes: a rock-breaking pick with adjustable angle for simulating different cutting conditions; a specimen clamping device located below the rock-breaking pick for fixing the specimen to be tested; an adjustable-speed fan arranged on the side of the rock-breaking pick for guiding the dust flow; a contraction-type channel facing the adjustable-speed fan for guiding the dust to the particle separation module; and a transparent baffle covering the rock-breaking area to prevent dust spillage.

[0027] In a possible design, the cutting angle of the rock-breaking pick can be adjusted according to specific conditions to simulate different cutting conditions; the wind speed of the adjustable-speed fan is controlled by an adjustment knob to adapt to different dust diffusion requirements.

[0028] In a possible design, the particle separation module includes: a cyclone separator that separates dust and impurities by centrifugal force and transports the dust sample to the dust diffusion module.

[0029] In a possible design, the dust diffusion module includes: a dust generation device connected to the cyclone separator, with a feeding tray and a conveyor belt inside for transporting the dust sample; a cylindrical air duct with contraction cross-sections at the front and rear ends, and a suction fan connected to the end for forming a negative pressure to diffuse the dust; a transparent observation window arranged in the second half of the air duct for observing the dynamic characteristics of the dust in real time; and a dust flow treatment box located at the end of the air duct, and the dust-containing air enters the dust flow treatment box after passing through the air duct.

[0030] In a possible design, the dust data acquisition module includes: a dust concentration meter for measuring the average dust concentration; and a dust image acquisition device for acquiring the real-time dust diffusion image through the transparent observation window. Description of the Drawings

[0031] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of related technologies. Obviously, the drawings in the following description are only some embodiments of the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0032] Figure 1 It is a schematic diagram of a dynamic diffusion simulation system for rock cutting dust provided by an embodiment of the present application, showing the layout of the rock cutting and breaking module, the particle separation module, the dust diffusion module, and the dust image acquisition module.

[0033] Figure 2 It is a schematic diagram of the rock cutting and breaking module provided by an embodiment of the present application, showing the layout of the rock cutting pick, the specimen clamping device, the adjustable-speed fan, the constricted channel, and the transparent baffle.

[0034] Figure 3 It is a schematic diagram of the particle separation module provided by an embodiment of the present application, showing the structure of the cyclone separator and its connection to the dust diffusion module.

[0035] Figure 4 It is a schematic diagram of the dust generation module provided by an embodiment of the present application, showing the layout of the conveyor belt, the feeding disk, and the dust diffusion chamber in the dust generation device.

[0036] Figure 5 It is a schematic diagram of the dust diffusion module (main body) provided by an embodiment of the present application, showing the layout of the air duct, the transparent observation window, and the exhaust fan.

[0037] Figure 6 It is a schematic diagram of the dust diffusion module (fan part) provided by an embodiment of the present application, showing the connection mode between the exhaust fan and the air duct.

[0038] Figure 7 It is a schematic diagram of the dust image acquisition and processing module (data collection part) provided by an embodiment of the present application, showing the layout of the dust concentration meter and the image acquisition device.

[0039] Figure 8 It is a schematic diagram of the dust image acquisition and processing module (data processing part) provided by an embodiment of the present application, showing the layout of the dust image data processing device.

[0040] Figure 9 It is a flowchart of the operation of the feedback adjustment system provided by an embodiment of the present application.

[0041] Figure 10 It is a flowchart of the implementation steps of a method for real-time environmental monitoring of dynamic diffusion of rock cutting dust provided by an embodiment of the present application.

[0042] Description of the reference numerals in the drawings:

[0043] 1. Rock cutting module; 2. Particle separation module; 3. Dust diffusion module; 4. Dust image acquisition and processing module; 5. Rock cutting pick; 6. Specimen clamping device; 7. Variable-speed blower; 8. Contracting channel; 9. Transparent baffle; 10. Adjusting knob; 11. Cyclone separator; 12. Upper outlet; 13. Lower outlet; 14. Dust generating device; 14-1. Conveyor belt; 14-2. Feeding tray; 14-3. Dust outlet chamber; 15. Stirring rod; 16. Dust diffusion chamber; 17. Air duct; 18. Air duct inlet; 19. Air duct outlet; 20. Transparent observation window; 21. Exhaust fan; 22. Dust flow treatment box; 23. Dust image acquisition device; 24. Supplementary light; 25. Image processing system. Detailed implementation manners

[0044] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] It should be noted that although the functional modules are divided in the device schematic diagram and the logical sequence is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order from the module division in the device or the sequence in the flowchart. Terms such as "first" and "second" in the description, claims and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0047] As Figure 1 shown, the embodiments of the present application provide a Figure 1 As shown, the embodiments of the present invention provide a gravel online scanning and automatic lump size analysis system, including: a rock cutting module 1, a particle separation module 2, a dust diffusion module 3, and a dust image acquisition and processing module 4. Among them, the rock cutting module 1 is mainly used to simulate the rock cutting process and generate dust; the particle separation module 2 is connected to the rock cutting module 1 and is used to separate dust and impurities; the main function of the dust diffusion module 3 is to be connected to the particle separation module 2 and is used to dynamically diffuse dust; the main function of the dust image acquisition and processing module 4 is to analyze the dust pollution situation during the rock cutting process by monitoring and processing the dust data in the dust diffusion module 3 in real time.

[0048] In this embodiment, as Figure 2 shown, the rock cutting and breaking module includes: a rock-breaking pick 5 with adjustable angle, used to simulate different cutting conditions; a specimen clamping device 6, located below the rock-breaking pick 5, used to fix the specimen to be tested; an adjustable-speed blower 7, arranged on the side of the rock-breaking pick 5, used to guide the flow of dust; a contraction-type channel 8, facing the adjustable-speed blower 7, used to direct the dust to the particle separation module 2; and a transparent baffle 9, covering the rock-breaking area to prevent dust from overflowing.

[0049] During the working process, the cutting angle of the rock-breaking pick 5 can be adjusted according to specific conditions to simulate different cutting conditions; the wind speed of the adjustable-speed blower 7 is controlled by an adjustment knob 10 to adapt to different dust diffusion requirements.

[0050] In this embodiment, as Figure 3 shown, the particle separation module includes: a cyclone separator 11, which separates dust and impurities by centrifugal force and transports the dust sample to the dust diffusion module.

[0051] During the working process, the cyclone separator 11 discharges the particle impurities from the upper outlet 12 by centrifugal force, and transports the separated dust sample from the lower outlet 13 to the dust generating device 14. The dust generating device is as Figure 4 shown.

[0052] In this embodiment, as Figure 5 、 Figure 6 shown, the dust diffusion module 3 includes: a dust generating device, connected to the cyclone separator 11, internally provided with a conveyor belt 14-1 and a feeding tray 14-2 to transport the dust sample to the dust outlet chamber 14-3, and the dust is stirred by a stirring rod 15 during the falling process; a wind tunnel 17, which is a cylindrical structure, with a contracted cross-section at the front and rear ends, and the end is connected to an exhaust fan 21, used to form a negative pressure to diffuse the dust; a transparent observation window 20, arranged in the second half of the wind tunnel 17, used to observe the dynamic characteristics of the dust in real time; a dust flow treatment box 22 is located at the end of the wind tunnel, and the dust-containing air flow enters the dust flow treatment box after passing through the wind tunnel. The box is internally provided with a high-efficiency filter screen to filter the particles in the dust-containing air flow. During the filtering process, the air flow and the dust particles are effectively separated, the purified air flow is directly discharged into the atmosphere, and the separated and precipitated dust particles are centrally collected for subsequent recycling and utilization.

[0053] During the working process, the conveyor belt 14-1 of the dust generating device is linked with the feeding tray 14-2 to evenly transport the dust sample obtained from the cyclone separator 11 to the wind tunnel inlet 18, and realize the dynamic diffusion of the dust through the negative pressure environment of the wind tunnel 17.

[0054] In this embodiment, as Figure 7As shown in the figure, the dust image acquisition and processing module includes: a dust concentration meter for measuring the dust concentration; a dust image acquisition device 23 for acquiring the dust diffusion image in real time through a transparent observation window 20; and an image processing system 25 communicatively connected to the dust concentration meter for synchronously analyzing the image data and the concentration data and generating a comprehensive pollution amount assessment report by combining numerical simulation methods, such as Figure 10 shown.

[0055] During the working process, the working flow of the dust image acquisition and processing module includes: a data acquisition layer that acquires the dynamic image of dust diffusion in real time through the transparent observation window 20 and synchronously obtains the data of the dust concentration meter (which can be called the average dust concentration), and transmits the two types of data (image data and concentration data) formed to the image processing system 25 to form a multi-dimensional data set to ensure the real-time and consistency of the data source; a data processing layer: the image processing system 25 analyzes the spatio-temporal distribution characteristics of dust diffusion by extracting particle features, combines the numerical values of the dust concentration meter, and establishes a dust diffusion model. At the same time, the system uses numerical simulation methods (CFD simulation) to verify the measured data and dynamically correct the model parameters to improve the accuracy of pollution amount assessment; a feedback control layer, such as Figure 8 shown: The analysis result is fed back to the system control unit in real time, and the cutting speed and cutting angle of the rock-breaking pick 5 are adjusted according to the dust concentration exceeding threshold value to control the generation and diffusion state of dust.

[0056] During the working process, a numerical simulation method is used to establish a dust diffusion model through ANSYS Fluent. By calculating the grid division and defining the flow field boundary conditions such as wind speed, pressure, and temperature, the motion trajectory of dust particles is simulated by combining the Euler-Lagrange model. The turbulence model can be used to improve the simulation accuracy, and the error analysis and correction are carried out on the CFD results by using the experimentally measured dust concentration data to ensure the consistency between the simulation results and the actual measurement data.

[0057] During the working process, the dust image acquisition and processing module can achieve: dynamic closed-loop control, through the closed-loop process of real-time data acquisition → analysis → feedback, breaking through the passivity of traditional dust monitoring and realizing active regulation; multi-modal data fusion, combining image (qualitative) and concentration meter (quantitative) data to improve the accuracy of pollution amount assessment and avoid the limitations of single measurement means. The cutting parameter optimization unit establishes a dust concentration-cutting parameter mapping model and dynamically calculates the adjustment amount of the cutting speed and cutting angle of the rock-breaking pick through the PID algorithm.

[0058] Based on the same inventive concept, this embodiment also provides a method for real-time environmental monitoring of the dynamic diffusion of rock cutting dust. The flowchart is as Figure 9 shown, including the following steps:

[0059] Based on the preset fan speed v and the working parameters of the rock cutting device (cutting speed , cutting angle ), image, acquisition device parameters (shutter , , focal length f), and light source parameters (light intensity L, light color λ) to collect images of the dust diffusion process; perform grayscale and binary processing on the obtained dust images, and extract image feature values through image processing algorithms , establish image feature values and dust concentration (which can be called the real-time concentration value, different from the above average concentration) to establish a quantitative equation: ; where , is the proportional coefficient, b is the constant term, determined by experimental calibration; is the image feature value of the dust image. Specifically, standard dust samples with different concentrations are selected, and under constant light conditions, the image feature values are calculated through image processing algorithms. The calibration experimental data are obtained from a dust meter, which can cover different dust particle sizes and concentration ranges to ensure that the model is applicable to the actual monitoring environment. Finally, the dust diffusion state is analyzed in real time in combination with the quantitative equation, and dynamic monitoring data are output to optimize the dust control strategy.

[0060] In addition, the system sets the dynamic adjustment trigger threshold to 5% of the deviation between the real-time concentration and the predicted concentration. By synchronously analyzing the average concentration and the real-time concentration based on the current parameters, the deviation is calculated and the absolute value and change trend are statistically analyzed. When the monitoring data exceed the preset threshold for 3 consecutive times, the parameter update mechanism is triggered: 1. Data screening, using the sliding window method to extract the latest 50 groups of synchronous data to ensure the timeliness and stability of the fitting samples; 2. Parameter refitting, optimizing the objective function based on the least squares method to solve the optimal k and b; 3. Threshold warning linkage, adding a deviation trend warning module, when the concentration change rate is abnormal or approaching the threshold, triggering parameter adjustment or control intervention in advance to achieve a rapid response to scenarios such as sudden increase in dust and sudden change in particle characteristics. Through the above mechanism, the gray-scale-concentration mapping relationship is dynamically corrected, significantly improving the accuracy and reliability of the quantitative equation, and breaking through the limitations of traditional static calibration models that rely on fixed experimental conditions and cannot adapt to complex working conditions.

[0061] Based on the mapping relationship between the dust concentration and the cutting parameters, that is, the cutting speed of the rock-breaking pick and the cutting angle , the adjustment amounts , of the cutting speed and angle are dynamically calculated through the PID algorithm ; is the adjustment amount of the cutting speed or the adjustment amount of the cutting angle ; is the concentration deviation value, representing the difference between the actual dust concentration and the safety threshold; is the dust concentration monitored in real time; is the preset safety threshold; is the proportionality coefficient, used to adjust the response speed and sensitivity of the system; is the integral coefficient, used to eliminate the steady-state error and ensure the stability of the system during long-term operation; is the differential coefficient, used to predict the future trend of the system and improve the stability of control.

[0062] Through the above formula, the system can calculate the cutting speed and the preset threshold based on the dust concentration monitored in real time and the cutting angle of the adjustment amount and .

[0063] Based on this PID algorithm, the execution module of the feedback control runs. This execution module actually adjusts the cutting speed and angle of the rock-breaking pick according to the adjustment amount and calculated by the cutting parameter optimization unit. The specific implementation method is: by changing the flow rate or pressure of the hydraulic oil to control the hydraulic drive system, the dynamic adjustment of the cutting speed is realized; by the electric or hydraulic drive mechanism, the cutting angle is adjusted to achieve the precise control of the cutting angle .

[0064] In this embodiment, at the data acquisition layer, the system uses a dust concentration meter and an image acquisition device to obtain the current dust concentration value, and calculates the average dust concentration within 5 seconds to smooth the data fluctuation. The data processing layer sets the dust concentration threshold (such as 100 mg / cubic meter), calculates the dust concentration change rate to judge the trend, and combines the CFD simulation model to predict the dust diffusion situation in the next 10 seconds. At the feedback control layer, the PID control strategy is adopted: when the dust concentration exceeds the threshold and the change rate shows an upward trend, the system will reduce the cutting speed (step size 10%) and decrease the cutting angle (step size 2°); when the dust concentration is lower than the threshold and the change rate shows a downward trend, the system will gradually restore the cutting speed (step size 5%) and the cutting angle (step size 1°).

[0065] The above is the preferred implementation manner of this application. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and refinements can still be made, and these improvements and refinements are also regarded as the protection scope of this application.

Claims

1. A dynamic diffusion simulation system for rock cutting dust, characterized in that, The simulation system includes a rock cutting module for generating dust, a particle separation module, a dust diffusion module, a dust data acquisition module, and a data processing module; The rock cutting module is used to simulate the rock cutting process that generates dust; The particle separation module is arranged at the rear end of the rock cutting module and is used to separate dust and impurities; the dust diffusion module is arranged at the rear end of the rock cutting module and is used to dynamically diffuse the separated dust; the dust data acquisition module is arranged on one side of the dust diffusion module and is used to monitor the dust in the dust diffusion module in real time to obtain real-time dust monitoring data; And the data processing module is electrically connected to the dust data acquisition module and is used to analyze and process the real-time dust monitoring data; The real-time dust monitoring data is a real-time dust diffusion image; The data processing module is specifically used for: performing grayscale conversion and binarization on the real-time dust diffusion image in sequence to obtain a binarized grayscale image; using an image processing algorithm to extract the real-time image feature values of the binarized grayscale image; Based on the established first mapping relationship between the image feature values and the concentration values, obtaining the real-time concentration value corresponding to the real-time image feature values; and based on the established second mapping relationship between the real-time concentration values and the adjustment amount of the cutting parameters of the rock cutting module, obtaining the real-time adjustment amount of the cutting parameters; The simulation system further includes a control module. The control module is electrically connected to the data processing module and is used to use the real-time adjustment amount of the cutting parameters to control the adjustment of the cutting parameters of the rock cutting module; The specific first mapping relationship is as follows: ; where is the real-time concentration value, , is the proportionality coefficient, b is the constant term, is the image feature value, and i and j are the position markers of the image pixels; The cutting parameters include cutting speed and angle; The specific second mapping relationship is as follows: ; where is the adjustment amount of the cutting speed or the adjustment amount of the cutting angle ; is the preset safety threshold; is the concentration deviation value, representing the difference between the concentration value and the safety threshold; is the proportionality coefficient, used to adjust the response speed and sensitivity of the system; is the integral coefficient, used to eliminate the steady-state error and ensure the stability of the system during long-term operation; is the differential coefficient, used to predict the future trend of the system and improve the stability of control.

2. The analog system according to claim 1, wherein The real-time dust monitoring data includes the dust average concentration and the real-time dust diffusion image synchronized in time; the data processing module is specifically further used to adjust the parameter values in the first mapping relationship according to the comparison result between the dust average concentration and the real-time concentration value.

3. The analog system according to claim 1, wherein The data processing module is specifically further used to extract the particle characteristics of the real-time dust diffusion image to obtain the spatio-temporal distribution characteristics of dust diffusion; and use a numerical simulation method to establish a dust diffusion model based on the spatio-temporal distribution characteristics.

4. The analog system according to claim 1, characterized in that, The rock cutting module includes a rock cutting pick with adjustable angle, a specimen clamping device, a variable-speed fan, a constricted channel, and a transparent baffle; the rock cutting pick with adjustable angle is used to simulate different cutting conditions; the specimen clamping device is located below the rock cutting pick and is used to fix the specimen to be tested; the variable-speed fan is arranged on the side of the rock cutting pick and is used to guide the flow of dust; The constricted channel faces the variable-speed fan and is used to direct the dust to the particle separation module; and the transparent baffle covers the rock cutting area to prevent dust from spilling out.

5. The analog system according to claim 4, wherein The cutting angle of the rock cutting pick is adjusted according to specific conditions to simulate different cutting conditions; the wind speed of the variable-speed fan is controlled by an adjustment knob to adapt to different dust diffusion requirements.

6. The analog system according to claim 1, wherein The particle separation module includes a cyclone separator. The cyclone separator separates dust and impurities by centrifugal force and conveys the dust sample to the dust diffusion module.

7. The analog system according to claim 1, wherein The dust diffusion module includes a dust generating device, a cylindrical air duct, a transparent observation window, and a dust flow treatment box; the dust generating device is connected to the cyclone separator and is internally provided with a feeding disk and a conveyor belt for transporting dust samples; the cylindrical air duct has a contracted cross-section at the front and rear ends, and a suction fan is connected to the end for forming a negative pressure to diffuse dust; the transparent observation window is arranged in the second half of the air duct for observing the dynamic characteristics of dust in real time; and the dust flow treatment box is located at the end of the air duct, and the dust-containing air flow enters the dust flow treatment box after passing through the air duct.

8. The analog system according to claim 2, wherein The dust data acquisition module includes a dust concentration meter and a dust image acquisition device; the dust concentration meter is used to measure the average dust concentration; the dust image acquisition device is used to collect the real-time dust diffusion images through the transparent observation window.

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