Energy consumption and cost prediction method for the whole mining process based on drilling parameters

Abstract

The present invention proposes a method for predicting energy consumption and cost of the entire mining process based on drilling parameters, which relates to the technical field of energy consumption and economic cost measurement in metal mines. The method includes: obtaining drilling parameters of the drilling rig during the drilling process; evaluating the mechanical properties of the ore and the structural characteristics of the ore body to be blasted according to the obtained drilling parameters; calculating the average blasting fragmentation according to the obtained mechanical properties of the ore and the structural characteristics of the ore body, combined with the blasting design parameters; establishing a mathematical model of the average blasting fragmentation and the energy consumption and cost of each mining process; predicting the energy consumption and cost of the entire mining process of the ore body to be blasted according to the calculated average blasting fragmentation, combined with relevant mathematical models. The present invention can quickly predict the energy consumption and cost required for the entire mining process of the ore body to be blasted only through drilling operations in the initial process of mining production, which is of great significance to the optimization of mine energy consumption and cost.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption and economic cost calculation of metal mines, and in particular to a method for real-time prediction of energy consumption and cost of the entire mining and selection process based on drilling parameters. Background Art

[0002] The rapid development of the current world industrialization process has brought serious impacts on the global climate and ecological system. It has become a consensus among countries around the world to promote the green, low-carbon and high-quality development of industry. Mining is a production activity with extremely high energy consumption. Promoting the construction of green mines and realizing the design concept of energy saving, cost reduction and efficiency improvement in mines play an important role in achieving the "dual carbon" goals. To this end, there is an urgent need for a set of methods that can accurately evaluate the energy consumption and economic costs of the entire process of mining production activities, analyze the space and ways to optimize the energy consumption and cost of each mining process, and provide data basis and technical support for energy saving, cost reduction and efficiency improvement of mining enterprises.

[0003] The energy consumption and cost prediction method for the whole process of mining and selection should include two necessary beneficial effects. The first is that the method needs to quickly predict the energy consumption and cost of each process of mining and selection before the ore body is excavated. This can help mines adjust the equipment conditions or technical parameters of each process in a timely manner according to the predicted energy consumption and cost to maximize corporate benefits and reduce environmental pollution. The second is that the method can consider the mechanical properties and structural characteristics of the ore body and accurately predict the energy consumption and cost of mining and selection of ore bodies in different regions. This is because the mechanical properties of the ore body as a natural geological body have significant spatial variability, which leads to significant differences in the energy consumption and cost of ore mining and selection in different regions. Therefore, for ore bodies in different regions, it is a key problem that mines need to solve to quickly predict the energy consumption and cost required for each process of mining and selection before excavation. However, in the prior art, there is still a lack of a method that can quickly predict the energy consumption and cost of the whole process of mining and selection of ore bodies in different regions before ore mining, without the need for additional processes. Summary of the invention

[0004] In order to solve the above problems in the prior art, the present invention provides a method for predicting energy consumption and cost of the entire mining process based on measurement while drilling technology. The method can use drilling operations to predict the energy consumption and cost of the entire mining process in any blasting area in advance, and guide mining companies to arrange production plans. The method includes:

[0005] Obtain drilling parameters during the drilling process of the drilling rig;

[0006] Evaluate the mechanical properties and structural characteristics of the ore body to be blasted based on the obtained drilling parameters;

[0007] Calculate the average blasting fragmentation based on the obtained ore mechanical properties and ore body structural characteristics, as well as blasting design parameters;

[0008] Establish a mathematical relationship model between average blasting size and energy consumption and cost of each mining process;

[0009] Based on the average blasting fragmentation and mathematical relationship model, the energy consumption and cost of the entire mining process of the ore body to be blasted are predicted.

[0010] Furthermore, the acquisition of drilling parameters during the drilling process of the drilling rig includes: installing sensors on the drilling rig to obtain drilling parameters such as thrust, torque, drilling speed and rotation speed at different depths during the drilling process.

[0011] Furthermore, the mechanical properties of the ore include uniaxial compressive strength UCS, elastic modulus E, hardness index HF and ore density influence index RDI; the ore body structural characteristics include ore quality description index RMD, joint plane spacing index JPS and joint plane orientation index JPO.

[0012] Furthermore, the calculation of the average blasting fragmentation according to the obtained mechanical properties and structural characteristics of the ore body and the blasting design parameters includes:

[0013] According to the mechanical properties of the ore and the structural characteristics of the ore body, the ore coefficient A is calculated:

[0014] A=0.06(RMD+JPS+JPO+RDI+HF) (1)

[0015] Collect the current blasting design parameters, including the unit consumption of explosives q, the mass of explosives per hole Q and the power of explosives relative to TNT E';

[0016] According to the blasting design parameters and ore coefficient A, calculate the average blasting fragmentation x50:

[0017]

[0018] Furthermore, the mathematical relationship model between the average blasting size and the energy consumption and cost of each mining process is established, including:

[0019] A mathematical model of the relationship between the average blasting fragmentation x50 and the energy consumption of rock drilling, blasting, shoveling, transportation, crushing, and grinding is established, which are denoted as E1, E2, E3, E4, E5, and E6 respectively;

[0020] A mathematical model of the relationship between the average blasting fragmentation x50 and the economic costs of rock drilling, blasting, shoveling, transportation, crushing, and grinding is established, which are denoted as C1, C2, C3, C4, C5, and C6 respectively;

[0021] According to the actual working conditions of mining machinery and equipment, the parameters in the above-mentioned energy consumption relationship mathematical model and cost relationship mathematical model are calibrated to obtain the energy consumption relationship mathematical model and cost relationship mathematical model of each mining and selection process only related to x50.

[0022] Furthermore, the comprehensive energy consumption E total and comprehensive cost C total The mathematical models of the average blasting block size x50 are:

[0023] E total =E1+E2+E3+E4+E5+E6 (3)

[0024] C total =C1+C2+C3+C4+C5+C6 (4).

[0025] Furthermore, the mathematical models of the average blasting fragmentation x50 and the drilling energy consumption E1, blasting energy consumption E2, shoveling energy consumption E3, transportation energy consumption E4, crushing energy consumption E5, and grinding energy consumption E6 are:

[0026]

[0027]

[0028] Among them, L1 represents the drilling depth; P1 represents the drilling rig power; K1 represents the drilling efficiency; Q represents the charge per hole; E' represents the power of the explosive relative to TNT; Q v represents the explosive heat; V1 represents the bucket volume; K2 represents the shovel cycle; P2 represents the shovel power; δ1 represents the shovel full bucket coefficient, δ1=-0.021x50+1.63; P3 represents the truck power; K3 represents the truck transportation cycle; V2 represents the truck volume; δ2 represents the truck full bucket coefficient, δ2=-7×10 -5 x50+0.86; k1 represents the ratio of dynamic compressive strength to static compressive strength; p50 represents the crusher discharge block size; ρ represents ore density; P4 represents crusher no-load power; K4 represents crusher efficiency; SPI represents semi-autogenous grinding index; P80 represents 80% discharge particle size of semi-autogenous grinding; P5 represents semi-autogenous grinding no-load power; K5 represents semi-autogenous grinding efficiency, K5=-1.42x50+564.32.

[0029] Furthermore, the mathematical models of the relationship between the average blasting fragmentation x50 and the rock drilling cost C1, blasting cost C2, shoveling cost C3, transportation cost C4, crushing cost C5, and grinding cost C6 are:

[0030]

[0031]

[0032] C5=E5×P e +ρa5 (15)

[0033] C6=E6×Pe +ρa6 (16)

[0034] In the formula, R1 represents the fuel consumption of the drilling rig, a1 represents the labor and material cost required for drilling per hour, a2 represents the labor and material cost required for loading per unit mass of explosives, R2 represents the fuel consumption of the forklift, a3 represents the labor and material cost per unit time of shoveling, R3 represents the fuel consumption of the truck, a4 represents the labor and material cost per unit time of transportation, a5 represents the labor and material cost per ton of ore crushing, a6 represents the labor and material cost per ton of ore semi-autogenous grinding, P e represents the electricity price, P o Indicates oil price.

[0035] Furthermore, the method for evaluating the uniaxial compressive strength UCS, elastic modulus E, hardness index HF and ore density influence index RDI of the area to be blasted includes:

[0036] Based on the mechanical analysis of the interaction between the drill bit and the ore, the relationship expressions between the drilling rig parameters and the mechanical properties of the ore, UCS and E, are established by means of energy balance method, limit static equilibrium method, empirical model method or semi-empirical model method.

[0037] According to the drilling parameters of the drilling rig at different depths, the UCS and E at different depths are calculated;

[0038] The UCS and E at the average unit drilling depth are taken as the UCS and E of the area to be blasted;

[0039] Calculate the hardness index HF based on the obtained ore mechanical properties UCS and E:

[0040]

[0041] According to the ore density, the ore density impact index RDI is obtained:

[0042] RDI=25ρ-50 (18)

[0043] Where ρ is the density of the ore.

[0044] Furthermore, the relationship between the drilling rig parameters and the mechanical properties of the ore, UCS and E, is expressed as follows:

[0045]

[0046] Where F is the drilling rig thrust; d is the penetration per revolution, d = v / N, v is the drilling speed, and N is the rotation speed.

[0047] Further, the method for evaluating the ore quality description index RMD, the joint plane spacing index JPS and the joint plane orientation index JPO of the area to be blasted includes:

[0048] The ore quality index FI is proposed to describe the degree of ore crushing. FI is expressed as:

[0049]

[0050] Among them, PV is the drilling speed variability index, TV is the torque variability index, and the calculation formula is as follows:

[0051]

[0052] in, is the average drilling speed, is the average torque, i is the data sample number, and n is the total number of drilling data samples;

[0053] According to the calculated FI value, the ore quality description index RMD is determined, which is expressed as:

[0054]

[0055] The sudden change of drilling parameters or their derived parameters is used as the signal for structural surface identification, and the average spacing S of the structural surfaces is calculated by the ratio of the drilling length to the number of identified structural surfaces. j :

[0056]

[0057] Among them, n j is the number of structural surfaces identified, L1 is the drilling length;

[0058] According to the average spacing S j , determine the joint spacing index JPS:

[0059]

[0060] The values ​​of the joint plane orientation index JPO are as follows: when the joint plane is horizontal, JPO=10; when the joint plane inclination is consistent with the working plane, JPO=20; when the joint plane strike is perpendicular to the working plane, JPO=30; when the joint plane inclination is opposite to the working plane, JPO=40.

[0061] For a given mine, production technical parameters and equipment operating conditions are usually unchanged. Therefore, these mathematical models do not need to recalibrate model parameters when predicting energy consumption and costs in other blasting areas. Instead, the ore coefficient A and average blasting block size x50 calculated based on drilling parameters are substituted into these mathematical models to quickly obtain the energy consumption and economic cost of the entire mining process of the ore body.

[0062] Beneficial effects of the present invention: The present invention utilizes the drilling process to obtain the mechanical properties and ore body structural characteristics of the ore body to be blasted; the ore coefficient A is obtained based on the obtained mechanical properties and ore body structural characteristics of the ore; the average blasting block size x50 of the ore body to be blasted is obtained based on the ore coefficient A and the blasting design parameters; the energy consumption and cost of the entire mining process of the ore body to be blasted is obtained based on the obtained x50 and the establishment of a mathematical model of energy consumption and cost of each mining process. The method relies on the drilling process, does not require other additional processes, and can consider the mechanical properties and structural characteristics of different ore bodies, predict the energy consumption and cost of ore body production, and is of great significance to the optimization of mine production. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a flow chart of a method for predicting energy consumption and cost of the entire mining process based on drilling parameters provided by an embodiment of the present invention;

[0064] Figure 2 is the energy consumption of the whole process of unit volume ore mining and dressing provided by the embodiment of the present invention;

[0065] Figure 3 It is the economic cost of the entire process of unit volume ore mining and selection provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0066] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0067] Taking an open-pit mine as an example, a detailed description is given.

[0068] S1, obtaining the drilling parameters of the drilling rig during the drilling process;

[0069] Specifically, in this embodiment, the implementation process of the above S1 is as follows:

[0070] Pressure sensors are installed at the inlet and outlet ports of the feed cylinder of the fully hydraulic rotary drilling rig to calculate the drilling rig thrust F through the pressure difference; pressure sensors are installed at the inlet and outlet ports of the rotating cylinder to calculate the drilling rig torque T through the pressure difference; a pull rope displacement sensor is installed on the drilling rig power head to calculate the drilling speed v; a proximity switch is installed on the drill rod to calculate the rotation speed N.

[0071] S2, based on the obtained drilling parameters, evaluate the mechanical properties and structural characteristics of the ore body to be blasted;

[0072] Specifically, in this embodiment, the above S2 implementation process is as follows:

[0073] The mechanical properties of the ore evaluated include uniaxial compressive strength UCS, elastic modulus E, ore density influence index RDI and hardness index HF. Among them, the calculation method of uniaxial compressive strength UCS and elastic modulus E is as follows:

[0074] Based on the semi-empirical method, the relationship expressions between the drilling rig parameters and UCS and E are established.

[0075]

[0076] Where, d is the penetration per revolution, d = v / N.

[0077] Substitute the drill rig parameters obtained at different depths into equations (1)-(2) to obtain UCS and E at different depths;

[0078] The UCS and E at the average unit drilling depth are taken as the UCS and E of the area to be blasted. In this embodiment, the UCS is 6.57 MPa and the E is 1.58 GPa.

[0079] The hardness index HF is calculated as follows:

[0080]

[0081] In this embodiment, HF=0.527.

[0082] The ore density impact index RDI is calculated as follows:

[0083] RDI=25ρ-50 (4)

[0084] Where ρ is the density of the ore. In this embodiment, ρ is 2.3695 kg / m 3 , RDI is 9.2375.

[0085] The identified ore body structural characteristics include the ore quality description index RMD, the joint plane spacing index JPS and the joint plane orientation index JPO. The specific calculation method is as follows:

[0086] The ore quality description index RMD is determined as follows:

[0087] First, determine the index FI that characterizes the degree of ore crushing. The lower the FI, the better the ore integrity, and the higher the FI, the more crushed the ore:

[0088]

[0089] Among them, PV is the drilling speed variability index, TV is the torque variability index, and the calculation formula is as follows:

[0090]

[0091] in, is the average drilling speed, is the average torque, i is the data sample number, and n is the total number of drilling data samples.

[0092] According to the calculated FI value, the ore quality description index RMD is determined, which is expressed as:

[0093]

[0094] In this embodiment, the RMD is 30.

[0095] The identification method of the joint spacing index JPS is as follows:

[0096] Identify structural surfaces through structural surface recognition algorithms:

[0097]

[0098] In the formula, σ 2 v is the drilling speed variance; 2 T is the torque variance. A sudden increase in the parameter Fracturing indicates the presence of a structural surface. The average spacing S of the structural surfaces is calculated based on the number of structural surfaces identified. j :

[0099]

[0100] Among them, n j is the number of structural surfaces identified, and L1 is the drilling length.

[0101] According to S j The value of the joint spacing index JPS is obtained:

[0102]

[0103] In this embodiment, JPS is 50.

[0104] The joint plane orientation index JPO is determined based on the geological survey data of the mining area and the inclination of the working face:

[0105] When the joint surface is horizontal, JPO=10; when the joint surface inclination is consistent with the working surface, JPO=20; when the joint surface strikes perpendicular to the working surface, JPO=30; when the joint surface inclination is opposite to the working surface, JPO=40. In this embodiment, JPO is 10.

[0106] S3, calculate the average blasting fragmentation x50 based on the obtained ore mechanical properties and ore body structural characteristics, as well as blasting design parameters;

[0107] Specifically, in this embodiment, the above S3 implementation process is as follows:

[0108] According to the mechanical properties and structural characteristics of the ore body obtained in step S2, the ore coefficient A is calculated as follows:

[0109] A=0.06(RMD+JPS+JPO+RDI+HF) (12)

[0110] In this embodiment, A is 6.

[0111] According to the obtained ore coefficient A and blasting design parameters, the average blasting fragmentation x50 is calculated as follows:

[0112]

[0113] Wherein, q is the unit consumption of explosives, Q is the mass of explosives per hole, and E' is the power of explosives relative to TNT; these parameters can be determined according to the design parameters of mine blasting. In this embodiment, the values ​​of these parameters are shown in Table 1, and x50 is 35.54 cm.

[0114] S4, establish a mathematical model of x50 and the energy consumption and cost of each mining process;

[0115] Specifically, in this embodiment, the above S4 implementation process is as follows:

[0116] In the processes of rock drilling, blasting, shoveling, transportation, crushing and grinding, the energy consumption required to process a unit volume of ore is recorded as E1, E2, E3, E4, E5 and E6 respectively, and is calculated by the following formula in this embodiment:

[0117]

[0118] Table 1 Meaning and units of energy consumption mathematical model parameters

[0119]

[0120] In this embodiment, the meaning and value of each parameter in the formula are shown in Table 1, and these parameters can be determined according to the mine design, equipment working conditions and technical parameters. Among them, the full bucket coefficient δ1 of the forklift, the full bucket coefficient δ2 of the truck, and the efficiency K5 of the semi-autogenous mill are all related to the average blasting fragmentation x50, which are expressed as follows in the embodiment:

[0121] δ1=-0.021x50+1.63 (20)

[0122] δ2=-7×10 -5 x50+0.86 (21)

[0123] K5=-1.42x50+564.32 (22)

[0124] Substituting δ1 into E3, δ2 into E4, and K5 into E6, we can get the mathematical model of energy consumption of the whole mining process represented by x50. Further, we can get the comprehensive energy consumption of mining and dressing Etotal , expressed as:

[0125] E total =E1+E2+E3+E4+E5+E6 (23)

[0126] In the processes of rock drilling, blasting, shoveling, transportation, crushing and grinding, the economic costs required to process a unit volume of ore are recorded as C1, C2, C3, C4, C5 and C6 respectively, and are calculated by the following formula in this embodiment:

[0127]

[0128] C5=E5×P e +ρa5 (28)

[0129] C6=E6×P e +ρa6 (29)

[0130] Table 2 Meaning and units of cost mathematical model parameters

[0131]

[0132] In this embodiment, the meaning and value of each parameter in the formula are shown in Table 2. These parameters can be determined according to the actual situation of the mine. Substitute δ1 and δ2 represented by x50 into C3 and C4 respectively, and substitute E5 and E6 represented by x50 into C5 and C6 respectively, and the mathematical model of the whole process cost of mining and dressing represented by x50 can be obtained. Further, the comprehensive cost of mining and dressing C is obtained. total , expressed as:

[0133] C total =C1+C2+C3+C4+C5+C6 (30)

[0134] S5, based on the calculated x50 and the established mathematical relationship model, predict the energy consumption and cost of the entire mining process of the ore body to be blasted;

[0135] Substituting the obtained x50=35.54cm into the energy consumption mathematical model, see equations (14)-(19), the energy consumption of the whole mining process is obtained, as follows: Figure 2 Substituting the obtained x50=35.54cm into the cost mathematical model, see equations (24)-(29), the economic cost of the entire mining process is obtained, as shown in Figure 3 In addition, according to formula (23), the comprehensive energy consumption of mining and selection E is obtained total According to formula (30), the comprehensive cost of mining and selection C is obtained total In this embodiment, E total 25.207 kWh / m 3 , C total 25.80 yuan / m3 . Figure 2 and 3 The energy consumption and cost ratio of each mining process in this embodiment are intuitively displayed. Figure 2 and Figure 3 It can be seen that in this embodiment, the transportation energy consumption and semi-autogenous grinding energy consumption account for the highest proportion, accounting for approximately 44.35% and 47.71% of the total energy consumption respectively, and the transportation cost accounts for the highest proportion, accounting for approximately 40.2% of the total cost. Therefore, for the mine in this embodiment, optimizing the transportation distance is an important breakthrough in energy conservation and cost reduction. The present invention provides a powerful means for mine energy consumption, cost analysis and optimization, and provides key data support for the evaluation of the effect of green mine construction.

[0136] Finally, it should be noted that the above embodiments are intended to illustrate the technical solutions of the present invention and do not constitute any form of limitation on the present invention. Those skilled in the art should fully understand that it is completely feasible to modify the technical solutions described in the above embodiments or to perform equivalent replacements on any part or all of the technical features therein. These modifications or replacements, as long as they do not deviate from the scope of protection determined by the claims of the present invention, should be regarded as reasonable extensions of the present invention.

Claims

1. A method for predicting energy consumption and cost of the entire mining process based on drilling parameters, characterized in that: include: Obtain drilling parameters during the drilling process of the drilling rig; Evaluate the mechanical properties and structural characteristics of the ore body to be blasted based on the obtained drilling parameters; According to the mechanical properties of the ore and the structural characteristics of the ore body, as well as the blasting design parameters, the average blasting fragmentation is calculated; including: according to the mechanical properties of the ore and the structural characteristics of the ore body, the ore coefficient A is calculated: A=0.06(RMD+JPS+JPO+RDI+HF) (1) Among them, HF is the hardness index, RDI is the ore density influence index, RMD is the ore quality description index, JPS is the joint plane spacing index, and JPO is the joint plane orientation index; Collect current blasting design parameters including explosive consumption per unit, explosive mass per hole, and explosive power relative to TNT; According to the blasting design parameters and ore coefficient A, calculate the average blasting fragmentation x 50 : Among them, q is the unit consumption of explosives, Q is the mass of explosives per hole, and E' is the power of explosives relative to TNT; Establish a mathematical relationship model between the average blasting size and the energy consumption and cost of each mining process; including: Establish the average blasting block size x 50 The mathematical models related to the energy consumption of rock drilling, blasting, shoveling, transportation, crushing, and grinding are denoted as E1, E2, E3, E4, E5, and E6 respectively; Establish the average blasting block size x 50 The mathematical model of the relationship between the cost of rock drilling, blasting, shoveling, transportation, crushing, and grinding are denoted as C1, C2, C3, C4, C5, and C6 respectively; The parameters in the energy consumption relationship mathematical model and the cost relationship mathematical model established above are calibrated to obtain the 50 The energy consumption relationship mathematical model and cost relationship mathematical model of each relevant mining process; Based on the average blasting fragmentation and mathematical relationship model, the energy consumption and cost of the entire mining process of the ore body to be blasted are predicted.

2. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to claim 1 is characterized in that: The method of obtaining the drilling parameters of the drilling rig during the drilling process includes: installing sensors on the drilling rig to obtain the drilling parameters including thrust, torque, drilling speed and rotation speed at different depths during the drilling process.

3. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to claim 2 is characterized in that: The mechanical properties of the ore include uniaxial compressive strength UCS, elastic modulus E, hardness index HF and ore density influence index RDI; the structural characteristics of the ore body include ore quality description index RMD, joint plane spacing index JPS and joint plane orientation index JPO.

4. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to claim 3 is characterized in that: Comprehensive energy consumption of mining and selection E total and comprehensive cost C total The average blasting size x 50 The mathematical model is: E total =E1+E2+E3+E4+E5+E6 (3) C total =C1+C2+C3+C4+C5+C6 (4)。 5. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to any one of claims 1 to 4, characterized in that: Average blasting block size x 50 The mathematical models of rock drilling energy consumption E1, blasting energy consumption E2, shoveling energy consumption E3, transportation energy consumption E4, crushing energy consumption E5, and grinding energy consumption E6 are: Among them, L1 represents the drilling depth; P1 represents the drilling rig power; K1 represents the drilling efficiency; Q represents the mass of explosives per hole; E' represents the power of explosives relative to TNT; Q v represents the explosive heat; V1 represents the bucket volume; K2 represents the shovel cycle; P2 represents the shovel power; δ1 represents the shovel full bucket coefficient, δ1 = -0.021x 50 +1.63; P3 is the truck power; K3 is the truck transportation cycle; V2 is the truck volume; δ2 is the truck full bucket coefficient, δ2=-7×10 -5 x 50 +0.86; k1 indicates that the dynamic compressive strength is higher than the static compressive strength; p 50 represents the crusher discharge block size; ρ represents the ore density; P4 represents the crusher no-load power; K4 represents the crusher efficiency; SPI represents the semi-autogenous grinding index; P 80 Indicates the particle size of 80% of the semi-autogenous grinding; P5 indicates the no-load power of the semi-autogenous grinding; K5 indicates the efficiency of the semi-autogenous grinding, K5 = -1.42x 50 +564.

32.

6. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to claim 5 is characterized in that: Average blasting block size x 50 The mathematical models of the relationship with rock drilling cost C1, blasting cost C2, shoveling cost C3, transportation cost C4, crushing cost C5, and grinding cost C6 are: In the formula, R1 represents the fuel consumption of the drilling rig, a1 represents the labor and material cost required for drilling per hour, a2 represents the labor and material cost required for loading per unit mass of explosives, R2 represents the fuel consumption of the forklift, a3 represents the labor and material cost per unit time of shoveling, R3 represents the fuel consumption of the truck, a4 represents the labor and material cost per unit time of transportation, a5 represents the labor and material cost per ton of ore crushing, a6 represents the labor and material cost per ton of ore semi-autogenous grinding, P e represents the electricity price, P o Indicates oil price.

7. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to claim 3 is characterized in that: Methods for evaluating the uniaxial compressive strength UCS, elastic modulus E, hardness index HF and ore density influence index RDI of the area to be blasted include: The relationship expressions between the drilling rig parameters and the uniaxial compressive strength UCS and elastic modulus E are established: Where, F is the drilling rig thrust; d is the penetration per revolution, d = v / N, v is the drilling speed, and N is the rotation speed; According to the drilling parameters of the drilling rig at different depths, the uniaxial compressive strength UCS and elastic modulus E at different depths are calculated; The uniaxial compressive strength UCS and elastic modulus E at the average unit drilling depth are used as the uniaxial compressive strength UCS and elastic modulus E of the area to be blasted; The hardness index HF is calculated based on the obtained uniaxial compressive strength UCS and elastic modulus E: According to the ore density, the ore density impact index RDI is obtained: RDI=25ρ-50 (20) Where ρ is the density of the ore.

8. The method for predicting energy consumption and cost of the entire mining process based on drilling parameters according to claim 3 is characterized in that: The method for evaluating the ore quality description index RMD, the joint plane spacing index JPS and the joint plane orientation index JPO of the area to be blasted includes: proposing an ore quality index FI to describe the degree of ore crushing, and FI is expressed as: Among them, PV is the drilling speed variability index, TV is the torque variability index, and the calculation formula is as follows: in, is the average drilling speed, is the average torque, i is the data sample number, and n is the total number of drilling data samples; According to the calculated FI value, the ore quality description index RMD is determined, which is expressed as: The sudden change of drilling parameters or their derived parameters is used as the signal for structural surface identification, and the average spacing S of the structural surfaces is calculated by the ratio of the drilling length to the number of identified structural surfaces. j : Among them, n j is the number of structural surfaces identified, L1 is the drilling length; According to the average spacing S j , determine the joint spacing index JPS: The values ​​of the joint plane orientation index JPO are as follows: when the joint plane is horizontal, JPO=10; when the joint plane inclination is consistent with the working plane, JPO=20; when the joint plane strike is perpendicular to the working plane, JPO=30; when the joint plane inclination is opposite to the working plane, JPO=40.

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