Excavation regulation and control and underground space rapid construction method based on system dynamics

Abstract

The invention discloses a mining regulation and underground space rapid construction method based on system dynamics, and relates to the technical field of mining engineering, and the method comprises the following steps: 1, mining system boundary modeling and key parameter identification; step 2, mining coupling mechanism and multi-loop feedback network modeling; step 3, construction of a mining cooperative dynamical model and development of a structural equation; and 4, performing production dynamic response simulation and production optimization decision making, and giving an evaluation conclusion through multivariate comprehensive judgment. According to the invention, multi-source parameter dynamic modeling including the tunneling subsystem and the coal mining subsystem is established, so that the excavation efficiency and safety control are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mining engineering, and particularly to a dynamic coordination and control method for excavation and mining based on a system dynamics model and an underground space rapid construction system. It is applicable to the dynamic coordination control of coal mine roadway driving and coal face advancing, especially for the multi-factor coupling analysis and real-time optimization of the excavation and mining system under deep complex geological conditions. Background Technique

[0002] The following technical bottlenecks exist in the current construction of underground space:

[0003] 1. Dynamic imbalance between excavation and mining: In traditional excavation and mining plans, it is often difficult to accurately grasp the reasonable ratio of driving and mining. When the driving speed cannot keep up with the mining speed, it will lead to a reduction in recoverable reserves, a situation of tight succession, and affect the continuous and stable production of the mine. If excessive emphasis is placed on mining work and the development of driving roadways is insufficient, after a period of time, the recoverable area will shrink, and forced production suspension for driving operations will cause production interruption and economic losses. On the contrary, if the driving speed is too fast and the mining cannot keep up, it will cause the roadway to be idle for too long and increase the maintenance cost;

[0004] 2. Multi-factor coupling effect: Existing coupling evaluations usually only measure the coordination of excavation and mining work with a few indicators such as output and cost, and lack a systematic evaluation of the coupling effects of 11 key factors such as geological structure, ground pressure manifestation, and equipment status (see Table 1). It cannot accurately reflect the coupling relationship between the excavation and mining system and various factors such as geological conditions, equipment operation, and personnel allocation;

[0005] Table 1 Key influencing factors of the excavation and mining system

[0006] 3. Response lag: When sudden situations occur during the excavation and mining process, such as equipment failures and geological condition changes, the adjustment mechanism of traditional excavation and mining plans is not flexible and the response speed is slow. From discovering the problem to formulating and implementing a new plan, it takes a long time, which will lead to a decrease in production efficiency during this period and may even cause safety accidents;

[0007] 4. Low data utilization rate: Most existing evaluation methods are static and cannot timely reflect the dynamic changes of various factors during the excavation and mining process. The geological conditions of coal mines are complex and changeable. During the mining process, geological structures such as faults and gas outbursts may be encountered, and traditional evaluations cannot adjust the plan in real time to adapt to these changes, resulting in the disconnection between the excavation and mining plan and the actual situation. For example, the patent with the application number CN117519012A established an intelligent production regulation and management system for coal mines, but did not establish a dynamic mapping model between state variables (such as driving footage and advancing distance) and rate variables (driving speed and advancing speed). Summary of the Invention

[0008] In order to overcome the deficiencies of the prior art, the present invention provides a mining control and rapid underground space construction method based on system dynamics, solving the problems in the background art above.

[0009] The object of the present invention is achieved as follows. A mining control and rapid underground space construction method based on system dynamics includes:

[0010] Step 1: Modeling the boundary of the mining system and identifying key parameters;

[0011] Step 2: Modeling the coupling mechanism between mining and excavation and the multi-loop feedback network;

[0012] Step 3: Constructing the collaborative dynamics model of mining and excavation and developing the structural equation;

[0013] Step 4: Simulating the dynamic response of production and making production optimization decisions.

[0014] By defining the system boundary and identifying key factors, the research scope of the coal mining and tunneling subsystems is clarified. Twelve core influencing factors such as geological structure, mine pressure, equipment failure rate, etc. are screened and weighted. Based on causal relationships and feedback loops, a causal diagram is drawn to reveal the dynamic interaction mechanism between variables. Using the structural flow diagram and equation modeling, state variables, rate variables, and composite indicators are defined, and a non-linear structural equation is established with the help of Vensim software. Finally, by inputting actual data through dynamic simulation and result application, the sensitivity of the model is verified, the dynamic change curves of the tunneling and coal mining processes are output, bottleneck factors are identified, and optimization strategies are proposed, ultimately providing quantitative decision-making support for the mining replacement plan and safe production.

[0015] I. Clarifying the scope of the research object: The coal mining system and the tunneling system are included in the system boundary as core subsystems, and other irrelevant factors (such as the transportation system, ventilation system, etc.) are excluded. Twelve key factors affecting the mining and excavation efficiency are screened through Table 1, including geological structure, mine pressure level, water inflow, gas concentration, equipment failure rate, etc. Among them, the coal mining system additionally includes the roadway mine pressure factor.

[0016] II. Variable classification and weight assignment: Variables are divided into level variables (such as tunneling footage), rate variables (such as tunneling speed), auxiliary variables (such as working environment level), and constants (such as normal advancing speed), and weights are assigned to each index (such as W1 - W 26 ), reflecting the influence degree of different factors on the system.

[0017] For the tunneling system, nine causal chains are established ( Figure 2 );

[0018] For the coal mining system, eleven causal chains are established (Figure 3 )

[0019] The so-called mining - tunneling system coupling: Through Figure 4 reflect the direct impact of tunneling footage on coal - mining advancing speed.

[0020] The cause - effect diagram of the mining - tunneling system is established based on the tunneling system and the coal - mining system. The relationship between the two mainly reflects the impact of tunneling footage on the advancing distance of the working face.

[0021] The so - called structural flow - chart design ( Figure 5 )

[0022] Use Vensim software to construct a dynamic model, including:

[0023] 1. State variables: Tunneling footage (cumulative quantity), coal - mining advancing distance;

[0024] 2. Rate variables: Tunneling speed, advancing speed of the working face;

[0025] 3. Auxiliary variables: Geological structure level, equipment failure level, etc.

[0026] The so - called structural equation design. According to the principles of system dynamics, the main structural equations of this system are as follows:

[0027] The so - called tunneling footage = original tunneling footage + tunneling speed*(DT) / / flow - level equation;

[0028] The so - called tunneling speed = IF THEN ELSE(tunneling footage < target tunneling footage, normal tunneling speed*(influence degree of geological structure level of the tunneling face on tunneling speed*W1 + influence degree of working environment level of the tunneling face on tunneling speed*W2 + influence degree of regular cycle level of the tunneling face on tunneling speed*W3 + influence degree of starting - up level of the tunneling face on tunneling speed*W4 + influence degree of mechanical equipment failure level of coal - mining on the tunneling face speed*W5), 0)

[0029] Among them, W1 represents the weight corresponding to the geological structure level in the influence degree of the geology of the tunneling face on tunneling speed; W2 represents the weight corresponding to the working environment level in the influence degree of the geology of the tunneling face on tunneling speed; W3 represents the weight corresponding to the regular cycle level in the influence degree of the geology of the tunneling face on tunneling speed; W4 represents the weight corresponding to the starting - up level in the influence degree of the geology of the tunneling face on tunneling speed; W5 represents the weight corresponding to the mechanical equipment failure level in the influence degree of the geology of the tunneling face on tunneling speed, And 0 ≤ W i ≤ 1.

[0030] The operation environment level of the heading face = the mine pressure level of the heading face * W6 + the gas level of the heading face * W7 + the mine water level of the heading face * W8;

[0031] Among them, W6 represents the weight corresponding to the mine pressure level in the heading face; W7 represents the weight corresponding to the gas level in the heading face; W8 represents the weight corresponding to the mine water level in the heading face. And 0 ≤ W i ≤ 1.

[0032] The mine pressure level of the heading face = the fragmentation degree of the roof of the heading roadway * W9 + the roof subsidence level of the heading face * W 10 + the convergence level of the two sides of the roadway 1 * W 11 (where W9 + W 10 + W 11 = 1);

[0033] Among them, W9 represents the weight corresponding to the fragmentation degree of the roof of the roadway in the heading face; W 10 represents the weight corresponding to the roof subsidence level in the heading face; W 11 represents the weight corresponding to the convergence level of the two sides of the roadway 1 in the heading face. And 0 ≤ W i ≤ 1.

[0034] The advancing distance of the coal mining face = the original advancing distance of the working face + the advancing speed of the working face * (DT) / / flow level equation;

[0035] The advancing speed of the working face = IF THEN ELSE (the advancing distance of the coal mining face < the target distance, the normal advancing speed of the working face * (the influence degree of the geological structure level of the coal mining face on the advancing speed of the working face * W 12 + the influence degree of the operation environment level of the coal mining face on the advancing speed of the working face * W 13 + the influence degree of the regular cycle level of the coal mining face on the advancing speed of the working face * W 14 + the influence degree of the starting level of the coal mining face on the advancing speed of the working face * W 15 + the influence degree of the mechanical equipment failure level of the coal mining face on the advancing speed of the working face * W 16 + the influence degree of the advanced support management level of the roadway on the advancing speed of the working face * W 17 + the influence degree of the heading speed on the advancing speed of the working face * W 18 ), 0);

[0036] Among them, W 12 represents the weight corresponding to the geological structure level in the influence degree of the coal mining face on the advancing speed of the working face; W 13Indicates the weight corresponding to the operation environment level in the influence degree of the coal mining face on the advancing speed of the working face; W 14 Indicates the weight corresponding to the regular mining level of the face in the influence degree of the coal mining face on the advancing speed of the working face; W 15 Indicates the weight corresponding to the starting level in the influence degree of the coal mining face on the advancing speed of the working face; W 16 Indicates the weight corresponding to the mechanical equipment failure level in the influence degree of the coal mining face on the advancing speed of the working face; W 17 Indicates the weight corresponding to the roadway advanced support management level in the influence degree of the coal mining face on the advancing speed of the working face; W 18 Indicates the weight corresponding to the tunneling speed in the influence degree of the coal mining face on the advancing speed of the working face, And 0 ≤ W i ≤ 1.

[0037] As described above, the operation environment level of the coal mining face = the mine pressure level of the coal mining face * W 19 + the gas level of the coal mining face * W 20 + the mine water level of the coal mining face * W 21 ;

[0038] Wherein, W 19 Indicates the weight corresponding to the mine pressure level in the coal mining face; W 20 Indicates the weight corresponding to the working face gas level in the coal mining face; W 21 Indicates the weight corresponding to the mine water level in the coal mining face, And 0 ≤ W i ≤ 1.

[0039] As described above, the mine pressure level of the coal mining face = the roof fragmentation degree of the coal mining face * W 22 + the roof subsidence level of the coal mining face * W 23 + the approaching situation of the two sides of the roadway * W 24 ;

[0040] Wherein, W 22 Indicates the weight corresponding to the roof fragmentation degree in the coal mining face; W 23 Indicates the weight corresponding to the roof subsidence level in the coal mining face; W 24 Indicates the weight corresponding to the approaching situation of the two sides of the roadway in the coal mining face, And 0 ≤ W i ≤ 1.

[0041] It is obtained that: the roadway advanced support management level = the roadway advanced support level * W 25 + the approaching level of the two sides of the roadway 2 * W 26 (Where W 25 + W26 = 1).

[0042] Among them, W 25 represents the weight corresponding to the advanced support level of the roadway in the coal mining face; W 26 represents the weight corresponding to the convergence level of the two sides of the roadway 2 in the coal mining face, and 0 ≤ W i ≤ 1.

[0043] The above-mentioned parameter assignment and data input include:

[0044] 1. Collect actual production data (such as the distance of the geological structure zone, the monthly average equipment failure rate), and set constants (normal tunneling speed, target advance distance);

[0045] 2. Determine the weights (W1 - W 26 ) through expert scoring or historical data fitting.

[0046] The above-mentioned simulation operation and verification include:

[0047] 1. Use Vensim for dynamic simulation and output the time series change curves of variables such as tunneling footage and advance speed;

[0048] 2. Sensitivity analysis: Adjust key parameters (such as the geological weight of W1), observe the fluctuations of the system output, and verify the robustness of the model.

[0049] The above-mentioned result application includes:

[0050] 1. Identify bottleneck factors (such as the significant impact of roof fragmentation on the working environment) and optimize the mining and excavation replacement plan;

[0051] 2. Develop control strategies: For example, increase the weight of equipment startup rate (W4) to improve the regular cycle level.

[0052] Aiming at the existing technical problems, a mining and excavation control and underground space rapid construction method based on system dynamics is provided. The beneficial effects that can be achieved are:

[0053] By integrating the system dynamics theory and the characteristics of mining and excavation technology, the present invention constructs a dynamic feedback model with multi-source parameter coupling of geology - equipment - environment, breaking through the limitations of traditional linear analysis methods. Aiming at the characteristics of non-linearity and strong coupling of the mining and excavation system, the analytic hierarchy process and weight matrix are innovatively introduced to quantify the interactive effects of 12 core parameters such as the distance of the geological structure zone and the roof fragmentation index, solving the pain points of strong subjectivity in weight allocation and fuzzy parameter correlation in traditional empirical decision-making. Through the dynamic structural equation established by Vensim software, the non-linear simulation prediction of key indicators such as tunneling speed and advance distance is realized, which is significantly better than the static planning method.

[0054] The dynamic feedback mechanism of the present invention significantly improves the collaborative efficiency of mining and excavation and the level of safety control. When the geological structure approaches the critical range, the system can identify the trend of footage attenuation in advance through dynamic weight adjustment, providing a key decision-making window for the implementation of advanced support measures; combined with sensitivity analysis, it accurately locates the sensitivity of high-risk parameters such as roof fragmentation, guiding on-site enhanced monitoring and prevention and control measures, and effectively reducing the incidence of roof accidents. Through the optimized output of the dynamic planning model for mining and excavation succession, the spatio-temporal matching and coordination of the advancement of the working face and the roadway driving are realized, significantly improving the problem of imbalance between mining and excavation in industrial applications and simultaneously reducing the frequency of unplanned equipment shutdowns.

[0055] The present invention provides core algorithm support for the intelligent transformation of coal mines. Its digital twin simulation module can map the underground working conditions in real time, supporting managers to optimize the production plan through parameter inversion; combined with the dynamic planning model, it realizes the autonomous decision-making of mining and excavation succession for the first time, and the response speed has been significantly improved compared with manual decision-making. This technology has formed a complete patent pool including system modeling methods, parameter fusion algorithms and decision support systems. Its multi-feedback network modeling framework can be extended to fields such as metal mines and tunnel engineering, providing a general solution for the intelligent management and control of complex underground engineering systems, and having significant industry demonstration value. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a technical solution diagram of the present invention.

[0057] Figure 2 It is a causal loop diagram of the tunneling system.

[0058] Figure 3 It is a causal loop diagram of the coal mining system.

[0059] Figure 4 It is a causal relationship diagram of the mining-excavation system.

[0060] Figure 5 It is a structural flow diagram of the mining-excavation system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0061] To make the objectives, technical solutions and advantages of the present application clearer, the present invention will be further described in detail below with reference to the embodiments and the drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0062] The present invention provides a mining and excavation regulation and underground space rapid construction method based on system dynamics. Please refer to Figure 1 as shown Figure 1Technical solution diagram of a mining control and underground space rapid construction method based on system dynamics provided by the present invention, including: mining system boundary modeling and key parameter identification; mining coupling mechanism and multi-loop feedback network modeling; mining collaborative dynamics model construction and structural equation development; production dynamic response simulation and production optimization decision-making.

[0063] The specific steps are as follows:

[0064] Step 1. Mining system boundary modeling and key parameter identification

[0065] Step 1.1. Define the scope of the research object

[0066] Include the coal mining system and the tunneling system as the core subsystems in the system boundary, and exclude other irrelevant factors (such as the transportation system, ventilation system, etc.). Through Table 1, 12 key factors affecting the mining efficiency are selected, including geological structure, mine pressure level, water inflow, gas concentration, equipment failure rate, etc. Among them, the coal mining system additionally includes the roadway mine pressure factor.

[0067] Step 1.2. Variable classification and weight assignment

[0068] Divide the variables into level variables (such as tunneling footage), rate variables (such as tunneling speed), auxiliary variables (such as working environment level), and constants (such as normal advancing speed), and assign weights to each index based on Table 2 (such as W1 - W 26 ), reflecting the influence degree of different factors on the system.

[0069] Table 2 Model weight table

[0070] Step 2. Mining coupling mechanism and multi-loop feedback network modeling

[0071] Step 2.1. Tunneling system: Establish 9 groups of causal chains ( Figure 2 )

[0072] The starting rate of mechanical equipment at the tunneling face ↑ → (+) The starting level at the tunneling face ↑ → (+) The tunneling footage of the roadway ↑;

[0073] The failure rate of mechanical equipment at the tunneling face ↑ → (-) The failure level of mechanical equipment at the tunneling face ↓ → (-) The tunneling footage of the roadway ↓;

[0074] The water inflow per unit time at the tunneling face ↑ → (-) The mine water level at the tunneling face ↓ → The working environment level at the tunneling face ↓ → (-) The tunneling footage of the roadway ↓;

[0075] The gas concentration in the return air flow at the tunneling face ↑ → (-) The gas level at the tunneling face ↓ → (-) The working environment level at the tunneling face ↓ → (-) The tunneling footage ↓;

[0076] Degree of fragmentation of the roof of the driving roadway ↑ → (-) Mine pressure level of the driving face ↓ → (-) Working environment level of the driving face ↓ → (-) Driving footage ↓;

[0077] Roof subsidence of the driving roadway ↑ → (-) Mine pressure level of the driving roadway ↓ → (+) Working environment level of the driving face ↓ → (-) Driving footage ↓;

[0078] Convergence of the two sides of the roadway ↑ → (-) Mine pressure level of the driving roadway ↓ → (+) Working environment level of the driving face ↓ → (-) Driving footage ↓;

[0079] Distance from the driving face to the geological structure zone ↑ → (+) Geological structure level of the driving face ↑ → (+) Driving footage ↑;

[0080] Regular cycle rate of the driving face ↑ → (+) Regular cycle level of the driving face ↑ → (+) Driving footage ↑.

[0081] Step 2.2, Coal mining system: Establish 11 groups of causal chains ( Figure 3 )

[0082] Startup rate of mechanical equipment in the coal mining face ↑ → (+) Startup level of the coal mining face ↑ → (+) Face advance distance ↑;

[0083] Failure rate of mechanical equipment in the coal mining face ↑ → (-) Failure level of mechanical equipment in the coal mining face ↓ → (-) Face advance distance ↓;

[0084] Water inflow per unit time in the coal mining face ↑ → (-) Mine water level in the coal mining face ↓ → Working environment level of the coal mining face ↓ → (-) Face advance distance ↓;

[0085] Gas concentration in the return air flow of the coal mining face ↑ → (-) Gas level in the coal mining face ↓ → (-) Working environment level of the coal mining face ↓ → (-) Face advance distance ↓;

[0086] Degree of fragmentation of the roof of the coal mining face ↑ → (-) Mine pressure level of the coal mining face ↓ → (-) Working environment level of the coal mining face ↓ → (-) Face advance distance ↓;

[0087] Roof subsidence of the coal mining face ↑ → (-) Mine pressure level of the coal mining face ↓ → (+) Working environment level of the coal mining face ↓ → (-) Face advance distance ↓;

[0088] Rate of convergence of the two sides ↑ → (-) Mine pressure level of the coal mining face ↓ → (-) Working environment level of the coal mining face ↓ → (-) Face advance distance ↓;

[0089] Distance between coal mining face and geological structure zone↑→(+) Geological structure level of driving face↑→(+) Driving footage↑;

[0090] Convergence of both sides of roadway↑→(-) Mine pressure level of roadway↓→(-) Advancing distance of working face↓;

[0091] Advance support distance of roadways at both ends of coal mining face↑→(-) Mine pressure level of roadway↓→(-) Advancing distance of working face↓;

[0092] Regular cycle rate of driving face↑→(+) Regular cycle level of driving face↑→(+) Driving footage↑.

[0093] Step 2.3, Coupling of coal mining - driving system: Through Figure 4 reflect the direct influence of driving footage on the coal - mining advancing speed.

[0094] The causal relationship diagram of the coal - mining - driving system is established on the basis of the driving system and the coal - mining system. The relationship between the two mainly reflects the influence of driving footage on the advancing distance of the working face.

[0095] Step 3, Construction of coal - mining and driving collaborative dynamics model and development of structural equation

[0096] Step 3.1, Design of structural flow diagram( Figure 5 )

[0097] Use Vensim software to construct a dynamic model, including:

[0098] 1. State variables: Driving footage (cumulative amount), Advancing distance of coal mining;

[0099] 2. Rate variables: Driving speed, Advancing speed of working face;

[0100] 3. Auxiliary variables: Geological structure level, Equipment failure level, etc.

[0101] Step 3.2, Design of structural equation

[0102] According to the principles of system dynamics, the main structural equations of this system are as follows:

[0103] 1. Driving footage = Original driving footage + Driving speed*(DT) / / Flow - level equation;

[0104] 2. Driving speed = IF THEN ELSE (driving footage < target driving footage, normal driving speed * (influence degree of geological structure level of driving face on driving speed * W1 + influence degree of working environment level of driving face on driving speed * W2 + influence degree of regular cycle level of driving face on driving speed * W3 + influence degree of starting level of driving face on driving speed * W4 + influence degree of mechanical equipment failure level of coal mining on driving face speed * W5), 0)

[0105] Among them, W1 represents the weight corresponding to the geological structure level in the influence degree of geology of the driving face on the driving speed; W2 represents the weight corresponding to the working environment level in the influence degree of geology of the driving face on the driving speed; W3 represents the weight corresponding to the regular cycle level in the influence degree of geology of the driving face on the driving speed; W4 represents the weight corresponding to the starting level in the influence degree of geology of the driving face on the driving speed; W5 represents the weight corresponding to the mechanical equipment failure level in the influence degree of geology of the driving face on the driving speed, and 0 ≤ W i ≤ 1.

[0106] 3. Working environment level of the driving face = mine pressure level of the driving face * W6 + gas level of the driving face * W7 + mine water level of the driving face * W8;

[0107] Among them, W6 represents the weight corresponding to the mine pressure level in the driving face; W7 represents the weight corresponding to the gas level in the driving face; W8 represents the weight corresponding to the mine water level in the driving face, and 0 ≤ W i ≤ 1.

[0108] 4. Mine pressure level of the driving face = fragmentation degree of the roof of the driving roadway * W9 + roof subsidence level of the driving face * W 10 + convergence level of the two sides of the roadway 1 * W 11 (where W9 + W 10 + W 11 = 1);

[0109] Among them, W9 represents the weight corresponding to the fragmentation degree of the roof of the roadway in the driving face; W 10 represents the weight corresponding to the roof subsidence level in the driving face; W 11 represents the weight corresponding to the convergence level of the two sides of the roadway 1 in the driving face, and 0 ≤ W i ≤ 1.

[0110] 5. Advancing distance of the coal mining face = original advancing distance of the working face + advancing speed of the working face * (DT) / / flow level equation;

[0111] 6. Working face advance speed = IF THEN ELSE (the advance distance of the coal mining face < the target distance, the normal advance speed of the working face * (the influence degree of the geological structure level of the coal mining face on the working face advance speed * W 12 + the influence degree of the working environment level of the coal mining face on the working face advance speed * W 13 + the influence degree of the regular cycle level of the working face of the coal mining face on the working face advance speed * W 14 + the influence degree of the starting level of the coal mining face on the working face advance speed * W 15 + the influence degree of the mechanical equipment failure level of the coal mining face on the working face advance speed * W 16 + the influence degree of the roadway advanced support management level on the working face advance speed * W 17 + the influence degree of the tunneling speed on the working face advance speed * W 18 ), 0);

[0112] Among them, W 12 represents the weight corresponding to the geological structure level in the influence degree of the coal mining face on the working face advance speed; W 13 represents the weight corresponding to the working environment level in the influence degree of the coal mining face on the working face advance speed; W 14 represents the weight corresponding to the regular cycle level of the working face in the influence degree of the coal mining face on the working face advance speed; W 15 represents the weight corresponding to the starting level in the influence degree of the coal mining face on the working face advance speed; W 16 represents the weight corresponding to the mechanical equipment failure level in the influence degree of the coal mining face on the working face advance speed; W 17 represents the weight corresponding to the roadway advanced support management level in the influence degree of the coal mining face on the working face advance speed; W 18 represents the weight corresponding to the tunneling speed in the influence degree of the coal mining face on the working face advance speed, and 0 ≤ W i ≤ 1.

[0113] 7. The working environment level of the coal mining face = the mine pressure level of the coal mining face * W 19 + the gas level of the coal mining face * W 20 + the mine water level of the coal mining face * W 21 ;

[0114] Among them, W 19 represents the weight corresponding to the mine pressure level in the coal mining face; W 20 represents the weight corresponding to the gas level of the working face in the coal mining face; W 21 represents the weight corresponding to the mine water level in the coal mining face, and 0 ≤ Wi ≤ 1.

[0115] 8. The mine pressure level of the coal mining face = the roof fragmentation degree of the coal mining face * W 22 + the roof subsidence level of the coal mining face * W 23 + the approaching situation of the two sides of the roadway * W 24 ;

[0116] Among them, W 22 represents the weight corresponding to the roof fragmentation degree in the coal mining face; W 23 represents the weight corresponding to the roof subsidence level in the coal mining face; W 24 represents the weight corresponding to the approaching situation of the two sides of the roadway in the coal mining face, and 0 ≤ W i ≤ 1.

[0117] It is obtained that: the advanced support management level of the roadway = the advanced support level of the roadway * W 25 + the approaching level of the two sides of the roadway 2 * W 26 (where W 25 + W 26 = 1).

[0118] Among them, W 25 represents the weight corresponding to the advanced support level of the roadway in the coal mining face; W 26 represents the weight corresponding to the approaching level of the two sides of the roadway 2 in the coal mining face, and 0 ≤ W i ≤ 1.

[0120] Step 4. Production dynamic response simulation and production optimization decision-making

[0121] Step 4.1. Parameter assignment and data input

[0122] Collect actual production data (such as the distance of the geological structure zone, the monthly average equipment failure rate), and set constants (normal tunneling speed, target advancing distance);

[0123] Determine the weights (W1 - W 26 ) through expert scoring or historical data fitting.

[0124] Step 4.2. Simulation operation and verification

[0125] Use Vensim for dynamic simulation and output the time series change curves of variables such as tunneling footage and advancing speed;

[0126] Sensitivity analysis: Adjust the key parameters (such as W1 geological weight), observe the system output fluctuations, and verify the robustness of the model.

[0127] Step 4.3. Result application

[0128] Identify bottleneck factors (such as the significant impact of roof fragmentation on the operating environment) and optimize the mining succession plan;

[0129] Formulate control strategies: for example, increase the weight of equipment operating rate (W4) to improve the regular cycle level.

[0130] Compared with the prior art, the present invention has the following beneficial effects:

[0131] 1. By integrating system dynamics theory with mining process characteristics, a dynamic feedback model of geological-equipment-environment multi-source parameter coupling was constructed, breaking through the limitations of traditional linear analysis methods. In view of the nonlinear and strongly coupled characteristics of the mining system, the hierarchical analysis method and weight matrix were innovatively introduced to quantify the interactive effects of 12 core parameters such as geological structural belt distance and roof crushing index, solving the pain points of strong subjectivity in weight allocation and fuzzy parameter correlation in traditional empirical decision-making. Nonlinear simulation prediction of key indicators such as excavation speed and advancement distance was achieved, which was significantly better than the static planning method.

[0132] 2. The dynamic feedback mechanism of the present invention significantly improves the efficiency of mining coordination and the level of safety control. When the geological structure is close to the critical range, the system can identify the trend of footage attenuation in advance through dynamic weight adjustment, providing a key decision-making window for the implementation of advanced support measures; combined with sensitivity analysis, it can accurately locate the sensitivity of high-risk parameters such as roof crushing, guide on-site enhanced monitoring and prevention and control measures, and effectively reduce the incidence of roof accidents. Through the optimized output of the mining and excavation succession dynamic programming model, the time and space matching and coordination of working face advancement and tunnel excavation is achieved, which significantly improves the problem of mining imbalance in industrial applications and simultaneously reduces the frequency of unplanned equipment shutdowns.

[0133] 3. It provides core algorithm support for the intelligent transformation of coal mines. Its digital twin simulation module can map underground working conditions in real time, and support managers to optimize production plans through parameter inversion; the combination of dynamic programming models has realized autonomous decision-making for mining and excavation for the first time, and the response speed has been significantly improved compared with manual decision-making. This technology has formed a complete patent pool including system modeling methods, parameter fusion algorithms and decision support systems. Its multi-feedback network modeling framework can be extended to metal mines, tunnel engineering and other fields, providing a universal solution for the intelligent management and control of complex underground engineering systems, and has significant industry demonstration value.

[0134] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A mining control and underground space rapid construction method based on system dynamics, characterized in that Including: Step 1, Modeling the boundary of the mining and excavation system and identifying key parameters; Step 2, Modeling the coupling mechanism between mining and excavation and the multi-loop feedback network; Step 3, Constructing the collaborative dynamics model of mining and excavation and developing the structural equation; Step 4, Simulating the production dynamic response and making production optimization decisions.

2. The method for mining regulation and rapid construction of underground space based on system dynamics according to claim 1, wherein: Modeling the boundary of the mining and excavation system and identifying key parameters; Including: Defining the scope of the research object: Incorporating the coal mining system and the tunneling system as the core subsystems into the system boundary, and excluding other irrelevant factors (such as the transportation system, ventilation system, etc.). Twelve key factors affecting the mining and excavation efficiency are screened out through Table 1, including geological structure, mine pressure level, water inflow, gas concentration, equipment failure rate, etc. Among them, the roadway mine pressure factor is additionally included in the coal mining system. Variable Classification and Weight Assignment: Variables are classified into horizontal variables (such as tunneling footage), rate variables (such as tunneling speed), auxiliary variables (such as working environment level), and constants (such as normal propulsion speed), and weights are assigned to each index (such as W1 - W 26 ), reflecting the influence degree of different factors on the system.

3. A method for mining regulation and rapid construction of underground space based on system dynamics according to claim 1, characterized in that: Modeling the coupling mechanism between mining and excavation and the multi-loop feedback network; Including: For the tunneling system described above: Establish 9 groups of causal chains (Figure 2); For the coal mining system described above: Establish 11 groups of causal chains (Figure 3); For the coupling of the mining - tunneling system described above: The direct influence of the tunneling footage on the coal mining advancing speed is reflected through Figure 4. The causal relationship diagram of the mining - tunneling system is established based on the tunneling system and the coal mining system, and the relationship between the two mainly reflects the influence of the tunneling footage on the advancing distance of the working face.

4. A method for mining regulation and rapid construction of underground space based on system dynamics according to claim 1, characterized in that: Constructing the collaborative dynamics model of mining and excavation and developing the structural equation; Including: Design of the structural flow diagram (Figure 5) Using Vensim software to construct a dynamic model, including: State variables: Tunneling footage (cumulative quantity), Coal mining advancing distance; Rate variables: Tunneling speed, Working face advancing speed; Auxiliary variables: Geological structure level, Equipment failure level, etc. Design of the structural equation described above. For the tunneling footage described above = Original tunneling footage + Tunneling speed * (DT) / / Flow position equation; For the tunneling speed described above = IF THEN ELSE (Tunneling footage < Target tunneling footage, Normal tunneling speed * (Influence degree of the geological structure level of the tunneling working face on the tunneling speed * W1 + Influence degree of the working environment level of the tunneling working face on the tunneling speed * W2 + Influence degree of the regular cycle level of the tunneling working face on the tunneling speed * W3 + Influence degree of the starting level of the tunneling working face on the tunneling speed * W4 + Influence degree of the mechanical equipment failure level of the coal mining on the tunneling face speed * W5), 0) Among them, W1 represents the weight corresponding to the geological structure level in the influence degree of the geology of the tunneling face on the tunneling speed; W2 represents the weight corresponding to the working environment level in the influence degree of the geology of the tunneling face on the tunneling speed; W3 represents the weight corresponding to the regular cycle level in the influence degree of the geology of the tunneling face on the tunneling speed; W4 represents the weight corresponding to the starting level in the influence degree of the geology of the tunneling face on the tunneling speed; W5 represents the weight corresponding to the mechanical equipment failure level in the influence degree of the geology of the tunneling face on the tunneling speed. And 0 ≤ W i ≤ 1. For the working environment level of the tunneling working face described above = Mine pressure level of the tunneling working face * W6 + Gas level of the tunneling working face * W7 + Mine water level of the tunneling working face * W8; Among them, W6 represents the weight corresponding to the mine pressure level in the driving face; W7 represents the weight corresponding to the gas level in the driving face; W8 represents the weight corresponding to the mine water level in the driving face, and 0 ≤ W i ≤ 1. The above-mentioned roadway pressure level in the driving face = the fragmentation degree of the roof of the driving roadway * W9 + the roof subsidence level of the driving face * W 10 + the approaching level of the two sides of the roadway * W 11 (where W9 + W 10 + W 11 = 1); Among them, W9 represents the weight corresponding to the degree of fragmentation of the roadway roof in the tunneling face; W 10 represents the weight corresponding to the roof subsidence level in the tunneling face; W 11 represents the weight corresponding to the approaching level 1 of the two sides of the roadway in the tunneling face, and 0 ≤ W i ≤ 1. For the advancing distance of the coal mining working face described above = Original working face advancing distance + Working face advancing speed * (DT) / / Flow position equation; The advancing speed of the working face = IF THEN ELSE (the advancing distance of the coal mining face < the target distance, the normal advancing speed of the working face * (the influence degree of the geological structure level of the coal mining face on the advancing speed of the working face * W 12 + the influence degree of the working environment level of the coal mining face on the advancing speed of the working face * W 13 + the influence degree of the regular cycle level of the coal mining face on the advancing speed of the working face * W 14 + the influence degree of the starting level of the coal mining face on the advancing speed of the working face * W 15 + the influence degree of the mechanical equipment failure level of the coal mining face on the advancing speed of the working face * W 16 + the influence degree of the advanced support management level of the roadway on the advancing speed of the working face * W 17 + the influence degree of the tunneling speed on the advancing speed of the working face * W 18 ), 0); Among them, W 12 represents the weight corresponding to the geological structure level in the influence degree of the coal mining face on the face advancing speed; W 13 represents the weight corresponding to the working environment level in the influence degree of the coal mining face on the face advancing speed; W 14 represents the weight corresponding to the face regular circulation level in the influence degree of the coal mining face on the face advancing speed; W 15 represents the weight corresponding to the machine starting level in the influence degree of the coal mining face on the face advancing speed; W 16 represents the weight corresponding to the mechanical equipment failure level in the influence degree of the coal mining face on the face advancing speed; W 17 represents the weight corresponding to the roadway advanced support management level in the influence degree of the coal mining face on the face advancing speed; W 18 represents the weight corresponding to the tunneling speed in the influence degree of the coal mining face on the face advancing speed, and 0 ≤ W i ≤ 1. The working environment level of the coal mining face = the strata pressure level of the coal mining face * W 19 + the gas level of the coal mining face * W 20 + the mine water level of the coal mining face * W 21 ; Among them, W 19 represents the weight corresponding to the strata pressure level in the coal mining face; W 20 represents the weight corresponding to the gas level in the coal mining face; W 21 represents the weight corresponding to the mine water level in the coal mining face, and 0 ≤ W i ≤ 1. The above-mentioned mine pressure level of the coal mining face = the fragmentation degree of the roof of the coal mining face * W 22 + the subsidence level of the roof of the coal mining face * W 23 + the approaching situation of the two sides of the roadway * W 24 ; Among them, W 22 represents the weight corresponding to the degree of roof fragmentation in the coal mining face; W 23 represents the weight corresponding to the roof subsidence level in the coal mining face; W 24 represents the weight corresponding to the approaching situation of both sides of the roadway in the coal mining face, and 0 ≤ W i ≤ 1. Obtained: Advance roadway support management level = Advance roadway support level * W 25 + Advance roadway support level on both sides of the roadway * 2 * W 26 (where W 25 + W 26 = 1). Among them, W 25 represents the weight corresponding to the advanced support level of the roadway in the coal mining face; W 26 represents the weight corresponding to the approaching level 2 of the two sides of the roadway in the coal mining face, and 0 ≤ W i ≤ 1.

5. A method for mining regulation and rapid construction of underground space based on system dynamics according to claim 1, characterized in that: Simulating the production dynamic response and making production optimization decisions. Including: The parameter assignment and data input described above include: Collecting actual production data (such as the distance of the geological structure zone, monthly average value of equipment failure rate), and setting constants (normal tunneling speed, target advancing distance); Determine the weights (W1 - W 26 ) by expert scoring or historical data fitting. The simulation operation and verification described above include: Using Vensim for dynamic simulation and outputting the time - series change curves of variables such as tunneling footage and advancing speed; Sensitivity analysis: Adjusting key parameters (such as the geological weight W1), observing the fluctuations of the system output, and verifying the robustness of the model. The result application described above includes: Identify bottleneck factors (such as the significant impact of roof fragmentation on the working environment), and optimize the mining and excavation replacement plan; Formulate control strategies: for example, increase the weight of equipment startup rate (W4) to improve the level of regular circulation.

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