Multi-node cooperative control method and system for surface mine blasting

Abstract

The invention discloses a multi-node cooperative control method and system for surface mine blasting, and relates to the technical field of mine blasting. The method comprises the following steps: dividing mine blasting operation into a drilling node, a blasting node, a shoveling node, a transportation node and a crushing node, obtaining a drilling energy consumption coefficient, a blasting energy consumption coefficient, a shoveling energy consumption coefficient, a transportation energy consumption coefficient and a crushing energy consumption coefficient, obtaining a first evaluation coefficient, and obtaining the optimal gravel lumpiness according to the first evaluation coefficient; constructing a blasting control model according to the historical blasting data, and obtaining an optimal blasting scheme by combining the drilling energy consumption coefficient and the blasting energy consumption coefficient; the energy consumption conditions of different nodes can be judged, the energy consumption of the different nodes can be reduced, and the collaboration among the different nodes can be enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of mine blasting, and in particular to a multi-node collaborative control method and system for open-pit mine blasting. Background Art

[0002] Coordinated control of multiple nodes in mine blasting is a complex and important project. It aims to optimize the efficiency and safety of blasting operations. By establishing a mathematical model that considers the interrelationships between nodes such as drilling, charging, wiring, and detonation, and then optimizing blasting parameters, it can significantly improve production efficiency and safety management, providing strong support for the development of the mining industry. Generally speaking, the size of the gravel produced in the blasting stage will directly affect the energy consumption of other subsequent stages. For example, if the gravel is too large in the crushing stage, its energy consumption will increase significantly. However, the existing technology lacks the technical means to connect different nodes together for energy consumption evaluation and optimization, resulting in low coordination between different nodes. In response to the shortcomings of the existing technology, the present invention provides a multi-node collaborative control method and system for open-pit mine blasting. Summary of the Invention

[0003] The purpose of the present invention is to provide a multi-node collaborative control method and system for open-pit mine blasting.

[0004] The purpose of the present invention can be achieved by the following technical solution: a multi-node collaborative control method and system for open-pit mine blasting, comprising the following modules: Node division module, used to divide mine blasting operations into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Energy consumption evaluation module, used to obtain drilling energy consumption coefficient, blasting energy consumption coefficient, shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient of drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; A fragmentation evaluation module is used to obtain a first evaluation coefficient based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient, and to obtain an optimal crushed stone fragmentation based on the first evaluation coefficient; The blockiness control module is used to obtain historical blasting data and build a blasting control model, combining the drilling energy consumption coefficient and the blasting energy consumption coefficient to obtain the optimal blasting plan.

[0005] Furthermore, the process of dividing the mine blasting operation into drilling node, blasting node, shoveling node, transportation node, and crushing node includes: The drilling node refers to the process of drilling holes in rock to provide space for placing explosives for subsequent blasting. The blasting node refers to the process of breaking rock by blasting explosives to form gravel. The shoveling node refers to the process of loading the blasted gravel onto transportation equipment. The transportation node refers to the process of transporting the gravel from the blasting site to the processing site. The crushing node refers to the process of crushing large pieces of gravel into small particles.

[0006] Furthermore, the process of obtaining the drilling energy consumption coefficient of the drilling node includes: Obtain the pressure work W during drilling Y and torque work W N , and the friction energy E consumed when friction destroys the rock R and the compression energy E consumed when compressing and destroying the rock Y ;

[0007]

[0008] Where F is the pressure acting on the rock, v is the downward pressure speed of the drill bit of the drilling equipment, n is the speed of the drill bit, N is the torque of the drill bit, and t is the action time of the drill bit; The friction energy E R Equal to the bottom friction energy E d and lateral friction energy E c and the frictional energy of water E s sum;

[0009]

[0010]

[0011] in, is the bottom friction coefficient, R is the drill bit radius, is the lateral friction coefficient, K c is the preset lateral conversion factor, is the standard density of water; The compression energy E Y Equal to the axial compression energy E z and the annular compression energy E h sum;

[0012]

[0013] According to the pressure work, torque work, friction energy and compression energy of a single borehole during the drilling process, the drilling energy consumption coefficient P of the single borehole is obtained. z ;

[0014] Furthermore, the process of obtaining the blasting energy consumption coefficient, shoveling energy consumption coefficient, and transportation energy consumption coefficient of the blasting node, shoveling node, and transportation node includes: For a blasting node, the amount of explosives in a single borehole is taken as the blasting energy consumption coefficient of the single borehole, which is recorded as P b ,For shoveling nodes and transportation nodes, obtain historical shoveling data and historical transportation data; The historical shovel loading data includes the fuel consumption y of the shovel loading equipment per unit time. a The average size of the crushed stone shoveled is c a , the average block size refers to the average diameter of each piece of gravel; According to the corresponding relationship between fuel consumption and average block size in different historical shovel loading data, the corresponding relationship function y is constructed. a =f(c a ), the fuel consumption corresponding to different average block sizes per unit time is taken as its shoveling energy consumption coefficient, recorded as P c ; The historical transportation data includes the fuel consumption y of the transportation equipment per unit time. b and the average size c of the crushed stone transported b ; According to the corresponding relationship between fuel consumption and average block size in different historical transportation data, the corresponding relationship function y is constructed. b =f(c b ), the fuel consumption corresponding to different average block sizes per unit time is taken as its transportation energy consumption coefficient, recorded as P y .

[0015] Furthermore, the process of obtaining the crushing energy consumption coefficient of the crushing node includes: Get the strength of crushed stone with volume V at any diameter , is the strength of the crushed stone when the diameter is infinite, is the strength of the crushed stone at a specific diameter, both of which are measured experimentally, D is the expected diameter of the crushed stone, and D x is a specific diameter; Obtain the fracture energy of crushed stone at any diameter , G w is the fracture energy of the crushed stone when the diameter is infinite, G a is the fracture energy of crushed stone at a specific diameter. Both are measured experimentally to obtain the total amount of blocks at a specific diameter. , k is the preset unevenness index; When the crushed stone diameter of the crushing node changes from x to When the volume difference of the crushed stone before and after crushing is taken as its crushing volume , obtain the crushing energy consumption coefficient P of crushed stone with volume V into the desired diameter p ;

[0016]

[0017] Furthermore, a first evaluation coefficient is obtained according to the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient. The process of obtaining the optimal crushed stone size according to the first evaluation coefficient includes: In the shoveling node and the transportation node, the corresponding shoveling energy consumption coefficient and transportation energy consumption coefficient are obtained respectively by combining the relationship function with the single average block size. In the crushing node, the single average block size is used as the crushed stone diameter x before crushing, and the crushed stone diameter after crushing is x. As a preset fixed value to obtain the corresponding crushing energy consumption coefficient; Set corresponding weight values ​​for the shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient, respectively, and record them as Q c , Q y , Q p , get the first evaluation coefficient , use the exhaustive method to obtain the first evaluation coefficients corresponding to different average fragment sizes, and take the average fragment size corresponding to the smallest first evaluation coefficient as the optimal gravel fragment size.

[0018] Furthermore, the process of obtaining historical blasting data, building a blasting control model, and combining the drilling energy consumption coefficient and the blasting energy consumption coefficient to obtain the optimal blasting plan includes: The historical blasting data refers to the drilling parameters, explosive parameters, blasting degree, and lithology information of a single borehole, including hole depth, hole diameter, hole spacing, row spacing, explosive quantity, charge structure, charge density and length, average fragmentation of crushed stone, and rock characteristics and properties; Taking hole spacing, row spacing, charge structure, charge density and length, rock characteristics and properties as quantitative factors, a blasting control set is generated based on the hole depth, hole diameter, explosive quantity and corresponding average fragmentation of different boreholes, and the blasting control set is divided into a training set and a test set. Construct a convolutional neural network, use different hole depths, hole diameters, and explosive quantities in the training set as input data of the convolutional neural network, use the corresponding average blockiness in the training set as output data of the convolutional neural network, and train the convolutional neural network to obtain an initial convolutional neural network; The initial convolutional neural network is verified using the test set, and the initial convolutional neural network with a test error threshold less than or equal to the preset value is output as the corresponding blasting control model. The input data of the blasting control model are continuously adjusted by using an exhaustive method, and the hole depth, hole diameter, and explosive quantity corresponding to the optimal crushed stone size are incorporated into the same blasting plan; The hole depth and hole diameter are related to the downward pressure speed, action time and radius of the drill bit. The shoveling energy consumption coefficient under the corresponding hole depth and hole diameter and the blasting energy consumption coefficient under the corresponding explosive amount in a single blasting scheme are obtained. The weight values ​​corresponding to the drilling energy consumption coefficient and the blasting energy consumption coefficient are set as Q z , Q b , get the second evaluation coefficient

[0019] The second evaluation coefficients corresponding to different blasting schemes are obtained, and the blasting scheme corresponding to the smallest second evaluation coefficient is used as the optimal blasting scheme. In subsequent mine blasting operations, drilling and blasting are performed according to the obtained optimal blasting scheme.

[0020] The multi-node collaborative control method for open-pit mine blasting includes the following steps: Step S1: Divide the mine blasting operation into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Step S2: Obtain drilling energy consumption coefficient, blasting energy consumption coefficient, shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient of drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Step S3: Obtain a first evaluation coefficient based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient, obtain the optimal crushed stone size based on the first evaluation coefficient, obtain historical blasting data, and construct a blasting control model, and obtain the optimal blasting plan by combining the drilling energy consumption coefficient and the blasting energy consumption coefficient.

[0021] Compared with the prior art, the present invention has the following beneficial effects: By dividing the mine blasting operation into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes, and obtaining the energy consumption coefficients of different nodes, the present invention can divide the entire mine blasting process into different sub-processes for analysis, which is conducive to judging the energy consumption of different nodes and providing a technical basis for subsequent treatment methods to reduce energy consumption; By obtaining the first evaluation coefficient of crushed stone at different average particle sizes, the optimal crushed stone particle size corresponding to the minimum first evaluation coefficient can be effectively obtained. Under the optimal crushed stone particle size, the total energy consumption of the shoveling node, the transportation node, and the crushing node can be guaranteed to be the lowest. By constructing a blasting control model, the corresponding blasting plan can be obtained with the optimal gravel size as the target. By obtaining the second evaluation coefficient under different blasting plans, the optimal blasting plan can be effectively obtained. Under the optimal blasting plan, it is beneficial to ensure that the total energy consumption of drilling nodes and blasting nodes is minimized, which can significantly reduce the energy consumption of different nodes and enhance the coordination between different nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0023] like Figure 1 As shown in the figure, the open-pit mine blasting multi-node collaborative control system includes the following modules: Node division module, used to divide mine blasting operations into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Energy consumption evaluation module, used to obtain drilling energy consumption coefficient, blasting energy consumption coefficient, shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient of drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; A fragmentation evaluation module is used to obtain a first evaluation coefficient based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient, and to obtain an optimal crushed stone fragmentation based on the first evaluation coefficient; The blockiness control module is used to obtain historical blasting data and build a blasting control model, combining the drilling energy consumption coefficient and the blasting energy consumption coefficient to obtain the optimal blasting plan.

[0024] It should be further explained that, in the specific implementation process, the process of dividing the mine blasting operation into drilling node, blasting node, shoveling node, transportation node, and crushing node includes: The drilling node refers to the process of drilling a hole in the rock to provide space for placing explosives for subsequent blasting. It is usually carried out using a rotary drill rig, which is recorded as drilling equipment. The drilling includes vertical, horizontal, and inclined types. The drilling depth and diameter are determined according to the blasting design. The blasting node refers to the process of breaking rock and forming gravel by blasting explosives, including the type, quantity, location and detonation sequence of explosives, and the use of electric detonators, detonating cords or electronic detonators for detonation; The shoveling node refers to the process of transporting the crushed rocks after blasting to the transportation equipment, which is usually carried out by an excavator, loader, or rock rake, which is recorded as shoveling equipment; The transportation node refers to the process of transporting crushed stone from the blasting site to the processing site, which is usually carried out using dump trucks, belt conveyors or trains, which are recorded as transportation equipment; The crushing node refers to the process of crushing large pieces of gravel into small particles, which usually uses jaw, cone or impact crushers, recorded as crushing equipment. The small particles after crushing meet the requirements of mineral processing or other industrial uses.

[0025] It should be further explained that, in the specific implementation process, the process of obtaining the drilling energy consumption coefficient of the drilling node includes: Since the drilling node uses specific drilling equipment and changes the rock morphology, in the embodiment of the present invention, the corresponding drilling energy consumption coefficient is obtained by evaluating various data generated during the drilling process; During the drilling process, there is pressure work W Y and torque work W N , and at the same time there is friction energy E consumed when friction destroys the rock R and the compression energy E consumed when compressing and destroying the rock Y ;

[0026]

[0027] Where F is the pressure acting on the rock, v is the downward pressure speed of the drill bit of the drilling equipment, n is the speed of the drill bit, N is the torque of the drill bit, and t is the action time of the drill bit; The friction energy E R Equal to the bottom friction energy E d and lateral friction energy E c and the frictional energy of water E s sum;

[0028] in, is the bottom friction coefficient, which is 0.21, and R is the drill bit radius;

[0029] in, is the lateral friction coefficient, which is 0.2, K c is the preset lateral conversion factor, with a value range of 0.23;

[0030] in, is the standard density of water; The compression energy E Y Equal to the axial compression energy E z and the annular compression energy E h sum;

[0031]

[0032] The above is the pressure work, torque work, friction energy, and compression energy of a single borehole during the drilling process. The drilling energy consumption coefficient P of the single borehole is obtained. z ;

[0033] It should be further explained that, in the specific implementation process, the process of obtaining the blasting energy consumption coefficient, shoveling energy consumption coefficient, and transportation energy consumption coefficient of the blasting node, shoveling node, and transportation node includes: For the blasting node, since it does not use specific equipment for operation but is blasted by explosives, in the embodiment of the present invention, the amount of explosives in a single borehole is directly used as the blasting energy consumption coefficient of the single borehole, which is recorded as P b ; For the loading node and the transportation node, since they only undertake transportation operations and do not change the rock morphology, the corresponding loading energy consumption coefficient and transportation energy consumption coefficient are evaluated by obtaining the fuel consumption of the loading equipment and transportation equipment in the historical loading data and historical transportation data; The historical shovel loading data includes the fuel consumption y of the shovel loading equipment per unit time. a The average size of the crushed stone shoveled is c a The average particle size refers to the average diameter of each piece of crushed stone. According to the corresponding relationship between fuel consumption and average particle size in different historical shoveling data, a corresponding relationship function is constructed, which is recorded as y a =f(c a ), the fuel consumption corresponding to different average block sizes per unit time is taken as its shoveling energy consumption coefficient, recorded as P c ; The historical transportation data includes the fuel consumption y of the transportation equipment per unit time. b and the average size c of the crushed stone transported b , according to the corresponding relationship between fuel consumption and average block size in different historical transportation data, a corresponding relationship function is constructed, which is recorded as y b =f(c b ), the fuel consumption corresponding to different average block sizes per unit time is taken as its transportation energy consumption coefficient, recorded as P y .

[0034] It should be further explained that, in the specific implementation process, the process of obtaining the crushing energy consumption coefficient of the crushing node includes: Whether chemical energy or mechanical energy, energy is consumed in order to crush the gravel. The minimum energy consumed to crush a unit volume of gravel into a specific diameter is its fracture energy G. The fracture energy is twice the surface free energy. The surface free energy is It describes the extra energy on the surface of the material relative to the interior;

[0035] The energy consumed in crushing the gravel with a volume of V into small particles with a desired diameter of D is recorded as the first crushing energy consumption coefficient P a ;

[0036] Since the strength of crushed stone increases with decreasing diameter, the strength of crushed stone at any diameter is recorded as ;

[0037] in, is the strength of the crushed stone when the diameter is infinite, is the crushed stone strength at a specific diameter, both of which are measured experimentally, D x is a specific diameter, and the fracture energy of the crushed stone at any diameter is recorded as G d ;

[0038] Among them, G w is the fracture energy of the crushed stone when the diameter is infinite, G a is the fracture energy of the crushed stone under a specific diameter, both of which are measured experimentally to obtain the second crushing energy consumption coefficient P at this time b ;

[0039] Since the crushed stone is not a block with a single uniform diameter, but has a certain diameter distribution, the total amount of blocks R at a specific diameter is obtained;

[0040] Wherein, k is a preset unevenness index. As k decreases, the proportion of small-diameter blocks increases, and as k increases, the proportion of large-diameter blocks decreases. When the crushed stone diameter of the crushing node changes from x to When the volume difference of the crushed stone before and after crushing is taken as its crushing volume ;

[0041] Get the third crushing energy consumption coefficient P at this time p, and use it as the crushing energy consumption coefficient for crushing the gravel with volume V into the desired diameter;

[0042] It should be further explained that, in a specific implementation process, the first evaluation coefficient is obtained based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient. The process of obtaining the optimal crushed stone size based on the first evaluation coefficient includes: Since the average block size directly affects the above-mentioned shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient, obtaining an appropriate average block size can significantly reduce the energy consumption of the three nodes. In the shoveling node and transportation node, the shoveling energy consumption coefficient and transportation energy consumption coefficient can be directly obtained through the corresponding relationship function; In the crushing node, the average fragmentation is represented by the crushed stone diameter before crushing, that is, x, and the crushed stone diameter after crushing is x. As a preset fixed value for analysis, the average size will also directly affect the crushing energy consumption coefficient; Set corresponding weight values ​​for the shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient, respectively, and record them as Q c , Q y , Q p , obtain the corresponding first evaluation coefficient, recorded as S1;

[0043] The exhaustive method is used to obtain the first evaluation coefficients corresponding to different average fragment sizes, and the average fragment size corresponding to the smallest first evaluation coefficient is taken as the optimal crushed stone fragment size.

[0044] It should be further explained that, in the specific implementation process, the process of obtaining historical blasting data, building a blasting control model, and combining the drilling energy consumption coefficient and the blasting energy consumption coefficient to obtain the optimal blasting plan includes: The historical blasting data refers to the drilling parameters, explosive parameters, blasting degree, lithology information, etc. of a single borehole. The drilling parameters include hole depth, hole diameter, hole spacing, and row spacing. The explosive parameters include the explosive quantity, charge structure, charge density, and length of a single borehole. The blasting degree refers to the average fragmentation of the crushed rock after a single borehole blasting operation. The lithologic information refers to the rock characteristics and properties corresponding to a single mine blasting operation. The blasting control model is constructed by taking hole spacing, row spacing, charge structure, charge density and length, and lithologic information as quantitative factors and analyzing the hole depth, hole diameter, explosive charge amount, and corresponding average fragmentation of different boreholes. A blasting control set is generated based on the hole depth, hole diameter, explosive charge and average particle size of different boreholes, and the blasting control set is divided into a training set and a test set; Construct a convolutional neural network, use the hole depth, hole diameter, and explosive charge of different boreholes in the training set as input data of the convolutional neural network, use the corresponding average blockiness in the training set as output data of the convolutional neural network, and train the convolutional neural network to obtain an initial convolutional neural network; The initial convolutional neural network is verified using the test set, and the initial convolutional neural network with a test error threshold less than or equal to the preset value is output as the corresponding blasting control model. Taking the optimal crushed stone size as the output data, the exhaustive method is used to continuously adjust the input data of the blasting control model, and the hole depth, hole diameter, and explosive quantity corresponding to the output data equal to the optimal crushed stone size are included in the same blasting plan; The hole depth and hole diameter are related to the downward pressure speed, action time and radius of the drill bit. The shoveling energy consumption coefficient under the corresponding hole depth and hole diameter and the blasting energy consumption coefficient under the corresponding explosive amount in a single blasting scheme are obtained. The weight values ​​corresponding to the drilling energy consumption coefficient and the blasting energy consumption coefficient are set as Q z , Q b , obtain the corresponding second evaluation coefficient, recorded as S2;

[0045] The second evaluation coefficients corresponding to different blasting schemes are obtained, and the blasting scheme corresponding to the smallest second evaluation coefficient is used as the optimal blasting scheme. In subsequent mine blasting operations, drilling and blasting are performed according to the obtained optimal blasting scheme.

[0046] In an embodiment of the present invention, a multi-node collaborative control method for open-pit mine blasting is also included, comprising the following steps: Step S1: Divide the mine blasting operation into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Step S2: Obtain drilling energy consumption coefficient, blasting energy consumption coefficient, shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient of drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Step S3: obtaining a first evaluation coefficient based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient, and obtaining the optimal crushed stone size based on the first evaluation coefficient; Step S4: Obtain historical blasting data, build a blasting control model, and obtain the optimal blasting plan by combining the drilling energy consumption coefficient and the blasting energy consumption coefficient.

[0047] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Open-pit mine blasting multi-node collaborative control system, characterized by: Includes the following modules: Node division module, used to divide mine blasting operations into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Energy consumption evaluation module, used to obtain drilling energy consumption coefficient, blasting energy consumption coefficient, shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient of drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; A fragmentation evaluation module is used to obtain a first evaluation coefficient based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient, and to obtain an optimal crushed stone fragmentation based on the first evaluation coefficient; The blockiness control module is used to obtain historical blasting data and build a blasting control model, combining the drilling energy consumption coefficient and the blasting energy consumption coefficient to obtain the optimal blasting plan.

2. The open-pit mine blasting multi-node collaborative control system according to claim 1, characterized in that: The process of dividing mine blasting operations into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes includes: The drilling node refers to the process of drilling holes in rock to provide space for placing explosives for subsequent blasting. The blasting node refers to the process of breaking rock by blasting explosives to form gravel. The shoveling node refers to the process of loading the blasted gravel onto transportation equipment. The transportation node refers to the process of transporting the gravel from the blasting site to the processing site. The crushing node refers to the process of crushing large pieces of gravel into small particles.

3. The open-pit mine blasting multi-node collaborative control system according to claim 2, characterized in that: The process of obtaining the drilling energy consumption coefficient of the drilling node includes: Obtain the pressure work W during drilling Y and torque work W N , and the friction energy E consumed when friction destroys the rock R and the compression energy E consumed when compressing and destroying the rock Y ; Where F is the pressure acting on the rock, v is the downward pressure speed of the drill bit of the drilling equipment, n is the speed of the drill bit, N is the torque of the drill bit, and t is the action time of the drill bit; The friction energy E R Equal to the bottom friction energy E d and lateral friction energy E c and the frictional energy of water E s sum; in, is the bottom friction coefficient, R is the drill bit radius, is the lateral friction coefficient, K c is the preset lateral conversion factor, is the standard density of water; The compression energy E Y Equal to the axial compression energy E z and the annular compression energy E h sum; According to the pressure work, torque work, friction energy and compression energy of a single borehole during the drilling process, the drilling energy consumption coefficient P of the single borehole is obtained. z ; 。 4. The open-pit mine blasting multi-node collaborative control system according to claim 3, characterized in that: The process of obtaining the blasting energy consumption coefficient, shoveling energy consumption coefficient, and transportation energy consumption coefficient includes: For a blasting node, the amount of explosives in a single borehole is taken as the blasting energy consumption coefficient of the single borehole, which is recorded as P b ,For shoveling nodes and transportation nodes, obtain historical shoveling data and historical transportation data; The historical shovel loading data includes the fuel consumption y of the shovel loading equipment per unit time. a The average size of the crushed stone shoveled is c a , the average block size refers to the average diameter of each piece of gravel; According to the corresponding relationship between fuel consumption and average block size in different historical shovel loading data, the corresponding relationship function y is constructed. a =f(c a ), the fuel consumption corresponding to different average block sizes per unit time is taken as its shoveling energy consumption coefficient, recorded as P c ; The historical transportation data includes the fuel consumption y of the transportation equipment per unit time. b and the average size c of the crushed stone transported b ; According to the corresponding relationship between fuel consumption and average block size in different historical transportation data, the corresponding relationship function y is constructed. b =f(c b ), the fuel consumption corresponding to different average block sizes per unit time is taken as its transportation energy consumption coefficient, recorded as P y .

5. The open-pit mine blasting multi-node collaborative control system according to claim 4, characterized in that: The process of obtaining the crushing energy consumption coefficient of the crushing node includes: Get the strength of crushed stone with volume V at any diameter , is the strength of the crushed stone when the diameter is infinite, is the strength of the crushed stone at a specific diameter, both of which are measured experimentally, D is the expected diameter of the crushed stone, and D x is a specific diameter; Obtain the fracture energy of crushed stone at any diameter , G w is the fracture energy of the crushed stone when the diameter is infinite, G a is the fracture energy of crushed stone at a specific diameter. Both are measured experimentally to obtain the total amount of blocks at a specific diameter. , k is the preset unevenness index; When the crushed stone diameter of the crushing node changes from x to When the volume difference of the crushed stone before and after crushing is taken as its crushing volume , obtain the crushing energy consumption coefficient P of crushed stone with volume V into the desired diameter p ; 。 6. The open-pit mine blasting multi-node collaborative control system according to claim 5, characterized in that: The process of obtaining the first evaluation coefficient and the optimal crushed stone size includes: In the shoveling node and the transportation node, the corresponding shoveling energy consumption coefficient and transportation energy consumption coefficient are obtained respectively by combining the relationship function with the single average block size. In the crushing node, the single average block size is used as the crushed stone diameter x before crushing, and the crushed stone diameter after crushing is x. As a preset fixed value to obtain the corresponding crushing energy consumption coefficient; Set corresponding weight values ​​for the shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient, respectively, and record them as Q c , Q y , Q p , get the first evaluation coefficient , use the exhaustive method to obtain the first evaluation coefficients corresponding to different average fragment sizes, and take the average fragment size corresponding to the smallest first evaluation coefficient as the optimal gravel fragment size.

7. The open-pit mine blasting multi-node coordinated control system according to claim 6, characterized in that: The process of building a blasting control model and obtaining the optimal blasting plan includes: The historical blasting data refers to the drilling parameters, explosive parameters, blasting degree, and lithology information of a single borehole, including hole depth, hole diameter, hole spacing, row spacing, explosive quantity, charge structure, charge density and length, average fragmentation of crushed stone, and rock characteristics and properties; Taking hole spacing, row spacing, charge structure, charge density and length, rock characteristics and properties as quantitative factors, a blasting control set is generated based on the hole depth, hole diameter, explosive quantity and corresponding average fragmentation of different boreholes, and the blasting control set is divided into a training set and a test set. Construct a convolutional neural network, use different hole depths, hole diameters, and explosive quantities in the training set as input data of the convolutional neural network, use the corresponding average blockiness in the training set as output data of the convolutional neural network, and train the convolutional neural network to obtain an initial convolutional neural network; The initial convolutional neural network is verified using the test set, and the initial convolutional neural network with a test error threshold less than or equal to the preset value is output as the corresponding blasting control model. The input data of the blasting control model are continuously adjusted by using an exhaustive method, and the hole depth, hole diameter, and explosive quantity corresponding to the optimal crushed stone size are incorporated into the same blasting plan; The hole depth and hole diameter are related to the downward pressure speed, action time and radius of the drill bit. The shoveling energy consumption coefficient under the corresponding hole depth and hole diameter and the blasting energy consumption coefficient under the corresponding explosive amount in a single blasting scheme are obtained. The weight values ​​corresponding to the drilling energy consumption coefficient and the blasting energy consumption coefficient are set as Q z , Q b , get the second evaluation coefficient The second evaluation coefficients corresponding to different blasting schemes are obtained, and the blasting scheme corresponding to the smallest second evaluation coefficient is used as the optimal blasting scheme. In subsequent mine blasting operations, drilling and blasting are performed according to the obtained optimal blasting scheme.

8. A multi-node collaborative control method for open-pit mine blasting, which is implemented based on the multi-node collaborative control system for open-pit mine blasting according to any one of claims 1 to 7, characterized in that: The method comprises: Step S1: Divide the mine blasting operation into drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Step S2: Obtain drilling energy consumption coefficient, blasting energy consumption coefficient, shoveling energy consumption coefficient, transportation energy consumption coefficient, and crushing energy consumption coefficient of drilling nodes, blasting nodes, shoveling nodes, transportation nodes, and crushing nodes; Step S3: Obtain a first evaluation coefficient based on the shoveling energy consumption coefficient, the transportation energy consumption coefficient, and the crushing energy consumption coefficient, obtain the optimal crushed stone size based on the first evaluation coefficient, obtain historical blasting data, and construct a blasting control model, and obtain the optimal blasting plan by combining the drilling energy consumption coefficient and the blasting energy consumption coefficient.

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