CN117145581B - Intelligent identification-tracking accurate dust falling system and method for dust source in underground operation space - Google Patents
Intelligent identification-tracking accurate dust falling system and method for dust source in underground operation space Download PDFInfo
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- 238000013508 migration Methods 0.000 claims abstract description 48
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B15/00—Details of spraying plant or spraying apparatus not otherwise provided for; Accessories
- B05B15/60—Arrangements for mounting, supporting or holding spraying apparatus
- B05B15/68—Arrangements for adjusting the position of spray heads
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B7/00—Spraying apparatus for discharge of liquids or other fluent materials from two or more sources, e.g. of liquid and air, of powder and gas
- B05B7/24—Spraying apparatus for discharge of liquids or other fluent materials from two or more sources, e.g. of liquid and air, of powder and gas with means, e.g. a container, for supplying liquid or other fluent material to a discharge device
- B05B7/26—Apparatus in which liquids or other fluent materials from different sources are brought together before entering the discharge device
- B05B7/262—Apparatus in which liquids or other fluent materials from different sources are brought together before entering the discharge device a liquid and a gas being brought together before entering the discharge device
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F5/00—Means or methods for preventing, binding, depositing, or removing dust; Preventing explosions or fires
- E21F5/02—Means or methods for preventing, binding, depositing, or removing dust; Preventing explosions or fires by wetting or spraying
- E21F5/04—Spraying barriers
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- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
- G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
- G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
- G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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Abstract
The invention discloses an intelligent dust source identification-tracking accurate dust fall system and method for an underground operation space, wherein a data acquisition unit is used for acquiring a real-time video image of dust in the underground operation space and feeding the real-time video image back to a dust source identification-tracking and spraying control unit; and then the dust source identification-tracking and spray control unit receives the fed-back dust real-time video data and analyzes and processes the data to obtain dust particle size distribution conditions and dust migration tracks in the underground operation space, further sends control instructions to the self-adaptive spray dust settling unit, and finally the self-adaptive spray dust settling unit adjusts the coverage range of a fog field and the particle size distribution of fog drops in real time according to the instructions of the dust source identification-tracking and spray control unit, so that the accurate treatment of the dust disaster sources in the underground operation space is realized. The whole process can realize dust particle size distribution identification and dust migration state tracking without more sensors, and high-efficiency and accurate dust fall is carried out on dust in a space according to monitoring conditions, so that the intelligent dust collector has the advantages of being strong in adaptability and high in intelligent degree.
Description
Technical Field
The invention relates to the technical field of mine dust control, in particular to an intelligent dust source identification-tracking accurate dust fall system and method for a downhole operation space.
Background
Along with the continuous improvement of the intelligent construction level of modern mine, the production efficiency of mine is improved continuously, and the underground dust yield is increased greatly. In addition, the underground operation environment is usually a limited operation space with limited import and export, poor natural ventilation and limited range of movement of workers, such as a single-head tunneling roadway, a drilling point, a belt transfer point and the like, and a large amount of dust in the operation place cannot be settled or discharged in time after being generated, so that a large amount of fine dust particles are accumulated in the space, and underground safe production and physical and mental health of workers are seriously threatened. Aiming at the dust prevention and control problem of the underground operation space, a water spray dust removal mode is mainly adopted at present. However, the existing spraying equipment mainly sprays water mist into the space in a single direction and power, and does not pay attention to dust conditions in the space, so that the problems of high water consumption, difficulty in efficiently inhibiting dust dissipation from a dust source, low intelligent degree and the like exist, a large amount of fine dust and water mist in the underground operation space are suspended in the air at the same time, and the operation condition is further deteriorated.
Publication number CN112169496a discloses a limited space intelligent accurate spray dust fall system and method, which realizes intelligent monitoring and spray dust fall of dust disaster state through various sensors, but because of the plurality of kinds and quantity of sensors adopted, the problems of high sensor cost, single function, a plurality of sensors and difficult field installation and maintenance are existed, and the actual dust control work requirement of underground operation space is difficult to meet. Publication number CN114033464a discloses a comprehensive digging working face self-tracking system and multi-angle dust gas integrated intelligent prevention and control system, mainly controls and removes the dissipation dust and improves a ventilation device by adjusting a ventilation mode, but lacks effective dust falling means, and does not realize the efficient treatment of dust sources of dust disasters. Publication number CN218266003U discloses an automatic spraying dust device of colliery that is convenient for install has improved the spraying coverage, but still has the problem that water pressure requirement is high, the water consumption is big and intelligent degree is lower, still can not realize the real-time regulation of spraying state. In summary, to solve the problem of dust prevention in the underground operation space, a new system and method are needed to realize dust particle size distribution identification and dust migration state tracking without more sensors, and to perform efficient and accurate dust fall on the dust in the space according to the monitoring conditions, so that the system and method have the advantages of strong adaptability and high intelligent degree.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides the intelligent recognition-tracking accurate dust fall system and the intelligent recognition-tracking accurate dust fall method for the dust source of the underground operation space, which can realize dust particle size distribution recognition and dust migration state tracking without more sensors, and can carry out efficient and accurate dust fall on dust in the space according to the monitoring condition, and have the advantages of strong adaptability and high intelligent degree.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: an intelligent dust source identification-tracking accurate dust fall system for an underground operation space comprises a data acquisition unit, a dust source identification-tracking and spraying control unit and an adaptive spraying dust fall unit;
the data acquisition unit is used for acquiring dust real-time video images of the underground working space and feeding the dust real-time video images back to the dust source identification-tracking and spraying control unit;
the dust source identification-tracking and spraying control unit is used for receiving the real-time video data of the dust shot by the data acquisition unit and analyzing and processing the real-time video data to obtain the dust particle size distribution condition and the dust migration track in the underground operation space, and further sending out a control instruction to enable the self-adaptive spraying dust fall unit to take corresponding spraying dust fall actions;
the self-adaptive spray dust settling unit is used for adjusting the coverage range of a fog field and the particle size distribution of fog drops in real time according to the control instruction of the dust source identification-tracking and spray control unit, so as to realize accurate dust settling in an underground operation space.
Further, the data acquisition unit comprises a high-definition camera, a base and an air curtain dust-proof device, a supporting rod is fixed on the base, a hoop is arranged on the high-definition camera, and the supporting rod is hinged with the hoop through a first connecting piece; the air curtain dust-separating device is arranged at the upper part of the front end of the high-definition camera; the air curtain dust-separating device comprises a guide cylinder and a guide groove, wherein the guide cylinder is cylindrical, one end of the guide cylinder is provided with an air inlet, the guide groove is arranged at the side part of the guide cylinder and is communicated with the inside of the guide cylinder, and a wedge-shaped flow passage is arranged in the guide cylinder and is used for enabling the flow field of air flow entering the guide cylinder to be uniformly distributed; the air outlet is formed in the guide groove, the direction of the air outlet is perpendicular to the shooting direction of the high-definition camera, and a plurality of combined guide vanes which are arranged at equal intervals are arranged in the guide groove and used for rectifying the air flow passing through the guide cylinder, so that the air outlet intensity of the air curtain and the anti-interference capability of the air flow are enhanced; the combined guide vane is formed by connecting vertical vanes and inclined vanes, and a certain included angle is formed between the vertical vanes and the inclined vanes, so that the inclination angle of the near wind side (namely the side close to the guide cylinder) of the combined guide vane is adjustable by 40-50 degrees, the strength of outlet wind flow can be improved, and the dust separation effect is enhanced. The dust is isolated outside the air curtain by the air curtain dust isolation device, so that the pollution of the dust in the underground operation space to the shooting lens of the high-definition camera can be greatly reduced.
Furthermore, the dust source identification-tracking and spraying control unit is a singlechip control box with built-in dust particle size distribution real-time identification and dust migration track tracking algorithm programs, and can realize real-time adjustment of spraying states.
Further, the self-adaptive spraying dust fall unit comprises a fixed seat, a control box body, a spraying box body, a first electric telescopic support rod, a second electric telescopic support rod and a miniature explosion-proof motor, wherein the miniature explosion-proof motor is arranged in the fixed seat, the fixed end of the first electric telescopic support rod is vertically arranged on the fixed seat through a rotating bearing, the first electric telescopic support rod can rotate relative to the fixed seat, and the fixed end of the first electric telescopic support rod is coaxially connected with an output shaft of the miniature explosion-proof motor, so that the miniature explosion-proof motor can drive the first electric telescopic support rod to synchronously rotate; the telescopic end of the first electric telescopic support rod is hinged with the lower part of the spraying box body, the fixed end of the second electric telescopic support rod is hinged with the side part of the fixed end of the first electric telescopic support rod, the telescopic end of the second electric telescopic support rod is hinged with the lower part of the spraying box body, and when the first electric telescopic support rod and the second electric telescopic support rod are telescopic, the spraying angle of the spraying box body can be adjusted; the control box body is arranged on the fixing seat, a controller is arranged in the control box body and is connected with the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor, the controller is used for controlling the start and stop of the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor, the control box body is provided with a power switch, a power interface and an RS485 data interface, the power interface is used for supplying power for the self-adaptive spraying dust fall unit, the power switch is used for controlling the on-off of a power supply circuit, the RS485 data interface is used for connecting the controller with the dust source identification-tracking and spray control unit, and the controller is used for receiving instructions of the dust source identification-tracking and spray control unit to control the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor; the side part of the spraying box body is provided with a plurality of air-water nozzles, the lower part of the spraying box body is provided with an air supply interface and a water supply interface, and air entering the spraying box body from the air supply interface and water entering the spraying box body from the water supply interface are mixed in the spraying box body and then sprayed out from the air-water nozzles to form spraying.
Further, the air supply interface and the water supply interface of the spraying box body are provided with proportional valves, the two proportional valves are connected with a dust source identification-tracking and spraying control unit, and the dust source identification-tracking and spraying control unit adjusts the air-liquid ratio entering the spraying box body by controlling the opening proportion of the two proportional valves, so that mist drops with different particle size distributions are finally sprayed from the air-water nozzles.
The working method of the intelligent identification-tracking accurate dust fall system for the dust source of the underground operation space comprises the following specific steps:
step one, laying out a system: in the underground operation space, arranging a dust source intelligent identification-tracking accurate dust fall system in a dust producing area;
step two, acquiring an original data set: selecting a plurality of groups of dust samples with known dust particle size distribution, sequentially releasing each group of dust samples in an underground operation space, continuously shooting video images of each group of dust samples released to the underground operation space through a data acquisition unit, and forming an original picture data set according to the particle size distribution data of each group of dust samples and combining the video image data of each group of dust samples in a corresponding release time range; then sorting the original data set, sorting the data of each group of dust samples according to the dust particle size distribution condition, and dividing the data into particle sizes D with dust particles cumulatively distributed to be 10% 10 Particle diameter D with dust particle cumulative distribution of 50% 50 Particle diameter D with dust particle cumulative distribution of 90% 90 And average particle diameter of dust particlesParticle diameter D in which dust particles are cumulatively distributed to 10% 10 That is, the cumulative volume of dust particles smaller than this particle diameter accounts for 10% of the cumulative volume of all dust particles; particle diameter D with dust particle cumulative distribution of 90% 90 That is, the cumulative volume of dust particles smaller than this particle diameter accounts for 90% of the cumulative volume of all dust particles; particle diameter D with dust particle cumulative distribution of 50% 50 Also called median diameter or median particle diameter, which is a typical value representing the size of the particle size, which accurately divides the population into halves, that is to say 50% of the dust particles have a particle size exceeding this value, and the other 50% have a particle size not exceeding this value; for example D for a dust sample 50 ＝5μm, it is stated that of all the particles of the particle diameter constituting the dust sample, dust particles exceeding 5 μm account for 50%, and dust particles not exceeding 5 μm account for 50%.
Step three, establishing a dust particle size distribution identification model: training and testing a dust particle size distribution identification model by adopting a CNN image identification method based on the original data set obtained in the second step; adding a time sequence into the CNN image recognition method, and recognizing the dust particle size D at each moment by taking the key frame number of the video as a time parameter 10 、D 50 、D 90 Andto identify the time distribution characteristics (T, D) 10 ，D 50 ，D 90 ，/>) Finally, a dust particle size distribution identification model is established, so that the model can dynamically identify the dust particle size distribution in the current underground operation space according to the real-time video image data acquired by the data acquisition unit;
step four, establishing a dust migration track tracking model: based on a HYSPLIT model, a dust migration track tracking model is established on the basis of the dust particle size distribution identification model established in the step three, the dust migration track tracking model can locate and track dust tracks in an underground operation space according to real-time video image data acquired by an acquisition unit, discrete track points are converted into continuous tracks to calculate the speed and acceleration of dust migration, and tracing and forward prediction are carried out on the dust tracks, so that dust migration state tracking in the underground operation space is realized;
step five, accurate dust fall: when the underground operation space starts to normally produce, the data acquisition unit acquires real-time video image data and transmits the data to the dust source identification-tracking and spraying control unit, the dust source identification-tracking and spraying control unit analyzes the video image data by using the dust particle size distribution identification model to obtain the current dust particle size distribution condition, and simultaneously analyzes the video image data by using the dust migration track tracking model to obtain the current dust migration track and forward prediction; then the dust source identification-tracking and spray control unit sends a control instruction to the self-adaptive spray dust falling unit according to the acquired dust migration track and the direction prediction, and a controller of the self-adaptive spray dust falling unit receives the instruction and then controls the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor, so that the spray direction and the spray angle of the self-adaptive spray dust falling unit are adjusted to be consistent with the dust migration track and the direction prediction; meanwhile, the dust source identification-tracking and spraying control unit controls the opening proportion of the two proportional valves according to the acquired dust particle size distribution condition, so that the gas-liquid ratio of the two proportional valves entering the spraying box body is adjusted, mist drops which are suitable for the dust particle size distribution condition are sprayed out by the gas-water nozzle, and the accurate dust fall in the underground operation space is finally realized.
Compared with the prior art, the invention adopts a mode of combining a data acquisition unit, a dust source identification-tracking and spray control unit and a self-adaptive spray dust fall unit, and has the specific advantages that:
1. the data acquisition unit is internally provided with the air curtain dust-separating device, and the air curtain dust-separating device forms an air curtain in front of the lens of the high-definition camera, so that the problem that high-concentration dust in an underground working space pollutes the lens of the high-definition camera is solved, the guide cylinder structure in the air curtain dust-separating device can uniformly distribute an internal gas flow field, and meanwhile, the structures of the guide grooves and the guide blades of the guide cylinder structure improve the air flow intensity of an air outlet, so that the dust-separating effect of the air curtain on the space in front of the lens of the high-definition camera is greatly enhanced, and compared with the traditional dustproof camera, the dustproof camera has the characteristics of intrinsic safety, low maintenance cost and strong adaptability, the imaging quality of the camera in a high-dust environment is improved, and reliable image data support is provided for intelligent dust identification and tracking.
2. According to the invention, an original image data set is firstly obtained, then a machine vision method is used for training and testing to establish a dust particle size distribution identification model and a dust migration track tracking model, then real-time video image data in an underground operation space is obtained and is input into the dust particle size distribution identification model, so that the particle size distribution of dust is identified in real time, the problem that the dust particle size distribution mainly depends on laboratory testing and lacks timeliness is solved, the timeliness of on-site dust particle size distribution characteristic acquisition is remarkably improved, and meanwhile, after the data is analyzed and processed by the dust migration track tracking model, the real-time tracing and the forward prediction of the dust migration track are realized, effective information support is provided for adjusting and controlling the state of spraying equipment by adopting targeted measures, the defects of poor flexibility and accuracy caused by the lack of real-time dust state information guidance of traditional spraying dust fall are overcome, and the intelligent and accurate prevention level of underground dust disasters is improved.
3. After the real-time particle size distribution and the migration track information of the dust are obtained, the gas-liquid ratio in the self-adaptive spraying dust fall unit can be adjusted by controlling the opening proportion of the two proportional valves, so that the self-adaptive spraying dust fall unit can spray mist drops which are suitable for obtaining the real-time particle size distribution of the dust; and the spraying direction and the spraying angle of the self-adaptive spraying dust fall unit are controlled to be adaptive to the acquired dust migration track, namely, the spraying direction and the spraying angle of the self-adaptive spraying dust fall unit continuously change along with the dust migration track, so that the self-adaptive function of spraying fog drop particle size distribution and fog field coverage is realized, the problem that the existing spraying dust fall equipment is difficult to effectively make timely treatment action according to the on-site dust development state is solved, compared with the traditional spraying equipment, the dust fall efficiency is remarkably improved, the unnecessary water consumption is reduced, the secondary deterioration of the operation environment caused by the suspension of excessive water mist in the air is avoided, and the accurate source management of dust disasters in the underground operation space is realized.
Drawings
FIG. 1 is a schematic diagram of a data acquisition unit according to the present invention;
fig. 2 is a partial enlarged view of the high-definition camera of fig. 1;
FIG. 3 is a schematic view showing the internal structure of the air curtain dust-separating apparatus of the present invention;
FIG. 4 is a flow chart showing the construction of a dust particle size distribution recognition model and a dust migration trajectory tracking model according to the present invention;
FIG. 5 is a schematic diagram of the structure of the adaptive spray dust suppression unit of the present invention;
FIG. 6 is a right side view of FIG. 5;
FIG. 7 is a schematic diagram of the operation of the dust source intelligent recognition-tracking accurate dust fall system of the present invention.
In the figure: the device comprises a base, a 2-supporting rod, a 3-first connecting piece, a 4-ferrule, a 5-high-definition camera, a 6-fixing piece, a 7-air curtain dust-proof device, an 8-guide cylinder, a 9-guide groove, a 10-combined guide vane, an 11-air inlet, a 12-air outlet, a 13-fixing seat, a 14-rotating bearing, a 15-first electric telescopic strut, a 16-second electric telescopic strut, a 17-second connecting piece, a 18-water supply interface, a 19-third connecting piece, a 20-spraying box body, a 21-controller, a 22-miniature explosion-proof motor, a 23-RS485 data interface, a 24-power interface, a 25-power switch, a 26-control box body, a 27-air supply interface and a 28-air-water nozzle.
Detailed Description
The present invention will be further described below.
As shown in fig. 7, the intelligent dust source identification-tracking accurate dust-settling system for the underground operation space comprises a data acquisition unit, a dust source identification-tracking and spraying control unit and an adaptive spraying dust-settling unit;
the data acquisition unit is used for acquiring dust real-time video images of the underground working space and feeding the dust real-time video images back to the dust source identification-tracking and spraying control unit; as shown in fig. 1 to 3, the data acquisition unit comprises a high-definition camera 5, a base 1 and an air curtain dust-proof device 7, wherein a supporting rod 2 is fixed on the base 1, a hoop 4 is arranged on the high-definition camera 5, and the supporting rod 2 is hinged with the hoop 4 through a first connecting piece 3; the air curtain dust-separating device 7 is arranged at the upper part of the front end of the high-definition camera 5; the air curtain dust separation device 7 comprises a guide cylinder 8 and a guide groove 9, wherein the guide cylinder 8 is cylindrical, one end of the guide cylinder is provided with an air inlet, the guide groove 9 is arranged on the side part of the guide cylinder 8 and is communicated with the inside of the guide cylinder 8, and a wedge-shaped flow passage is arranged in the guide cylinder 8 and is used for enabling the flow field of air flow entering the guide cylinder 8 to be uniformly distributed; the air outlet is formed in the guide groove 9, the direction of the air outlet is perpendicular to the shooting direction of the high-definition camera 5, and a plurality of combined guide vanes 10 which are arranged at equal intervals are arranged in the guide groove 9 and are used for rectifying the air flow passing through the guide cylinder 8, so that the air outlet intensity of the air curtain and the anti-interference capability of the air flow are enhanced; the combined guide vane 10 is formed by connecting a vertical vane and an inclined vane, and a certain included angle is formed between the vertical vane and the inclined vane, so that the inclined angle of the near wind side of the combined guide vane 10 is adjustable by 40-50 degrees, the strength of outlet wind flow can be improved, and the dust separation effect is enhanced. The dust is isolated outside the air curtain by the air curtain generated by the air curtain dust isolation device 7, so that the pollution of the dust in the underground operation space to the shooting lens of the high-definition camera 5 can be greatly reduced.
The dust source identification-tracking and spraying control unit is a singlechip control box internally provided with a dust particle size distribution real-time identification and dust migration track tracking algorithm program and is used for receiving dust real-time video data shot by the data acquisition unit and analyzing and processing the dust real-time video data to obtain dust particle size distribution conditions and dust migration tracks in an underground working space, and the dust source identification-tracking and spraying control unit is used for receiving the dust real-time video data shot by the data acquisition unit and analyzing and processing the dust real-time video data to obtain dust particle size distribution conditions and dust migration tracks in the underground working space and further sending a control instruction to enable the self-adaptive spraying dust fall unit to take corresponding spraying dust fall actions; thereby enabling real-time adjustment of the spray status.
The self-adaptive spray dust settling unit is used for adjusting the coverage range of a fog field and the particle size distribution of fog drops in real time according to the control instruction of the dust source identification-tracking and spray control unit, so as to realize accurate dust settling in an underground operation space. As shown in fig. 5 and 6, the self-adaptive spray dust settling unit comprises a fixed seat 13, a control box 26, a spray box 20, a first electric telescopic strut 15, a second electric telescopic strut 16 and a miniature explosion-proof motor 22, wherein the miniature explosion-proof motor 22 is arranged in the fixed seat 13, the fixed end of the first electric telescopic strut 15 is vertically arranged on the fixed seat 13 through a rotating bearing 14, the first electric telescopic strut 15 can rotate relative to the fixed seat 13, and the fixed end of the first electric telescopic strut 15 is coaxially connected with an output shaft of the miniature explosion-proof motor 22, so that the miniature explosion-proof motor 22 can drive the first electric telescopic strut 15 to synchronously rotate; the telescopic end of the first electric telescopic strut 15 is hinged with the lower part of the spraying box body 20 through a third connecting piece 19, the fixed end of the second electric telescopic strut 16 is hinged with the side part of the fixed end of the first electric telescopic strut 15, the telescopic end of the second electric telescopic strut 16 is hinged with the lower part of the spraying box body 20 through a second connecting piece 17, and when the first electric telescopic strut 15 and the second electric telescopic strut 16 stretch out and draw back, the spraying angle of the spraying box body 20 can be adjusted; the control box 26 is arranged on the fixed seat 13, a controller 21 is arranged in the control box 26, the controller 21 is connected with the first electric telescopic support rod 15, the second electric telescopic support rod 16 and the miniature explosion-proof motor 22 and is used for controlling the start and stop of the first electric telescopic support rod 15, the second electric telescopic support rod 16 and the miniature explosion-proof motor 22, the control box 16 is provided with a power switch 25, a power interface 24 and an RS485 data interface 23, the power interface 24 is used for supplying power for the self-adaptive spraying dust fall unit, the power switch 25 is used for controlling the on-off of a power supply circuit, and the RS485 data interface 23 is used for connecting the controller 21 with a dust source identification-tracking and spraying control unit so that the controller 21 receives instructions of the dust source identification-tracking and spraying control unit to control the first electric telescopic support rod 15, the second electric telescopic support rod 16 and the miniature explosion-proof motor 22; the side part of the spraying box body 20 is provided with a plurality of air-water nozzles 28, the lower part of the spraying box body is provided with an air supply interface 27 and a water supply interface 18, and air entering the spraying box body 20 from the air supply interface 27 and water entering the spraying box body 20 from the water supply interface 18 are mixed in the spraying box body 20 and then sprayed out from the air-water nozzles 28 to form spraying; the air supply interface 27 and the water supply interface 18 of the spraying box body 20 are respectively provided with a proportional valve, and the two proportional valves are connected with a dust source identification-tracking and spraying control unit, and the dust source identification-tracking and spraying control unit adjusts the air-liquid ratio entering the spraying box body 20 by controlling the opening proportion of the two proportional valves, so that mist drops with different particle size distributions are finally sprayed from the air-water nozzle 28.
As shown in fig. 4, the working method of the above-mentioned intelligent dust source identification-tracking accurate dust fall system for underground operation space specifically comprises the following steps:
step one, laying out a system: in the underground operation space, arranging a dust source intelligent identification-tracking accurate dust fall system in a dust producing area;
step two, obtaining the original numberData set: selecting a plurality of groups of dust samples with known dust particle size distribution, sequentially releasing each group of dust samples in an underground operation space, continuously shooting video images of each group of dust samples released to the underground operation space through a data acquisition unit, and forming an original picture data set according to the particle size distribution data of each group of dust samples and combining the video image data of each group of dust samples in a corresponding release time range; then sorting the original data set, sorting the data of each group of dust samples according to the dust particle size distribution condition, and dividing the data into particle sizes D with dust particles cumulatively distributed to be 10% 10 Particle diameter D with dust particle cumulative distribution of 50% 50 Particle diameter D with dust particle cumulative distribution of 90% 90 And average particle diameter of dust particlesParticle diameter D in which dust particles are cumulatively distributed to 10% 10 That is, the cumulative volume of dust particles smaller than this particle diameter accounts for 10% of the cumulative volume of all dust particles; particle diameter D with dust particle cumulative distribution of 90% 90 That is, the cumulative volume of dust particles smaller than this particle diameter accounts for 90% of the cumulative volume of all dust particles; particle diameter D with dust particle cumulative distribution of 50% 50 Also called median diameter or median particle diameter, which is a typical value representing the size of the particle size, which accurately divides the population into halves, that is to say 50% of the dust particles have a particle size exceeding this value, and the other 50% have a particle size not exceeding this value; for example D for a dust sample 50 =5 μm, indicating that of all the particle size particles constituting the dust sample, dust particles exceeding 5 μm account for 50%, and dust particles not exceeding 5 μm account for 50%.
Step three, establishing a dust particle size distribution identification model: training and testing a dust particle size distribution identification model by adopting a CNN image identification method based on the original data set obtained in the second step; the method comprises the following steps: training and testing the original data set according to the proportion of 7:3, and calculating the identification errorWherein n is predictive label and realThe number of data with inconsistent inter-label is N as the total predicted data, when the error is less than 1%, the optimal parameters of the model are saved, a preliminary dust particle size distribution identification model is output, then a time sequence is added in a CNN image identification method, the key frame serial number of a video is used as the time parameter, the time T(s) is recorded by the key frame time sequence j (frame), T=12j, and the dust particle size D at each moment is identified 10 、D 50 、D 90 And->To identify the time distribution characteristics (T, D) 10 ，D 50 ，D 90 ，/>) Finally, a dust particle size distribution identification model is established, so that the model can dynamically identify the dust particle size distribution in the current underground operation space according to the real-time video image data acquired by the data acquisition unit;
step four, establishing a dust migration track tracking model: based on a HYSPLIT model, a dust migration track tracking model is established on the basis of the dust particle size distribution identification model established in the step three, the dust migration track tracking model can locate and track dust tracks in an underground operation space according to real-time video image data acquired by an acquisition unit, discrete track points are converted into continuous tracks to calculate the speed and acceleration of dust migration, and tracing and forward prediction are carried out on the dust tracks, so that dust migration state tracking in the underground operation space is realized; the method comprises the following steps:
(1) adding a track to a dust particle size distribution identification model for positioning; a binary image of 0 and 1 is output on a Softmax layer of the dust particle size distribution identification model, wherein 0 represents a background area, 1 represents a target area, the mass center (i.e. mass center) of the target area is calculated as a track point of dust at the current moment, and the two-dimensional discrete and finite point set is calculated by the following form:
wherein T represents time, i represents pixel sequence number, and w i Represents the coordinate weights in each axial direction, and w= Σ i w i Expressed as the overall quality of the image correspondence;
(2) converting the two-dimensional coordinates of the centroid into three-dimensional coordinates, specifically comprising the following steps:
1) Calibrating a camera to obtain internal and external parameters of the high-definition camera, including internal parameters (such as focal length, principal point coordinates and the like) and external parameters (such as camera position and orientation) of the high-definition camera, and establishing an internal reference matrix and an external reference matrix of the high-definition camera;
2) Multiplying the two-dimensional coordinate points by the external reference matrix to convert centroid points in the two-dimensional image into points of a camera coordinate system;
3) Converting the position of the centroid from a camera coordinate system to a world coordinate system, and calculating three-dimensional coordinates (x, y, z) of the centroid point in the world coordinate system by using a dot function in a numpy library of python;
(3) three-dimensional reconstruction, connecting track points in sequence according to a key frame time sequence, and drawing an actual dust migration track graph g 0 ＝f(x，y，z，T)；
(4) Tracing and forward prediction are carried out on dust tracks by using the thought of calculating and analyzing atmospheric transmission and diffusion by using a HYSPLIT model, a Lagrange method is adopted for advection and diffusion calculation, and if particles in air drift with wind, the moving track is the integral of position vectors on time and space; when the motion trail of particles carried by the airflow is calculated, the final position is calculated by the average velocity of the initial position Q and the first guess position Q':
first guess position
Q′(T+ΔT)＝Q(T)+V(Q,T)ΔT
Final position
Q(T+ΔT)＝Q(T)+0.5×[V(Q,T)+V(Q′,T+ΔT)]ΔT
Wherein DeltaT is a time step and can be selected according to requirements;
(5) drawing a predicted track graph g 1 =f (x, y, z, T) and trace-trace graph g 2 ＝f(x，y，z，T)，Deriving a new trajectory graphThe speed calculation of dust migration is that the motion trail g=f (x, y, z, T) of the mass center is obtained by the step, and the speeds in x, y and z can be obtained by deviating T:
velocity derivative to obtain acceleration:
through the steps, a dust migration track tracking model is finally established;
step five, accurate dust fall: when the underground operation space starts to normally produce, the data acquisition unit acquires real-time video image data and transmits the data to the dust source identification-tracking and spraying control unit, the dust source identification-tracking and spraying control unit analyzes the video image data by using the dust particle size distribution identification model to obtain the current dust particle size distribution condition, and simultaneously analyzes the video image data by using the dust migration track tracking model to obtain the current dust migration track and forward prediction; then the dust source identification-tracking and spray control unit sends a control instruction to the self-adaptive spray dust settling unit according to the acquired dust migration track and the direction prediction, and the controller of the self-adaptive spray dust settling unit receives the instruction and then controls the first electric telescopic support rod 115, the second electric telescopic support rod 16 and the miniature explosion-proof motor 22, so that the spray direction and the angle of the self-adaptive spray dust settling unit are adjusted to be consistent with the dust migration track and the direction prediction, and the targeted adjustment of the spray coverage area is realized by adaptively adjusting the spray direction and the angle, thereby remarkably improving the dust settling efficiency, simultaneously reducing unnecessary water consumption, solving the problem that the existing spray dust settling equipment is difficult to effectively make timely treatment action according to the on-site dust development state, and solving the problems that the existing spray dust settling equipment is difficult to effectivelyThe method avoids the deterioration of the working environment caused by the suspension of excessive water mist in the air of the underground working space, and realizes the accurate source management of dust disasters in the underground working space. At the same time, the dust source recognition-tracking and spraying control unit obtains the dust particle size distribution (i.e. obtains the average particle sizes of dust particles at different positions)) The opening ratio of the two proportional valves is controlled, so that the gas-liquid ratio of the spray box body is adjusted, the gas-water nozzle sprays mist drops which are suitable for the dust particle size distribution, the specific adjustment parameters are shown in table 1, the dust settling effect can be ensured by adapting the mist drop particle size to the dust particle size distribution, the water consumption is further reduced, and the accurate dust settling in the underground operation space is finally realized.
TABLE 1 comparison of dust particle size distribution and mist particle size distribution
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (5)
1. The working method of the underground operation space dust source intelligent identification-tracking accurate dust fall system is characterized in that the adopted underground operation space dust source intelligent identification-tracking accurate dust fall system comprises a data acquisition unit, a dust source identification-tracking and spraying control unit and a self-adaptive spraying dust fall unit; the data acquisition unit is used for acquiring dust real-time video images of the underground working space and feeding the dust real-time video images back to the dust source identification-tracking and spraying control unit; the dust source identification-tracking and spraying control unit is used for receiving the real-time video data of the dust shot by the data acquisition unit and analyzing and processing the real-time video data to obtain the dust particle size distribution condition and the dust migration track in the underground operation space, and further sending out a control instruction to enable the self-adaptive spraying dust fall unit to take corresponding spraying dust fall actions; the self-adaptive spray dust fall unit is used for adjusting the coverage range of a fog field and the particle size distribution of fog drops in real time according to the control instruction of the dust source identification-tracking and spray control unit, and realizes accurate dust fall in an underground operation space, and comprises the following specific working steps:
step one, laying out a system: in the underground operation space, arranging a dust source intelligent identification-tracking accurate dust fall system in a dust producing area;
step two, acquiring an original data set: selecting a plurality of groups of dust samples with known dust particle size distribution, sequentially releasing each group of dust samples in an underground operation space, continuously shooting video images of each group of dust samples released to the underground operation space through a data acquisition unit, and forming an original data set according to the particle size distribution data of each group of dust samples and combining the video image data of each group of dust samples in a corresponding release time range; then sorting the original data set, sorting the data of each group of dust samples according to the dust particle size distribution condition, and dividing the data into particle sizes D with dust particles cumulatively distributed to be 10% 10 Particle diameter D with dust particle cumulative distribution of 50% 50 Particle diameter D with dust particle cumulative distribution of 90% 90 And average particle diameter of dust particles
Step three, establishing a dust particle size distribution identification model: training and testing a dust particle size distribution identification model by adopting a CNN image identification method based on the original data set obtained in the second step; adding a time sequence into the CNN image recognition method, and recognizing the dust particle size D at each moment by taking the key frame number of the video as a time parameter 10 、D 50 、D 90 Andto identify the time distribution characteristic of the dust particle size distribution +.>Finally, a dust particle size distribution identification model is established, so that the model can dynamically identify the dust particle size distribution in the current underground operation space according to the real-time video image data acquired by the data acquisition unit;
step four, establishing a dust migration track tracking model: based on a HYSPLIT model, a dust migration track tracking model is established on the basis of the dust particle size distribution identification model established in the step three, the dust migration track tracking model can locate and track dust tracks in an underground operation space according to real-time video image data acquired by an acquisition unit, discrete track points are converted into continuous tracks to calculate the speed and acceleration of dust migration, and tracing and forward prediction are carried out on the dust tracks, so that dust migration state tracking in the underground operation space is realized;
step five, accurate dust fall: when the underground operation space starts to normally produce, the data acquisition unit acquires real-time video image data and transmits the data to the dust source identification-tracking and spraying control unit, the dust source identification-tracking and spraying control unit analyzes the video image data by using the dust particle size distribution identification model to obtain the current dust particle size distribution condition, and simultaneously analyzes the video image data by using the dust migration track tracking model to obtain the current dust migration track and forward prediction; then the dust source identification-tracking and spraying control unit sends a control instruction to the self-adaptive spraying dust-settling unit according to the acquired dust migration track and the acquired forward prediction, so that the spraying direction and the spraying angle of the self-adaptive spraying dust-settling unit are adjusted to be consistent with the dust migration track and the forward prediction; meanwhile, the dust source identification-tracking and spraying control unit adjusts the gas-liquid ratio entering the spraying box body according to the acquired dust particle size distribution condition, and finally, mist drops which are suitable for the dust particle size distribution condition are sprayed out from the gas-water nozzle, so that accurate dust fall in the underground operation space is finally realized.
2. The working method of the intelligent identification-tracking accurate dust fall system for the underground working space according to claim 1, wherein the data acquisition unit comprises a high-definition camera, a base and an air curtain dust isolation device, a support rod is fixed on the base, a hoop is arranged on the high-definition camera, and the support rod is hinged with the hoop through a first connecting piece; the air curtain dust-separating device is arranged at the upper part of the front end of the high-definition camera; the air curtain dust-separating device comprises a guide cylinder and a guide groove, wherein the guide cylinder is cylindrical, one end of the guide cylinder is provided with an air inlet, the guide groove is arranged at the side part of the guide cylinder and is communicated with the inside of the guide cylinder, and a wedge-shaped flow passage is arranged in the guide cylinder and is used for enabling the flow field of air flow entering the guide cylinder to be uniformly distributed; the air outlet is formed in the guide groove, the direction of the air outlet is perpendicular to the shooting direction of the high-definition camera, and a plurality of combined guide vanes which are arranged at equal intervals are arranged in the guide groove and used for rectifying air flow passing through the guide cylinder, so that the air outlet intensity of the air curtain and the anti-interference capability of air flow are enhanced.
3. The working method of the intelligent dust source identification-tracking accurate dust fall system for the underground working space according to claim 1, wherein the dust source identification-tracking and spraying control unit is a singlechip control box with built-in dust particle size distribution real-time identification and dust migration track tracking algorithm programs, and can realize real-time adjustment of spraying states.
4. The working method of the intelligent dust source identification-tracking accurate dust fall system for the underground working space according to claim 1, wherein the self-adaptive spraying dust fall unit comprises a fixed seat, a control box body, a spraying box body, a first electric telescopic support rod, a second electric telescopic support rod and a miniature explosion-proof motor, the miniature explosion-proof motor is arranged in the fixed seat, the fixed end of the first electric telescopic support rod is vertically arranged on the fixed seat through a rotating bearing, the first electric telescopic support rod can rotate relative to the fixed seat, and the fixed end of the first electric telescopic support rod is coaxially connected with an output shaft of the miniature explosion-proof motor, so that the miniature explosion-proof motor can drive the first electric telescopic support rod to synchronously rotate; the telescopic end of the first electric telescopic support rod is hinged with the lower part of the spraying box body, the fixed end of the second electric telescopic support rod is hinged with the side part of the fixed end of the first electric telescopic support rod, the telescopic end of the second electric telescopic support rod is hinged with the lower part of the spraying box body, and when the first electric telescopic support rod and the second electric telescopic support rod are telescopic, the spraying angle of the spraying box body can be adjusted; the control box body is arranged on the fixing seat, a controller is arranged in the control box body and is connected with the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor, the controller is used for controlling the start and stop of the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor, the control box body is provided with a power switch, a power interface and an RS485 data interface, the power interface is used for supplying power for the self-adaptive spraying dust fall unit, the power switch is used for controlling the on-off of a power supply circuit, the RS485 data interface is used for connecting the controller with the dust source identification-tracking and spray control unit, and the controller is used for receiving instructions of the dust source identification-tracking and spray control unit to control the first electric telescopic support rod, the second electric telescopic support rod and the miniature explosion-proof motor; the side part of the spraying box body is provided with a plurality of air-water nozzles, the lower part of the spraying box body is provided with an air supply interface and a water supply interface, and air entering the spraying box body from the air supply interface and water entering the spraying box body from the water supply interface are mixed in the spraying box body and then sprayed out from the air-water nozzles to form spraying.
5. The working method of the intelligent dust source identification-tracking accurate dust fall system for the underground working space according to claim 4, wherein proportional valves are arranged at an air supply interface and a water supply interface of the spraying box body, the two proportional valves are connected with a dust source identification-tracking and spraying control unit, and the dust source identification-tracking and spraying control unit adjusts the gas-liquid ratio entering the spraying box body by controlling the opening proportion of the two proportional valves, so that mist drops with different particle size distributions are finally sprayed from a gas-water nozzle.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110410075A (en) * | 2019-07-31 | 2019-11-05 | 西安科技大学 | A kind of full-mechanized roadway/constructing tunnel dust removal method and dust pelletizing system |
| KR102041945B1 (en) * | 2019-07-04 | 2019-11-07 | 김영호 | Artificial intelligent system for removing dust for structure demolition method |
| CN216457759U (en) * | 2021-12-18 | 2022-05-10 | 郑州市丰悦机械有限公司 | Intelligent spraying dust-settling device |
| CN115596441A (en) * | 2022-10-18 | 2023-01-13 | 山东科技大学（Cn） | Dynamic tracking intelligent spraying dust-settling device and working method |
-
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102041945B1 (en) * | 2019-07-04 | 2019-11-07 | 김영호 | Artificial intelligent system for removing dust for structure demolition method |
| CN110410075A (en) * | 2019-07-31 | 2019-11-05 | 西安科技大学 | A kind of full-mechanized roadway/constructing tunnel dust removal method and dust pelletizing system |
| CN216457759U (en) * | 2021-12-18 | 2022-05-10 | 郑州市丰悦机械有限公司 | Intelligent spraying dust-settling device |
| CN115596441A (en) * | 2022-10-18 | 2023-01-13 | 山东科技大学（Cn） | Dynamic tracking intelligent spraying dust-settling device and working method |
Non-Patent Citations (1)
| Title |
|---|
| 煤与瓦斯突出煤粉在巷道内运移分布规律试验研究;张超林等;《煤田地质与勘探》(第6期);11-19 * |
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