Dust falling device and dust falling method based on machine vision

Abstract

The invention relates to the technical field of tunnel construction, in particular to a dust falling device and method based on machine vision, and the dust falling device comprises a surrounding rock structural surface intelligent recognition device, an anchoring assembly, a sliding rail assembly, an atomization assembly, a vision device, a dust concentration instrument, a four-in-one gas monitor, a phase Doppler particle analyzer and a control device. The anchoring assembly is detachably installed on the top wall of a tunnel, the sliding rail assembly is connected to the anchoring assembly, the sliding rail assembly is arranged in the axial direction of the tunnel, the atomization assembly is connected to the sliding rail assembly, the atomization assembly is connected to the sliding rail assembly, and the atomization assembly is connected to a tunnel water pipe. The intelligent recognition equipment for the surrounding rock structural plane is mounted at a position close to a tunnel face in a tunnel. The technical problems that in the prior art, tunnel blasting and dust falling equipment always operates independently, and effective coordination and intelligent control are lacked are solved.

Description

Technical Field

[0001] This invention relates to the field of tunnel engineering technology, specifically to a dust suppression device and method based on machine vision. Background Technology

[0002] Blasting operations during tunnel construction generate large amounts of dust and harmful gases, posing a threat to the health of construction workers and polluting the surrounding environment. Furthermore, accurately controlling the blasting process to minimize damage to the surrounding rock structure is a key technical challenge in tunnel construction. Traditional tunnel blasting and dust suppression equipment often operate independently, lacking effective coordination and intelligent control, resulting in low blasting efficiency and unsatisfactory dust suppression effects.

[0003] In conclusion, there is an urgent need for a dust suppression device that can coordinate tunnel blasting to solve the problems existing in the current technology. Summary of the Invention

[0004] The purpose of this invention is to provide a dust suppression device and method based on machine vision, in order to solve the technical problem that existing tunnel blasting and dust suppression equipment often operate independently, lacking effective coordination and intelligent control. The specific technical solution is as follows:

[0005] This invention provides a dust suppression device based on machine vision, including an intelligent identification device for surrounding rock structures, an anchoring assembly, a slide rail assembly, an atomizing assembly, a dust concentration meter, a four-in-one gas monitor, a phase Doppler particle analyzer, and a control device. The control device is connected to the intelligent identification device for surrounding rock structures, the slide rail assembly, the atomizing assembly, the dust concentration meter, the four-in-one gas monitor, and the phase Doppler particle analyzer. The anchoring assembly is detachably installed on the tunnel roof. The slide rail assembly is connected to the anchoring assembly and is arranged along the tunnel axis. The atomizing assembly is connected to the slide rail assembly and is connected to the tunnel water pipe. The intelligent identification device for surrounding rock structures is installed inside the tunnel near the tunnel face.

[0006] A further improvement of the dust suppression device based on machine vision in this invention is that the anchoring assembly includes two rows of anchor rods and two connecting rods. The anchor rods are detachably connected between the tunnel top wall and the connecting rods. The length direction of the connecting rods is arranged along the axial direction of the tunnel, and the two connecting rods are arranged side by side. Each row of anchor rods consists of at least two anchor rods, and the at least two anchor rods are arranged at intervals along the length direction of the connecting rods.

[0007] A further improvement of the dust suppression device based on machine vision in this invention is that the slide rail assembly includes a guide rail, a hanging member, and a pulley assembly. The hanging member is fixed to the top of the guide rail and is hung on the connecting rod. The pulley assembly is slidably mounted on the guide rail, and the atomizing component is connected to the pulley assembly.

[0008] A further improvement of the dust suppression device based on machine vision in this invention is that the atomizing component includes a dust suppression tube, a lifting rod, and multiple nozzles. The lifting rod is connected between the dust suppression tube and the pulley assembly, and the multiple nozzles are installed at intervals on the dust suppression tube, which is arc-shaped.

[0009] The present invention also includes a dust reduction method based on machine vision, which uses the dust reduction device based on machine vision as described above for dust reduction, and includes the following steps:

[0010] Step 1: Analyze the joint and fracture information of the working face using the intelligent identification device for surrounding rock structure, and classify the surrounding rock near the working face in combination with geological information;

[0011] Step 2: Using the joint and fissure characteristic parameters of the tunnel face and the geological information of the surrounding rock identified by the intelligent identification device for the surrounding rock structure, numerical simulation is performed, and the layout of blast holes and the amount of explosive charge are calculated.

[0012] Step 3: Adjust the starting position and initial water pressure of the atomizing component according to the surrounding rock grade and the amount of explosive.

[0013] Step 4: After the blasting is completed, the control equipment adjusts the position and atomization intensity of the atomizing components based on the concentration of blasting dust monitored by the dust concentration meter, the concentration of harmful gases monitored by the four-in-one gas monitor, and the propagation speed of blasting dust monitored by the phase Doppler particle analyzer.

[0014] A further improvement of the machine vision-based dust reduction method of this invention lies in the evaluation of the surrounding rock grade using the Q-value classification method:

[0015]

[0016] Where: RQD is the rock quality index, which judges the quality of the rock mass based on the integrity of the rock core during drilling. It is expressed as a percentage, using the ratio of the total length of solid and intact rock cores with a length of ≥10cm to the borehole length.

[0017]

[0018] Where: l i J represents the core length. n J represents the total number of joints; r J is the joint roughness coefficient; a J is the joint alteration coefficient; wSRF is the stress reduction factor;

[0019] Based on the Q value, the surrounding rock is divided into the following nine grades: Very poor (Q < 0.01); Extremely poor (0.01 ≤ Q < 0.1); Very poor (0.1 ≤ Q < 1); Poor (1 ≤ Q < 4); Medium (4 ≤ Q < 10); Good (10 ≤ Q < 40); Very good (40 ≤ Q < 100); Excellent (100 ≤ Q < 400); Very good (Q ≥ 400).

[0020] A further improvement of the dust suppression method based on machine vision in this invention is that, in step three, the starting position of the dust suppression device and the initial water pressure are adjusted based on the peak particle vibration velocity (PPV) during blasting. The higher the PPV, the greater the distance between the dust suppression device and the working face, and the higher the initial water pressure. The formula for calculating the PPV is as follows:

[0021]

[0022] Where: Q is the amount of explosive; R is the distance from the blast source; K is the d coefficient related to the terrain and geological conditions from the blast point to the monitoring point; and a is the attenuation index related to the terrain and geological conditions from the blast point to the monitoring point.

[0023] A further improvement of the machine vision-based dust reduction method of this invention lies in that, after monitoring the concentrations of explosive dust by a dust concentration meter and harmful gases by a four-in-one gas monitor, the on-site environmental classification index is calculated according to the following formula:

[0024]

[0025] Where: a is the volume content, b is the gas content; c is the noise level in decibels; T is the ambient temperature.

[0026] A further improvement of the machine vision-based dust suppression method of this invention lies in the fact that the propagation velocity of blasting dust monitored by the phase Doppler particle analyzer is obtained by the following formula:

[0027]

[0028] Where: f D V is the offset frequency obtained from the phase Doppler particle analyzer; q λ is the propagation velocity of the blasting dust; λ is the wavelength of the laser emitted by the phase Doppler particle analyzer; and θ is the angle between the line connecting the dust particle and the laser source and the direction of the dust velocity.

[0029] A further improvement of the machine vision-based dust reduction method of the present invention lies in the following expression for the amount of dust reduction per unit distance and unit time of droplets of the atomizing component when the atomization intensity of the atomizing component is controlled by the control device:

[0030] δ M =f(v,η) g ,C,A,q,S,V) / V 6);

[0031] Where: δ M η represents the dustfall rate per unit distance per unit time; f is the functional relationship; v is the relative velocity between the droplets and the dust; η g q represents the collection efficiency of a single droplet; C represents the dust concentration; A represents the cross-sectional area of ​​the collection zone; q represents the volumetric medium content; S represents the droplet cross-sectional area; and V represents the droplet volume in m³. 3 ;

[0032] The collection efficiency η of a single droplet g The following expression is used for calculation:

[0033]

[0034] Where: Stokes number s t The calculation expression is:

[0035]

[0036] Where: d p ρ represents the particle size of the blasting dust. p The density of the blasting dust; μ g D is the gas density. c denoted as droplet diameter.

[0037] The application of the technical solution of the present invention has the following beneficial effects:

[0038] This invention relates to a machine vision-based dust suppression device. By combining an intelligent rock structure surface recognition device with spray dust suppression, it solves the technical problem in existing technologies where tunnel blasting and dust suppression equipment often operate independently, lacking effective coordination and intelligent control. This invention utilizes the intelligent rock structure surface recognition device to identify characteristic parameters such as joints and fissures at the tunnel face, controlling the charge amount during blasting and thus adjusting the total spray pressure of the atomizing dust suppression equipment, reducing construction costs. After blasting, the control equipment monitors dust concentration using a dust concentration meter, a four-in-one gas monitor, and a phase Doppler particle analyzer. This invention addresses the concentration of blasting dust and harmful gases, as well as the propagation speed of the blasting dust. By adjusting the position of the atomizing dust suppression components, the position and angle of the nozzles, and the spraying speed of the atomizing medium, it achieves faster, more comprehensive dust suppression in a shorter time, effectively reducing the concentration of blasting dust in tunnels and improving the air quality of the tunnel construction environment. The invention is easy to implement, with a highly detachable, recyclable, and operable overall structure. It can quickly and comprehensively reduce the dust concentration in tunnels to the required level within a shorter time, solving the problems of long spray dust suppression time, low efficiency, and impact on construction progress.

[0039] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0040] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0041] Figure 1 This is a perspective view of the dust removal device based on machine vision according to the present invention;

[0042] Figure 2 This is a front view of the dust reduction device based on machine vision according to the present invention;

[0043] Figure 3 This is a front view of the slide rail assembly of the dust removal device based on machine vision according to the present invention;

[0044] Figure 4 This is a front view of the atomizing component of the dust suppression device based on machine vision according to the present invention;

[0045] Figure 5 This is a schematic diagram of the splicing pipe structure of the dust suppression device based on machine vision according to the present invention.

[0046] The components include: 1. Intelligent identification device for surrounding rock structure surface; 2. Slide rail assembly; 2.1. Anchoring assembly; 2.2. Guide rail; 3. Atomizing assembly; 3.1. Walking control system; 3.11. Pulley; 3.12. Telescopic rod; 3.2. Atomizing dust suppression assembly; 3.21. Splicing pipe; 3.22. Installation sleeve; 3.23. Nozzle; 3.24. External water pipe connector; 4. Dust concentration meter; 5. Four-in-one gas monitor; 6. Phase Doppler particle analyzer. Detailed Implementation

[0047] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered by the claims.

[0048] See Figures 1-5As shown, a dust suppression device based on machine vision includes an intelligent identification device for surrounding rock structures, an anchoring component 2.1, a slide rail component 2, an atomizing component 3, a dust concentration meter 4, a four-in-one gas monitor 5, a phase Doppler particle analyzer 6, and a control device. The control device is connected to the intelligent identification device for surrounding rock structures, the slide rail component 2, the atomizing component 3, the dust concentration meter 4, the four-in-one gas monitor 5, and the phase Doppler particle analyzer 6. The anchoring component 2.1 is detachably installed on the tunnel roof. The slide rail component 2 is connected to the anchoring component 2.1 and is arranged along the tunnel axis. The atomizing component 3 is connected to the slide rail component 2 and is connected to the tunnel water pipe. The intelligent identification device for surrounding rock structures is installed inside the tunnel near the tunnel face.

[0049] Specifically, the intelligent identification device 1 for surrounding rock structure faces mainly includes a high-speed camera and a deep learning network module. The intelligent identification device 1 for surrounding rock structure faces is based on Chinese patents CN117824599A and CN116295292A. The intelligent identification device 1 for surrounding rock structure faces is installed on the tunnel surface 3m-5m in front of the tunnel face to allow for direct and comprehensive observation of the rock mass structure at the tunnel face. A sliding rail system is installed along the tunnel length at the tunnel arch. The sliding rail body can slide continuously along the tunnel length by continuously moving forward through the anchoring device. The atomizing dust suppression equipment includes a walking control system 3.1 and an atomizing dust suppression component 3.2. The atomizing dust suppression component 3.2 is installed on the sliding rail system through the walking control system 3.1 and can slide along the tunnel length via pulleys 3.11 and move up and down via telescopic rods 3.12. Other components include a dust concentration meter 4, a four-in-one gas monitor 5, and a phase detector. The Doppler particle analyzer 6 is set up on the open ground in front of the tunnel face to monitor the concentration of blasting dust and harmful gases, as well as the propagation speed of the blasting dust. The slide rail system, walking control system 3.1, nozzle 3.23, dust concentration meter 4, four-in-one gas monitor 5, and phase Doppler particle analyzer 6 are all connected to the control equipment. After the blasting is completed, the control equipment adjusts the position of the atomizing dust suppression component 3.2 and the position and angle of the nozzle 3.23, as well as the spraying speed of the atomizing medium, based on the concentration and propagation speed of the blasting dust monitored by the dust concentration meter 4 and the phase Doppler particle analyzer 6, to better achieve rapid dust suppression in a short time and all directions.

[0050] Preferred, such as Figure 2 and Figure 3As shown, the anchoring assembly 2.1 includes two rows of anchor rods and two connecting rods. The anchor rods are detachably connected to the tunnel roof and the connecting rods. The length direction of the connecting rods is arranged along the tunnel axial direction, and the two connecting rods are arranged side by side. Each row of anchor rods consists of at least two anchor rods, and the at least two anchor rods are spaced apart along the length direction of the connecting rods. Specifically, the anchor rods can move forward continuously according to the progress of tunnel excavation and are detachably connected to the tunnel arch, thereby realizing the overall movement of the slide rail assembly 2 and improving the overall flexibility of the device.

[0051] Preferred, such as Figure 3 and Figure 4 As shown, the slide rail assembly 2 includes a guide rail 2.2, a hanging component, and a pulley assembly. The hanging component is fixed to the top of the guide rail 2.2 and is hung on the connecting rod. The pulley assembly is slidably mounted on the guide rail 2.2, and the atomizing component 3 is connected to the pulley assembly. Specifically, there are two sets of hanging components, each fixed to one side of the top of the guide rail 2.2. Each set includes at least two hanging members, which are spaced apart along the axial direction of the guide rail 2.2. Each hanging member is slidably hung on the connecting rod and located between two adjacent anchor rods. The sliding of the hanging members allows for changes in the position of the guide rail 2.2, further improving the flexibility of the atomizing component 3. The pulley assembly includes a rotating shaft and two rollers rotatably connected to the rotating shaft. The cross-section of the guide rail 2.2 is C-shaped with an opening facing downwards, and the two rollers are located on both sides of the guide wheel. Preferably, the slide rail assembly 2 further includes a travel control system 3.1, which is mounted on the rotating shaft. A drive motor is mounted on the pulley block, and the drive motor is connected to the travel control system 3.1. The travel control system 3.1 is connected to the control device.

[0052] Preferred, such as Figure 4 and Figure 5As shown, the atomizing component 3 includes a dust-suppressing pipe, a lifting rod, and multiple nozzles 3.23. The lifting rod connects the dust-suppressing pipe to the pulley system, and the multiple nozzles 3.23 are spaced apart on the dust-suppressing pipe, which is arc-shaped. Multiple atomizing components 3 are arranged at intervals along the tunnel axis. The end of the dust-suppressing pipe is equipped with an external water pipe connector 3.24 for connecting to the tunnel water pipe. The dust-suppressing pipe includes multiple splicing pipe sections 3.21, which are connected to adjacent sections using mounting sleeves 3.22. The splicing pipe sections 3.21 are connected to a rotating shaft via connecting rods. The nozzles 3.23 are mounted on the splicing pipe sections 3.21. The splicing pipe section 3.21 has a mother-daughter pipe structure, consisting of multiple daughter pipe sections and multiple mother pipe sections connected together, thus fulfilling the function of the dust-suppressing pipe's retractability. The splicing pipe section 3.21 is made of stainless steel. In this embodiment, the atomizing dust suppression component 3.2 includes nine media conveying pipes, eight mounting sleeves 3.22, nine nozzles 3.23, and an external water pipe connector 3.24 for connecting to the tunnel water pipe. The telescopic rod 3.12 is an electric telescopic rod 3.12, which enables the dust suppression pipe to move up and down. After dust suppression is completed in the area to be dusted, the construction personnel continue their work, disconnect the external water pipe connector 3.24 from the tunnel water pipe, and use the control equipment to control the slide rail assembly 2 to move the atomizing component 3 to the next working position. Then, they reconnect the external water pipe connector 3.24 to the tunnel water pipe for continuous operation.

[0053] The present invention also includes a dust reduction method based on machine vision, which uses the dust reduction device based on machine vision as described above for dust reduction, and includes the following steps:

[0054] Step 1: Analyze the joint and fracture information of the working face using the intelligent identification device 1 for surrounding rock structure, and classify the surrounding rock near the working face in combination with geological information;

[0055] Step 2: Using the joint and fissure characteristic parameters of the tunnel face and the geological information of the surrounding rock identified by the intelligent identification device 1 for surrounding rock structure, perform numerical simulation and calculate the layout of blast holes and the amount of explosives.

[0056] Step 3: Adjust the starting position and initial water pressure of atomizing component 3 according to the surrounding rock grade and the amount of explosives.

[0057] Step 4: After the blasting is completed, the control equipment adjusts the position and atomization intensity of the atomizing component 3 based on the concentration of blasting dust monitored by the dust concentration meter 4, the concentration of harmful gases monitored by the four-in-one gas monitor 5, and the propagation speed of blasting dust monitored by the phase Doppler particle analyzer 6.

[0058] Specifically, prior to step one, geological information of the tunnel face to be excavated is collected based on the geological survey results. A machine vision-based dust suppression device is installed inside the tunnel. The joint and fracture information of the tunnel face is analyzed by the high-speed camera and deep learning network of the intelligent rock structure surface recognition device 1. The characteristic parameters such as joints and fractures of the tunnel face and the geological information of the surrounding rock, identified by the intelligent rock structure surface recognition device 1, are used to perform numerical simulations using software such as ANSYS (Computer-Aided Engineering (CAE) software) to calculate the layout of blast holes and the amount of explosives. The position of the atomizing dust suppression component 3.2 and the position, angle, and spray speed of the atomizing medium can be dynamically adjusted by controlling the equipment to better achieve dust suppression.

[0059] Preferably, the surrounding rock grade is evaluated using the Q-value classification method:

[0060]

[0061] Where: RQD is the rock quality index, which judges the quality of the rock mass based on the integrity of the rock core during drilling. It is expressed as a percentage, using the ratio of the total length of solid and intact rock cores with a length of ≥10cm to the borehole length.

[0062]

[0063] Where: l i J represents the core length. n J represents the total number of joints; r J is the joint roughness coefficient; a J is the joint alteration coefficient; w SRF is the stress reduction factor;

[0064] Based on the Q value, the surrounding rock is divided into the following nine grades: Very poor (Q < 0.01); Extremely poor (0.01 ≤ Q < 0.1); Very poor (0.1 ≤ Q < 1); Poor (1 ≤ Q < 4); Medium (4 ≤ Q < 10); Good (10 ≤ Q < 40); Very good (40 ≤ Q < 100); Excellent (100 ≤ Q < 400); Very good (Q ≥ 400).

[0065] Preferably, in step three, the starting position of the dust suppression device and the initial water pressure are adjusted based on the peak particle vibration velocity (PPV) during blasting. The higher the PPV, the greater the distance between the dust suppression device and the working face, and the higher the initial water pressure. The formula for calculating the PPV is as follows:

[0066]

[0067] Where: PPV is measured in cm / s; Q is the explosive charge (kg), total charge for simultaneous blasting, and maximum charge for delayed blasting; R is the blast source distance, representing the distance (m) between the monitoring point and the blasting point; K and a are coefficients and attenuation indexes related to the terrain and geological conditions from the blasting point to the monitoring point, respectively; in the absence of experimental data for the initial blasting design, the values ​​of K and a can be selected with reference to the "Safety Regulations for Blasting" (GB6722-2014).

[0068] Refer to the paper "Blasting Control Parameters and Reliability Analysis Based on Rock Mass Quality". The formula for calculating the rock mass quality BQ can be approximated as: BQ = 0.6402Q + 514.158. The values ​​of K and a can be calculated inversely from the value of BQ: K = 4BQ -2.125 ×10 7 a = -0.0019BQ + 2.4277.

[0069] Preferably, after the concentrations of explosion dust monitored by the dust concentration meter 4 and harmful gases monitored by the four-in-one gas monitor 5 are obtained, the on-site environmental classification index is calculated according to the following formula:

[0070]

[0071] Where: a is the volume content, b is the gas content; c is the noise level in decibels; T is the ambient temperature.

[0072] Preferably, the phase Doppler particle analyzer 6 monitors the propagation velocity of blasting dust using the following formula:

[0073]

[0074] Where: f D V is the offset frequency obtained from the phase Doppler particle analyzer 6; q λ is the propagation velocity of the blasting dust; λ is the wavelength of the laser emitted by the phase Doppler particle analyzer 6; and θ is the angle between the line connecting the dust particles and the laser source and the direction of the dust velocity.

[0075] Preferably, when the atomization intensity of the atomizing component 3 is controlled by the control device, the dust settling amount of the droplets of the atomizing component 3 per unit distance and unit time is expressed by the following expression:

[0076] δ M =f(v,η) g ,C,A,q,S,V) / V 6);

[0077] Where: δ M η represents the dustfall rate per unit distance per unit time; f is the functional relationship; v is the relative velocity between the droplets and the dust; η gq represents the collection efficiency of a single droplet; C represents the dust concentration; A represents the cross-sectional area of ​​the collection zone; q represents the volumetric medium content; S represents the droplet cross-sectional area; and V represents the droplet volume in m³. 3 See the paper "Study on dust suppression performance of a new spray device during drilling and blasting construction in the metrotunnel," which shows that the variables in f are positively correlated with the amount of dust falling per unit distance per unit time.

[0078] The collection efficiency η of a single droplet g The following expression is used for calculation:

[0079]

[0080] Where: Stokes number s t The calculation expression is:

[0081]

[0082] Where: d p ρ represents the particle size of the blasting dust. p The density of the blasting dust; μ g D is the gas density. c denoted as droplet diameter.

[0083] This invention utilizes an intelligent rock structure identification device 1 to identify characteristic parameters such as joints and fissures at the tunnel face, controlling the amount of explosives used during blasting, and thus adjusting the total spray pressure of the atomizing dust suppression equipment to reduce construction costs. After blasting, the control equipment adjusts the position of the atomizing dust suppression component 3.2 and the position and angle of the nozzle 3.23, as well as the water spraying speed, based on the concentration of blasting dust and harmful gases monitored by the dust concentration meter 4, the four-in-one gas monitor 5, and the phase Doppler particle analyzer 6, to achieve faster, more comprehensive dust suppression in a shorter time, effectively reducing the concentration of blasting dust in the tunnel and improving the air quality of the tunnel construction environment. This invention is easy to implement, with a highly detachable, recyclable, and operable overall structure, enabling it to reduce the dust concentration in the tunnel to the required standard value more quickly and comprehensively in a shorter time, solving the problems of long spray dust suppression time, low efficiency, and impact on construction progress.

[0084] This invention relates to a machine vision-based dust suppression device. By combining an intelligent rock structure surface recognition device 1 with spray dust suppression, it solves the technical problem in existing technologies where tunnel blasting and dust suppression equipment often operate independently, lacking effective coordination and intelligent control. This invention utilizes the intelligent rock structure surface recognition device 1 to identify characteristic parameters such as joints and fissures at the tunnel face, controlling the amount of explosive charge during blasting, and thus adjusting the total spray pressure of the atomizing dust suppression equipment, reducing construction costs. After blasting, the control equipment uses dust concentration meter 4, a four-in-one gas monitor 5, and a phase Doppler particle analyzer 6 to monitor... By adjusting the position of the atomizing dust suppression component 3.2 and the position and angle of the nozzle 3.23, as well as the spraying speed of the atomizing medium, the concentration of blasting dust and harmful gases, as well as the propagation speed of the blasting dust, can be controlled to achieve faster, more comprehensive dust suppression in a shorter time. This effectively reduces the concentration of blasting dust in the tunnel and improves the air quality of the tunnel construction environment. The invention is easy to implement, and its overall structure is highly detachable, recyclable, and operable. It can reduce the dust concentration in the tunnel to the required level more quickly and comprehensively in a shorter time, solving the problems of long spray dust suppression time, low efficiency, and impact on construction progress.

[0085] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A machine vision based dust fall device, characterized in that, The device comprises a surrounding rock structure surface intelligent identification device, an anchoring assembly (2.1), a sliding rail assembly (2), an atomization assembly (3), a dust concentration instrument (4), a four-in-one gas monitoring instrument (5), a phase Doppler particle analyzer (6), and a control device connected to the surrounding rock structure surface intelligent identification device, the sliding rail assembly (2), the atomization assembly (3), the dust concentration instrument (4), the four-in-one gas monitoring instrument (5), and the phase Doppler particle analyzer (6).

2. The machine vision based dust suppression device of claim 1, wherein, The anchoring assembly (2.1) is detachably mounted on the tunnel top wall, the sliding rail assembly (2) is connected to the anchoring assembly (2.1), the sliding rail assembly (2) is arranged along the axial direction of the tunnel, the atomization assembly (3) is connected to the sliding rail assembly (2), the atomization assembly (3) is connected to the sliding rail assembly (2), the atomization assembly (3) is connected to the tunnel water pipe, and the surrounding rock structure surface intelligent identification device is mounted on the tunnel interior near the tunnel face.

3. The machine vision based dust fall device as claimed in claim 2, wherein, The anchoring assembly (2.1) comprises two rows of anchoring rods and two connecting rods, the anchoring rods are detachably connected between the tunnel top wall and the connecting rods, the length direction of the connecting rods is arranged along the axial direction of the tunnel, and the two connecting rods are arranged side by side, each row of anchoring rods is composed of at least two anchoring rods, and the at least two anchoring rods are arranged along the length direction of the connecting rods.

4. The machine vision based dust fall device as claimed in claim 3, wherein, The sliding rail assembly (2) comprises a guide rail (2.2), a hanging piece, and a pulley block, the hanging piece is fixed to the top of the guide rail (2.2), the hanging piece is hung on the connecting rod, the pulley block is slidingly installed on the guide rail (2.2), and the atomization assembly (3) is connected to the pulley block.

5. A machine vision based dust fall method, characterized by, The atomization assembly (3) comprises a dust falling pipe, a lifting rod, and a plurality of spray heads (3.23), the lifting rod is connected between the dust falling pipe and the pulley block, the plurality of spray heads (3.23) are arranged on the dust falling pipe at intervals, and the dust falling pipe is in an arc shape. The dust falling device based on machine vision is used for dust falling, and comprises the following steps: Step one: analyzing the joint fissure information of the tunnel face by the surrounding rock structure surface intelligent identification device (1), and grading the surrounding rock near the tunnel face in combination with the geological information; Step two: performing numerical simulation, blast hole arrangement, and charge calculation according to the joint fissure characteristic parameters of the tunnel face and the surrounding rock geological information identified by the surrounding rock structure surface intelligent identification device (1); Step three: adjusting the initial position and initial water pressure of the atomization assembly (3) according to the surrounding rock grade and the charge; 6. The machine vision-based dust fall method of claim 5, wherein, Step four: after blasting, adjusting the position and atomization intensity of the atomization assembly (3) according to the concentration of the blasting dust monitored by the dust concentration instrument (4), the concentration of the harmful gas monitored by the four-in-one gas monitoring instrument (5), and the propagation speed of the blasting dust monitored by the phase Doppler particle analyzer (6). The surrounding rock grade is evaluated by the Q value classification method. Wherein: RQD is rock quality index, according to the core of the degree of perfection when drilling to judge the quality of rock mass, the length of the solid and complete, its length is greater than or equal to 10 cm total length of the borehole length ratio, percentage is: Where: l i is the core length; J n is the total number of joints; J r is the joint roughness coefficient; J a is the joint alteration coefficient; J w is the joint water reduction factor; SRF is the stress reduction factor; According to the Q value size, the surrounding rock is divided into the following nine levels: very poor, Q < 0.01; extremely poor, 0.01 ≤ Q < 0.1; very poor, 0.1 ≤ Q < 1; poor, 1 ≤ Q < 4; medium, 4 ≤ Q < 10; good, 10 ≤ Q < 40; very good, 40 ≤ Q < 100; excellent, 100 ≤ Q < 400; very good, Q ≥ 400.

7. The machine vision-based dust fall method of claim 5, wherein, In step three, the starting position and initial water pressure of the dust falling device are adjusted according to the peak particle velocity as an index. The greater the peak particle velocity, the greater the distance between the dust falling device and the working face, and the greater the initial water pressure. The peak particle velocity PPV is calculated according to the following formula: Wherein: Q is the explosive quantity; R is the distance from the explosion source; K is the d coefficient related to the topography and geological conditions from the explosion point to the monitoring point; a is the attenuation index related to the topography and geological conditions from the explosion point to the monitoring point.

8. The machine vision-based dust fall method of claim 5, wherein, After monitoring the concentration of blasting dust by the dust concentration instrument (4) and the concentration of harmful gas by the four-in-one gas monitoring instrument (5), the on-site environmental classification index is calculated according to the following formula: Wherein: a is the volume content, b is the gas; c is the noise decibel level; T is the environmental temperature.

9. The machine vision-based dust fall method of claim 5, wherein, The propagation speed of the blasting dust monitored by the phase Doppler particle analyzer (6) is obtained by the following formula: wherein: f D is the shift frequency obtained by the phase Doppler particle analyzer (6); V q is the propagation velocity of the blasting dust; λ is the wavelength of the laser emitted by the phase Doppler particle analyzer (6), and θ is the angle between the line connecting the dust particle and the laser source and the direction of the dust velocity.

10. The machine vision-based dust fall method of claim 5, wherein, When the atomization intensity of the atomization assembly (3) is controlled by the control equipment, the dust falling amount of the droplets of the atomization assembly (3) per unit distance per unit time is expressed as follows: When the atomization intensity of the atomization assembly (3) is controlled by the control equipment, the dust falling amount of the droplets of the atomization assembly (3) per unit distance per unit time is expressed as follows: δ M = f(v, η g , C, A, q, S, V) / V 6); wherein: δ M is the dust fall per unit distance per unit time; f is a functional relationship; v is the relative velocity of the droplet and the dust; η g is the single droplet collection efficiency; C is the dust concentration; A is the cross-sectional area of the collection zone; q is the volumetric content of the medium; S is the cross-sectional area of the droplet; V is the volume of the droplet m 3 ; The capture efficiency η of a single droplet g The calculation is performed using the following expression: where: the Stokes number s t The calculation expression is: where: d p is the particle size of the blasting dust; p p is the density of the blasting dust; m g is the gas density; D c is the droplet size.

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