Intelligent data acquisition and optimization control system applied to mine filling system

Abstract

The invention discloses an intelligent data acquisition and optimization control system applied to a mine filling system, and relates to the technical field of computer automatic control, the system comprises an ore body stress analysis unit, a filling slurry solid phase mass analysis unit, a filling body physical property analysis unit and a filling control and analysis unit; the ore body stress analysis unit is used for establishing a three-dimensional ore body geometric model according to an ore body geological exploration result, dividing the three-dimensional ore body geometric model into finite element grids and calculating the solid phase mass concentration of filling slurry; the filling body physical property analysis unit is used for establishing a rheological model of the filling slurry according to the solid phase mass concentration of the filling slurry; and the filling control and analysis unit is used for calculating the filling stability according to the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry to obtain a stability coefficient. The filling speed can be intelligently controlled, the construction stability is evaluated in real time, and the safety and high efficiency of the filling construction process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of computer automatic control, and in particular to an intelligent data acquisition and optimization control system applied to a mine filling system. Background Art

[0002] Underground cementitious filling technology is a green mining method widely used in mining. It supports the rock layer, reduces surface subsidence and controls ore body deformation by backfilling slurry into the goaf, thereby improving the safety and environmental friendliness of the mining process. With the increasing depletion of mining resources, the demand for deep mining is gradually increasing, and the requirements for green mining and sustainable development are becoming increasingly stringent. This has led to the gradual development of underground cementitious filling technology from simple manual control to a complex system that relies on automation and intelligent control. However, although the existing technology has made significant progress in filling material selection, slurry conveying equipment, construction technology, etc., there are still many deficiencies in system integration, dynamic control, and adaptability under complex ore body conditions.

[0003] In traditional underground cementing filling technology, commonly used filling materials mainly include cement-based slurry, fly ash-based slurry and tailings-based slurry. These materials are injected into the goaf by pumping or gravity conveying. Existing filling construction mostly adopts fixed parameter construction, that is, the slurry concentration, pumping speed and filling volume are set according to experience, and the construction process usually lacks the ability to respond to complex working conditions in real time. The typical cementing filling system includes slurry preparation equipment, conveying equipment and grouting equipment, etc. The operation of the system depends on manual monitoring, and its automation and intelligence level is relatively low. In terms of filling design, the existing technology usually uses a simplified mechanical model to make a preliminary estimate of the ore body stress and filling body strength. For example, some studies use the burial depth and lithology data of the ore body to estimate the initial ground stress of the ore body, while for the filling body strength, it is usually designed based on the experimentally measured solid phase concentration and cement ratio empirical values. However, this simplified model ignores the complexity of the three-dimensional stress field of the ore body and fails to fully consider the dynamic coupling of ore body stress, pore water pressure and filling body mechanical properties. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent data acquisition and optimization control system applied to a mine filling system. The present invention can intelligently control the filling speed, evaluate the construction stability in real time, and ensure the safety and efficiency of the filling construction process.

[0005] In order to solve the above technical problems, the present invention provides an intelligent data acquisition and optimization control system applied to a mine filling system, the system comprising: an ore body stress analysis unit, a filling slurry solid phase quality analysis unit, a filling body physical property analysis unit and a filling control and analysis unit; the ore body stress analysis unit is used to establish a three-dimensional ore body geometric model according to the ore body geological exploration results, divide the three-dimensional ore body geometric model into finite element grids, and calculate the three-dimensional stress tensor field of the ore body; the filling slurry solid phase quality analysis unit is used to calculate the solid phase mass concentration of the filling slurry according to the three-dimensional stress tensor field of the ore body; the filling body physical property analysis unit is used to establish a rheological model of the filling slurry according to the solid phase mass concentration of the filling slurry; the filling slurry solid phase quality analysis unit is used to calculate the solid phase mass concentration ... A rheological model of the filling slurry is used to construct a filling body strength prediction model to predict the filling body strength of the filling slurry at each time; and based on the predicted filling body strength of the filling slurry at each time, the pore water pressure of the filling slurry at each time is calculated; the filling control and analysis unit is used to calculate the stability of the filling according to the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry, and obtain the stability coefficient; the stability coefficient describes the ability of the ore body and the filling body to withstand external stress, and the higher the value, the stronger the ability of the ore body and the filling body to withstand external stress; according to the stability coefficient, the filling body strength and the pore water pressure, the preset filling speed control model is used to calculate the current optimal filling speed, and the optimal filling speed is used to control the filling slurry for filling.

[0006] Furthermore, the stress analysis unit of the ore body is set up, and the three-dimensional ore body geometric model is divided into finite element grids. The unit volume of each finite element grid is ; The three-dimensional stress tensor field of the ore body is calculated by the following formula : ; in, is the rock mass density of the ore body, which indicates the weight per unit volume of rock in the ore body; is the burial depth, which indicates the thickness of the rock layer covering the ore body; It represents the initial geostress coefficient, the ratio of horizontal stress to vertical stress, obtained through geostress measurement; The elastic modulus of the ore body is a material property that reflects the ability of the rock in the ore body to resist deformation. It is measured by laboratory uniaxial compression tests of rocks or by the sonic method. is Poisson's ratio, which describes the ratio of the lateral deformation to the longitudinal deformation of the rock, and takes a value of 0.2 or 0.4, which is determined by triaxial loading experiments; The position coordinates are The displacement at is obtained by numerical simulation based on the finite element method; is the Laplace operator The position coordinates are stress at is the divergence operator; The total volume of all finite element meshes.

[0007] Furthermore, the filling slurry solid phase mass analysis unit calculates the solid phase mass concentration of the filling slurry according to the three-dimensional stress tensor field of the ore body through the following formula: : ; in, is temperature; is the temperature influence coefficient, which is the preset value; is the residual yield stress, which describes the residual shear stress generated by the contact force of particles in the filling slurry and is determined by rheological experiments; is the maximum yield stress, is the maximum allowable shear stress, and is the set value; is the pressure influence coefficient, is the set value; is the critical pressure, indicating the maximum allowable pressure; is the porosity of the filling slurry; is the water density; is the solid phase density; is the standard pressure, is the set value; for The maximum value of is the median particle size, measured by laser particle size analyzer or sieving method; is the reference particle size; For pressure.

[0008] Furthermore, the filling body physical property analysis unit establishes a rheological model of the filling slurry according to the solid mass concentration of the filling slurry through the following formula; ; in, For time Shear stress at is the flow index; is the pressure loss; is the length of the pipeline; For time The filling speed of the filling slurry at ; is the pipe radius; is the solid phase volume fraction, which indicates the proportion of solid particles in the volume of the filling slurry; is the preset maximum solid volume fraction; is the preset minimum porosity; is the activation energy of the filling slurry.

[0009] Furthermore, the pressure loss Calculated using the following formula: ; in, is the gas constant.

[0010] Furthermore, the filling body physical property analysis unit constructs a filling body strength prediction model by combining the solid phase mass concentration of the filling slurry and the rheological model of the filling slurry through the following formula: ; in, Indicates that the solid mass concentration of the filling slurry is Maximum filling strength at ; is the characteristic time of the hydration reaction of the filling slurry, and the time when the hydration reaction of the filling slurry reaches 50% is determined by the hydration heat release experiment; Indicates when When the shear stress is , the temperature is The hydration rate at ; is the baseline hydration rate.

[0011] Furthermore, the filling body physical property analysis unit calculates the pore water pressure of the filling slurry at each time according to the predicted filling body strength of the filling slurry at each time by the following formula: ; in, For time The pore water pressure at The filling strength is The permeability coefficient at the time of filling is obtained according to the pre-established relationship between the filling body strength and the permeability coefficient; is the volume compression coefficient of the filling slurry, which indicates the ratio of the actual volume of the filling slurry to the volume of the pipeline; is the specific gravity of water.

[0012] Furthermore, the filling control and analysis unit uses the following formula to calculate the filling stability according to the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry to obtain the stability coefficient : ; in, is the critical pore water pressure, is the set value.

[0013] Furthermore, the filling control and analysis unit uses the following formula to calculate the current optimal filling speed based on the stability coefficient, filling body strength and pore water pressure using a preset filling speed control model: : .

[0014] The intelligent data acquisition and optimization control system applied to the mine filling system of the present invention has the following beneficial effects: The present invention uses an ore body stress analysis unit to accurately calculate the three-dimensional stress tensor field of the ore body, which makes up for the limitations of the traditional two-dimensional simplified model. The finite element method is used to combine the ore body geometry, fault distribution, lithology differences and goaf characteristics to comprehensively describe the stress distribution of the ore body under a complex mining environment. The three-dimensional stress tensor field calculation provides a scientific basis for the design of the filling body, especially the accurate prediction of the filling strength requirements in high stress concentration areas, which improves the pertinence and safety of the filling body design. In addition, the precise stress field analysis can also dynamically reflect the redistribution of ore body stress, providing a basis for real-time adjustment during the construction process. While ensuring construction safety, the present invention optimizes the efficiency and resource utilization of the filling construction. For example, through the filling speed control model, the present invention can dynamically optimize the construction speed while ensuring the performance of the filling body, avoiding unnecessary material waste; through the accurate calculation of the slurry solid phase mass concentration, the excessive use of high-concentration slurry is reduced, thereby reducing material costs.

[0015] In addition, the precise construction control of the present invention reduces disturbances to the ore body and the surrounding environment, helps reduce surface subsidence and environmental pollution during ore mining, and meets the requirements of modern mining for green environmental protection. The present invention establishes a filling strength prediction model through a filling physical property analysis unit, combined with solid phase mass concentration and rheological model, which fundamentally solves the static limitations of the prediction of filling mechanical properties in traditional technologies. The strength prediction model comprehensively considers the dynamic effects of multiple factors such as shear stress, temperature and hydration reaction characteristics on the strength development of the filling, and can accurately describe the changes in the mechanical properties of the filling during the solidification process. In particular, through the dynamic calculation of the hydration rate model and pore water pressure, the present invention can make reasonable predictions for hydration reactions and pore water pressure accumulation problems in complex deep high-stress environments, providing scientific support for the optimization of the entire process of filling construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0017] Figure 1 A schematic diagram of the system structure of an intelligent data acquisition and optimization control system applied to a mine filling system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Example 1, reference Figure 1 :An intelligent data acquisition and optimization control system applied to mine filling systems, the system comprising: an ore body stress analysis unit, a filling slurry solid phase quality analysis unit, a filling body physical property analysis unit and a filling control and analysis unit; the ore body stress analysis unit is used to establish a three-dimensional ore body geometric model according to the ore body geological exploration results, divide the three-dimensional ore body geometric model into finite element grids, and calculate the three-dimensional stress tensor field of the ore body; the filling slurry solid phase quality analysis unit is used to calculate the solid phase mass concentration of the filling slurry according to the three-dimensional stress tensor field of the ore body; the filling body physical property analysis unit is used to establish a rheological model of the filling slurry according to the solid phase mass concentration of the filling slurry; the rheological model of the filling slurry is calculated by combining the solid phase mass concentration of the filling slurry and the rheological model of the filling slurry. A filling body strength prediction model is constructed to predict the filling body strength of the filling slurry at each time; and based on the predicted filling body strength of the filling slurry at each time, the pore water pressure of the filling slurry at each time is calculated; the filling control and analysis unit is used to calculate the stability of the filling according to the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry, and obtain the stability coefficient; the stability coefficient describes the ability of the ore body and the filling body to withstand external stress, and the higher the value, the stronger the ability of the ore body and the filling body to withstand external stress; according to the stability coefficient, the filling body strength and the pore water pressure, the preset filling speed control model is used to calculate the current optimal filling speed, and the optimal filling speed is used to control the filling slurry for filling.

[0020] Specifically, the ore body stress analysis unit is the basis of the entire system, and its core function is to conduct a comprehensive analysis of the three-dimensional mechanical state of the underground ore body. During the underground longwall mining operation, the ore body often forms a complex stress distribution due to the influence of mining, and these stress states directly affect the stability of the stope and the stress of the filling body. To solve this problem, the ore body stress analysis unit constructs a three-dimensional geometric model of the ore body based on geological exploration data. By collecting the physical parameters, fault distribution, lithology interface and goaf range of the ore body, a digital model that can fully reflect the actual state of the ore body is established. Subsequently, the system uses the finite element analysis method to divide the three-dimensional model of the ore body into multiple discrete small units. The purpose of this grid division is to discretize the complex continuum problem so that the stress and deformation characteristics of each unit can be solved by numerical methods. The mechanical equilibrium equation and constitutive relationship inside each unit are combined, and the three-dimensional stress tensor field of the entire ore body is finally formed through iterative calculation. The core of the three-dimensional stress tensor field is to fully describe the internal stress state of the ore body. For underground mining, the stress inside the ore body can be divided into the principal stress component (i.e., the maximum and minimum normal stresses along a specific direction) and the shear stress component (describing the shear effect in the plane). Through the calculation of the stress tensor field, the system can not only determine the location of the high stress concentration area in the ore body, but also determine the stress redistribution characteristics caused by mining. This information directly provides guidance for the filling design, because the filling body needs to withstand the effects of these stresses after formation, so the strength and stability design of the filling material must be highly matched with the mechanical state of the ore body. Compared with traditional technologies, the present invention provides a more efficient guidance scheme for the subsequent filling process through more accurate and dynamic stress field analysis. Based on the results of the ore body stress analysis, the filling slurry solid mass analysis unit further calculates the solid mass concentration of the filling slurry, which is an important indicator for determining the mechanical properties of the filling body. The solid mass concentration describes the mass proportion of solid particles in the slurry, which directly affects the strength, fluidity and consolidation properties of the slurry. In the present invention, the calculation of the solid mass analysis unit is not only based on the physical properties of the solid material, but also dynamically combines the distribution characteristics of the three-dimensional stress tensor field of the ore body. High stress areas in the stress tensor field usually require a higher strength filling body, which requires an increase in the solid concentration of the filling slurry. Low stress areas allow for lower concentration slurry to ensure the economy and construction efficiency of the filling process. Therefore, the present invention analyzes the internal stress distribution of the ore body and intelligently adjusts the solid concentration of the slurry, so that the filling design can meet the mechanical requirements and avoid material waste.

[0021] The calculation process of solid mass concentration is actually a coupling optimization combining multiple physical fields. The solid particles in the slurry need to form a stable suspension system under the action of water. Too low solid concentration may lead to insufficient strength of the slurry, while too high concentration will increase the difficulty of construction and may cause pipe blockage risk. To this end, the solid mass analysis unit introduces a dynamic adjustment mechanism, which takes the ore body stress tensor field as input and obtains the optimal solid concentration distribution required for each ore body unit through multiple iterative calculations. The system not only takes into account the demand for slurry strength, but also comprehensively evaluates the fluidity of the slurry in the pipeline, the pumping pressure, and the adaptability to the on-site construction conditions. For example, when the slurry needs to be transported over a long distance, the system will automatically reduce the solid concentration to reduce pipeline wear and pumping resistance; while in high stress concentration areas, the solid concentration will be significantly increased to enhance the compressive strength of the filling body. It is worth mentioning that the solid concentration design of the filling slurry needs to match the subsequent rheological model. The rheological properties are directly affected by the solid phase concentration. The yield stress and viscosity coefficient of the slurry change with the change of the solid phase concentration, and these parameters further affect the operability of the slurry during the construction process and the strength performance after the final consolidation. Therefore, when the solid phase mass analysis unit calculates the concentration, it will simultaneously predict the rheological parameters of the slurry to ensure the comprehensiveness and feasibility of the design scheme. Through this multi-parameter coordinated optimization, the filling design of the present invention achieves the best balance between mechanical properties and construction efficiency. .

[0022] The core task of the backfill physical property analysis unit is to comprehensively analyze the physical properties of the backfill slurry from the perspective of materials science, especially its rheological properties, strength growth characteristics and pore water pressure changes under different conditions. This unit first establishes its rheological model based on the solid mass concentration of the slurry to describe the fluidity and stability of the slurry during the construction process. Long-distance underground transportation and complex space construction place high demands on the fluidity of the slurry, so the rheological model becomes an important tool to ensure smooth construction. In the present invention, the rheological model comprehensively considers the solid phase particle distribution, viscosity, yield stress and other parameters of the slurry to reflect its flow characteristics under different shear conditions. The yield stress of the slurry is a key parameter in the model, which reflects the minimum shear force required for the slurry to start flowing. By predicting the yield stress, the system can evaluate whether the slurry has sufficient anti-segregation ability to prevent particle sedimentation from affecting the uniformity and construction quality of the slurry. In addition, the backfill physical property analysis unit also dynamically evaluates the consolidation performance of the slurry by introducing a strength prediction model. After the construction of the mine filling slurry is completed, it needs to be gradually consolidated to form a filling body with sufficient bearing capacity. In this process, the strength of the slurry increases over time and is affected by its composition, solid mass concentration and surrounding environmental conditions. The system has established a time-based strength growth prediction model through a combination of experiments and modeling. The model can accurately predict the strength of the slurry at different time points, guide construction personnel to choose reasonable construction intervals and operation rhythms, and avoid filling body damage caused by premature loading. Through strength prediction, the system can also further adjust the slurry ratio and filling process to make the performance of the filling body more in line with the needs of mining engineering.

[0023] At the same time, in order to comprehensively evaluate the problems that may arise during the consolidation process of the slurry, this unit specifically introduces an analysis module for pore water pressure. During the filling process, the pore water pressure inside the slurry is one of the key factors affecting its consolidation speed and stability. Excessive pore water pressure may make it difficult for the slurry to drain, thereby delaying its consolidation process and even causing structural instability. This system constructs a dynamic calculation model of pore water pressure by comprehensively considering the material properties of the filling body and the construction environment conditions, and predicts the pore water pressure distribution of the slurry at different consolidation stages. The accuracy of the model provides the necessary safety guarantee for the subsequent construction process.

[0024] All analysis results generated by the backfill physical property analysis unit directly provide key data support for the backfill control and analysis unit. The main task of the backfill control and analysis unit is to dynamically control the backfill process in real time according to the stress conditions of the ore body, the slurry characteristics and the construction process, so as to optimize the backfill efficiency and ensure the construction safety. In the core control logic of this unit, the three-dimensional stress tensor field of the ore body is combined with the backfill strength and pore water pressure to form a stability evaluation mechanism. The key indicator of stability evaluation is the stability coefficient, which reflects the ability of the backfill to withstand external stress under the current stress conditions. By calculating the stability coefficient, the system can accurately determine whether the backfill meets the design requirements and avoid engineering safety problems caused by insufficient stability. In terms of backfill control, the backfill control and analysis unit dynamically adjusts the backfill speed and slurry flow rate based on the real-time calculated stability coefficient, pore water pressure and strength growth data. The determination of the backfill speed is a comprehensive optimization process, which needs to take into account multiple factors such as material strength growth, pore water pressure dissipation and construction efficiency. By building a filling speed control model, the system can calculate the current optimal filling speed based on real-time parameters, thereby maximizing construction efficiency and ensuring that the performance of the filling body meets the design requirements. For example, in high-stress areas, due to the large external load on the filling body, the system will increase the solid phase concentration of the slurry and appropriately reduce the filling speed to ensure that the strength growth rate of the filling body can keep up with the rhythm of stress loading; while in low-stress areas, the slurry concentration can be appropriately reduced and the filling speed can be accelerated to improve the overall construction efficiency. The dynamic nature of filling speed control enables the system to flexibly respond to various complex mining conditions, which is exactly what the traditional fixed-speed filling method does not have. The filling control and analysis unit also has intelligent decision-making capabilities. By interconnecting with other units of the entire system, it can achieve comprehensive perception and rapid response to the complex environment of the mine. For example, when the system detects that the pore water pressure in a certain area of ​​the ore body is too high, it can immediately issue an alarm and adjust the filling plan to reduce construction risks. At the same time, when the filling body strength growth rate is not enough to meet the design requirements, the system will also optimize the filling effect by increasing the solid phase concentration or extending the construction interval. This intelligent decision-making based on real-time data significantly improves the safety and reliability of the system.

[0025] Example 2: Assume an ore body stress analysis unit, divide the three-dimensional ore body geometric model into finite element grids, and the unit volume of each finite element grid is ; The three-dimensional stress tensor field of the ore body is calculated by the following formula : ; in, is the rock mass density of the ore body, which indicates the weight per unit volume of rock in the ore body; is the burial depth, which indicates the thickness of the rock layer covering the ore body; It represents the initial geostress coefficient, the ratio of horizontal stress to vertical stress, obtained through geostress measurement; The elastic modulus of the ore body is a material property that reflects the ability of the rock in the ore body to resist deformation. It is measured by laboratory uniaxial compression tests of rocks or by the sonic method. is Poisson's ratio, which describes the ratio of the lateral deformation to the longitudinal deformation of the rock, and takes a value of 0.2 or 0.4, which is determined by triaxial loading experiments; The position coordinates are The displacement at is obtained by numerical simulation based on the finite element method; is the Laplace operator The position coordinates are stress at is the divergence operator; The total volume of all finite element meshes.

[0026] Specifically, the first part of the formula, , represents the stress distribution of the ore body under static geostress. This part is the basic stress field of the ore body and is directly related to the geological conditions. The bulk density of the rock mass indicates the weight of the rock per unit volume. It is an important indicator for describing the physical properties of the rock. It is usually measured through laboratory tests. Its value directly affects the stress caused by the deadweight of the ore body. It indicates the thickness of the rock layer covering the ore body, which is an important determinant of the static stress of the ore body. As the vertical stress on the ore body increases, the vertical stress on the ore body increases linearly. In addition, the geostress coefficient It is the ratio of horizontal stress to vertical stress, used to describe the anisotropy of ground stress and obtained through ground stress measurement. The value of is affected by the regional geological structure and the characteristics of the rock itself, and is usually in the range of 0.4 to 1.0. The physical meaning of the static stress term is to describe the basic stress state of the ore body without external disturbance, and to provide a benchmark for the initial stress distribution of the ore body. The second part of the formula, the integral term, describes the ore body under elastic deformation due to the displacement field. This is partly achieved by introducing the elastic modulus and Poisson's ratio Incorporate the mechanical properties of rock materials into the formula. Elastic modulus It is a parameter that characterizes the rock's ability to resist deformation and reflects the stiffness of the rock material under external forces. Its value is usually determined by uniaxial compression tests and is one of the foundations of rock mechanical property research. It describes the lateral deformation characteristics of rock when subjected to longitudinal compression, and its value is between 0.2 and 0.4, obtained through triaxial loading experiments. The combination of the two describes the elastic response characteristics of rock mass under external forces, and converts these characteristics into calculation parameters of stress distribution.

[0027] In the integral term, the displacement field It is the local deformation of the ore body caused by external loads and boundary conditions, indicating the displacement changes of each point inside the ore body due to the force. By using the finite element method, the three-dimensional ore body geometric model is divided into volumes The Laplace operator in the formula is and divergence operator They describe the local bending and compression behaviors of the displacement field respectively. The Laplace operator represents the second-order change of the displacement field in the local space, and its physical meaning is the stress distribution caused by shear in the ore body; the divergence operator term is related to the volume deformation, which describes the expansion or compression effect of the ore body material when subjected to uniform loading. After combining these two terms, the elastic modulus and Poisson's ratio The parameterization of fully describes the additional stress field under the elastic deformation state of the ore body. In order to obtain the stress distribution in the entire ore body, the formula uses the integral form to accumulate the contributions of all finite elements. Represents the total grid volume This calculation method can integrate the local stress response of the ore body into an overall three-dimensional stress tensor field. , thus accurately reflecting the stress distribution state of the ore body under the combined action of static geostress and dynamic external force. The result of this stress tensor field has clear engineering significance. First, through the calculation of the stress tensor field, the location and range of the stress concentration area in the ore body can be determined. These areas are often the key parts that are prone to instability during mining. Secondly, the stress tensor field provides a scientific basis for the design of filling bodies. In high stress concentration areas, high-strength filling bodies are required to share external forces to prevent rock mass instability; while in low stress areas, filling materials with lower strength but higher economy can be used. Thirdly, the distribution of the stress tensor field also provides basic data for parameter control during filling construction. For example, the dynamic adjustment of the solid mass concentration of the slurry can be optimized based on the requirements of the stress field. The formula fully considers the influence of the intrinsic physical properties and external loads of the ore body on the stress distribution through the coupling of static geostress terms and dynamic stress terms. The introduction of the finite element method enables the formula to be numerically solved with high precision under complex geological conditions, which is particularly suitable for the complex and changeable stress field of the ore body during longwall mining. The applicability of this calculation method is not only reflected in the solution of stress distribution in three-dimensional space, but also in the ability to dynamically adjust the design parameters of the filling system by simulating the interaction between mining operations and the filling process to ensure the overall stability of the ore body.

[0028] Embodiment 3: The solid mass analysis unit of the filling slurry calculates the solid mass concentration of the filling slurry according to the three-dimensional stress tensor field of the ore body by the following formula: : ; in, is temperature; is the temperature influence coefficient, which is the preset value; is the residual yield stress, which describes the residual shear stress generated by the contact force of particles in the filling slurry and is determined by rheological experiments; is the maximum yield stress, is the maximum allowable shear stress, and is the set value; is the pressure influence coefficient, is the set value; is the critical pressure, indicating the maximum allowable pressure; is the porosity of the filling slurry; is the water density; is the solid phase density; is the standard pressure, is the set value; for The maximum value of is the median particle size, measured by laser particle size analyzer or sieving method; is the reference particle size; For pressure.

[0029] Specifically, the first part of the formula It represents the relationship between the solid concentration of the filling slurry and the ratio of the maximum stress of the ore body. is the maximum principal stress at a point in the three-dimensional stress tensor field of the ore body, obtained from the stress calculation formula in Example 2, and is a key parameter for describing the degree of local stress concentration in the ore body. It is the standard pressure, which is used as a reference value for normalization so that the stress calculation results of different areas can be uniformly included in the concentration calculation. Through this ratio, the requirements of the high stress area of ​​the ore body can be directly converted into the design basis of the slurry solid phase concentration. The high stress area requires a higher solid phase concentration to provide sufficient strength. Part II The particle characteristics and environmental factors of the filling slurry are introduced. This section mainly describes the adjustment mechanism of the solid phase concentration based on the particle distribution, porosity and temperature conditions of the slurry. and The density of solid particles and water respectively. Their ratio determines the buoyancy effect of the solid phase in the slurry. The greater the density difference, the easier it is for the particles to settle, which requires a higher concentration to maintain the uniformity of the slurry. is the void ratio in the slurry, describing the filling efficiency of the solid particles. It directly reflects the relationship between the interparticle gap and the solid particle volume. Lower porosity indicates that the particles are closely packed, which can improve the overall strength of the slurry, but may reduce its fluidity, so it needs to be weighed in the concentration calculation. and reference particle size It is used to characterize the particle size distribution of particles, and its ratio It reflects the influence of particle size change on slurry performance. Small) can usually fill the gaps between particles and improve density, but it will increase the viscosity of the slurry and make it difficult to pump. and temperature influence coefficient This further adds to the impact of the environment on the slurry properties. The fluidity and solidification rate of the slurry may decrease in a low temperature environment, so appropriate adjustments need to be made in the concentration calculation. The third part of the formula Describes the effect of residual yield stress generated by contact force between particles in slurry on solid phase concentration. It reflects the residual shear strength of the slurry under shear, which is usually determined by the particle contact force and friction. The ratio of the two indicates how close the current shear stress of the slurry is to its ultimate shear resistance. When the residual yield stress is high, the shear resistance between particles is significant, indicating that the fluidity of the slurry is poor. At this time, the solid phase concentration needs to be reduced to improve its pumping performance. Used to introduce the effect of construction pressure on solid phase concentration. Construction pressure With critical pressure The ratio describes the relative strength of the pressure on the slurry. Determines the sensitivity of pressure changes to slurry concentration adjustments. As the solid phase increases, the particles in the slurry tend to be arranged more closely, so it is necessary to appropriately reduce the solid phase concentration to avoid the risk of slurry blockage in the pipeline.

[0030] Embodiment 4: The filling body physical property analysis unit establishes a rheological model of the filling slurry according to the solid mass concentration of the filling slurry through the following formula; ; in, For time Shear stress at is the flow index; is the pressure loss; is the length of the pipeline; For time The filling speed of the filling slurry at ; is the pipe radius; is the solid phase volume fraction, which indicates the proportion of solid particles in the volume of the filling slurry; is the preset maximum solid volume fraction; is the preset minimum porosity; is the activation energy of the filling slurry.

[0031] Specifically, the first major part of the rheological model describes the basic shear stress characteristics of the slurry. It is the maximum allowable shear stress, representing the ultimate shear resistance of the slurry. It is a key value preset by the physical parameters of the slurry and the construction requirements. It is the ratio of the volume of solid particles in the slurry to the total slurry volume, which is the core parameter affecting the fluidity and strength of the slurry. When increases, the contact force and friction between particles increase, thus significantly improving the shear resistance of the slurry. In order to prevent the unlimited amplification of shear stress by solid phase volume fraction, the formula is As a normalization factor, it ensures that the calculated shear stress results can be kept within a reasonable range. On this basis, the formula further introduces , which is used to describe the inhibitory effect of pressure loss on shear stress. Pressure loss It is the energy consumption caused by the flow resistance of the slurry in the pipeline, and its value increases with the increase of flow rate and pipeline length. is a preset limit value, which represents the upper limit of the effect of pressure loss on shear stress. When it increases, the energy consumption of the slurry increases, which will lead to a relative decrease in the shear stress of the slurry, thereby maintaining the fluidity of the slurry during the construction process. The introduction of the pressure loss term enables the formula to effectively adapt to the working conditions of long-distance pumping and complex pipeline structures.

[0032] The second part of the formula It further describes the shear stress changes of the slurry during the dynamic flow process. First, the shear rate It is the key driving force of slurry flow change, which is related to the flow index Together they determine the dynamic adjustment characteristics of shear stress. It is an important parameter to characterize the rheological properties of slurry. When , the slurry behaves as a Newtonian fluid, and the shear stress is linearly related to the shear rate; when When the shear rate increases, the slurry behaves as a pseudoplastic fluid, that is, the shear stress decreases when the shear rate increases. This characteristic is usually beneficial to construction; This indicates that the slurry is an expansive fluid, and the higher the shear rate, the greater the shear stress. The effects of temperature, activation energy, filling speed and pipeline parameters on shear stress are combined. First, activation energy It is the energy required for the slurry to overcome the adsorption and binding forces between particles during the flow process. It is determined experimentally and is an important parameter to characterize the strength of the interaction between slurry particles. When the activation energy increases, the binding force between particles weakens, the inhibition of activation energy decreases, and the shear stress of the slurry decreases. This relationship is expressed by the exponential term At the same time, The filling speed and solid phase mass concentration Effect on shear stress. When the filling speed is high, the interaction between particles is enhanced, resulting in increased shear stress; long pipes and high pressure losses weaken this effect, thereby maintaining the fluidity of the slurry. By introducing the slurry porosity Correction was made for shear stress. Porosity Characterizes the void ratio between solid particles, which is directly related to the density and fluidity of the slurry. When the porosity is high, the friction between particles is low and the shear stress is reduced accordingly; when the porosity is close to the minimum value, the shear stress is reduced. When the particle size is smaller than 0.01, the arrangement between particles tends to be close, resulting in a significant increase in shear stress. Through this correction term, the formula can accurately reflect the influence of different particle distribution states on the rheological properties of the slurry.

[0033] Example 5: Pressure loss Calculated using the following formula: ; in, is the gas constant.

[0034] Specifically, the first part of the formula The basic effects of flow velocity, pipe length and diameter on pressure loss are described. First, Indicates the length of the pipeline. As the length of the pipeline increases, the friction resistance that the slurry needs to overcome during transportation will increase linearly. It is a direct factor affecting pressure loss. Is the slurry at time The flow rate at the time of the pipe is the speed at which the slurry is delivered. High flow rates are usually accompanied by greater internal flow resistance, resulting in higher pressure losses. The effect on pressure loss is nonlinear, which is It is introduced in the form of , indicating that the reduction of pipe diameter will significantly increase pressure loss. A smaller pipe diameter will cause the slurry flow rate to increase locally, thereby significantly increasing the effect of pipe wall friction and fluid resistance. Therefore, in actual construction, in order to reduce pressure loss, a larger pipe diameter is usually selected. The second part of the formula The flow index is further considered Correction for pressure loss. Flow index It is a parameter that describes the rheological properties of the slurry, which determines the viscosity behavior of the slurry under different flow conditions. When , the slurry behaves as a Newtonian fluid, and its viscosity behavior is linearly related to the flow rate; When , the slurry behaves as a pseudoplastic fluid, that is, as the flow rate increases, its viscosity decreases, thereby reducing the pressure loss; when When the slurry is subjected to the action of an expansive fluid, its viscosity increases with the increase of the flow rate, resulting in an increase of the pressure loss. The introduction of ensures that the formula can dynamically adapt to slurries with different rheological properties, especially under pseudoplastic fluid conditions. This correction significantly reduces the calculated value of pressure loss, making the formula more in line with the physical phenomena in actual transportation. Overall, the pressure loss formula accurately describes the flow characteristics of slurry in pipeline transportation, organically combines flow velocity, pipeline geometric parameters and slurry rheological characteristics, and provides a theoretical basis for parameter optimization in complex construction environments. Each part of the formula has a clear physical meaning: pipeline length and diameter Reflects the restriction of the geometric characteristics of the pipeline on the slurry flow; flow rate Directly determines the magnitude of fluid dynamics resistance; and the flow index The viscosity behavior is modified to ensure that the formula can adapt to different types of filling slurries.

[0035] Embodiment 6: The filling body physical property analysis unit constructs a filling body strength prediction model by combining the solid mass concentration of the filling slurry and the rheological model of the filling slurry through the following formula: ; in, Indicates that the solid mass concentration of the filling slurry is Maximum filling strength at ; is the characteristic time of the hydration reaction of the filling slurry, and the time when the hydration reaction of the filling slurry reaches 50% is determined by the hydration heat release experiment; Indicates when When the shear stress is , the temperature is The hydration rate at ; is the baseline hydration rate.

[0036] Specifically, first of all, Indicates the specific solid mass concentration The maximum strength of the lower filling body, which is the basic parameter in the model. is the mass ratio of solid particles in the filling slurry and is one of the main factors determining the final strength. High solid concentration usually corresponds to higher particle packing density and less porosity, thus forming a stronger consolidated structure. This article determines the different The corresponding maximum intensity , which provides a clear target for slurry mix design. The second part of the formula The control effect of hydration reaction on strength growth is described. Hydration reaction is the most critical chemical reaction in the curing process of filling slurry. Its characteristic time It indicates the time required for the hydration reaction to reach 50% completion, which is determined by the hydration heat release experiment. This time constant reflects the reaction rate and activity of the hydrating substances in the slurry. Hydration rate This is the core of the section, describing the , shear stress and temperature Specifically, There are multiple influencing factors in the baseline hydration rate. It is the hydration rate of the slurry under standard conditions and describes the inherent reactivity of the material. and activation energy The effect of temperature on the hydration reaction rate is reflected by the classic Arrhenius equation. The increase in temperature will significantly accelerate the hydration rate, which is caused by the activation energy reducing the chemical reaction barrier on the particle surface. At the same time, the shear stress and maximum yield stress The ratio of further modifies the hydration rate. Larger shear stress accelerates hydration by increasing the contact frequency between particles and breaking the inert layer on the surface of particles. It is a cumulative description of the degree of completion of the hydration reaction, expressed in time The total effect of the previous hydration reaction. The ratio of the integral term rises to The formula effectively captures the dynamic control of the hydration reaction on the strength formation. The negative sign in the exponential term indicates that when the hydration reaction rate is low or the time is short, the strength growth will be significantly slowed down. The third part of the formula It is the correction term of pressure loss on filling body strength. It is the pressure energy consumed by the slurry during transportation due to flow resistance, which may affect the uniformity of the slurry in the pipeline and the compactness of the particle distribution. It is a reference value used for normalization to ensure that the effects of pressure loss under different construction conditions can be reasonably compared. When the pressure loss is small, this item has little effect on the strength; but when the pressure loss approaches or exceeds the critical value, the uneven distribution of particles and the shear effect of the slurry may significantly reduce the final strength.

[0037] Embodiment 7: The filling body physical property analysis unit calculates the pore water pressure of the filling slurry at each time according to the predicted filling body strength of the filling slurry at each time by the following formula: ; in, For time The pore water pressure at The filling strength is The permeability coefficient at the time of filling is obtained according to the pre-established relationship between the filling body strength and the permeability coefficient; is the volume compression coefficient of the filling slurry, which means the ratio of the actual volume of the filling slurry to the volume of the pipeline; is the specific gravity of water.

[0038] Specifically, the permeability coefficient in the formula It is the core parameter describing the dissipation rate of pore water pressure, which is closely related to the filling body strength. Dynamic correlation. The permeability coefficient reflects the flow capacity of water in the filling body, which is usually obtained through a pre-established strength-permeability relationship curve. When the filling body strength is low (initial curing), the permeability coefficient As the strength increases (the degree of solidification increases), the slurry gradually forms a dense consolidation structure, and the permeability coefficient decreases significantly, thereby slowing down the dissipation rate of the pore water pressure. By expressing the permeability coefficient as a function of strength, the formula can dynamically adjust the evolution of pore water pressure to adapt to the solidification process of the filling body. The core expression of the formula is The migration characteristics of pore water in three-dimensional space are described under the influence of the mechanical behavior of the filling body. is the displacement field inside the ore body, calculated by the finite element method in Example 2, and represents the local deformation distribution caused by the ore body stress and external force in the three-dimensional coordinate system. The introduction of further reflects the constraint effect of mechanical parameters on water migration during the solidification process. The second-order partial derivative in the expression represents the pore water The gradient distribution of diffusion on the plane, while the vertical derivative It reflects the flow trend of water in the vertical direction. This coupling relationship in the spatial dimension fully characterizes the change law of pore water pressure under the combined action of displacement field and intensity field. Describes the process of pore water pressure dissipation over time. This term directly introduces the volume compressibility coefficient , water density , Permeability coefficient and time Volume compression coefficient It is the volume response parameter of the filling slurry, which indicates the volume change of the slurry under pressure. It is usually determined by experiments. This indicates that the slurry has a higher compressibility, which leads to a faster dissipation rate of pore water pressure. It is a physical parameter that characterizes the contribution of the gravity effect of water to the pressure. As time goes by, the negative exponent in the exponential term makes the pore water pressure show exponential decay characteristics, reflecting the dynamic law of seepage. The instantaneous rate of change of pore water pressure is expressed, and the above parameters are combined to comprehensively describe the evolution of pore water pressure during the solidification process of the filling body. In the initial stage, the pore water pressure drops rapidly due to infiltration and water migration; as time goes by, the increase in the degree of solidification reduces the permeability coefficient, and the attenuation of pore water pressure gradually stabilizes. Through the precise modeling of this dynamic process, the formula can reflect the transformation process of the filling slurry from liquid to solidified in real time, providing important data support for the adjustment of construction parameters and stability evaluation.

[0039] Embodiment 8: The filling control and analysis unit uses the following formula to calculate the filling stability according to the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry to obtain the stability coefficient : ; in, is the critical pore water pressure, is the set value.

[0040] Specifically, the first key part of the formula It indicates the ratio of filling strength to ore body stress. This ratio reflects the resistance level of the filling under the current stress conditions. The time for the filling paste to solidify The compressive strength at that time is calculated based on the strength prediction model in Example 6. This reflects the gradual enhancement of mechanical properties during the slurry solidification process as the hydration reaction proceeds. is the external load distribution of the ore body during mining and construction, which is determined by the three-dimensional stress tensor field calculated by the finite element method in Example 2. The formula directly quantifies the bearing capacity of the filling body under the ore body stress through the ratio of the two: Higher and When it is lower, the filling body has a higher bearing margin and stability coefficient On the contrary, when Lower or When it is high, the bearing capacity of the filling body is insufficient and the stability coefficient Descend. Part 2 is the pore water pressure Correction term for stability. Pore water pressure is the hydrostatic pressure generated by the incomplete discharge of water inside the filling during the solidification process. Its value is determined by the pore water pressure calculation formula of Example 7. Critical pore water pressure It is a safety reference value set during the design process to define the upper limit of the effect of pore water pressure on the stability of the filling body. Close to critical value hour, Close to 1, correction term It tends to 0, indicating that the weakening effect of pore water pressure on stability is significant. This term reflects the dynamic influence of hydraulic factors on the mechanical properties of the filling body: high pore water pressure may lead to reduced shear strength, uneven consolidation or internal cracking of the filling body, significantly weakening its stability; when the pore water pressure is low, the correction term tends to 1, indicating that its influence on stability can be ignored. The third part of the formula It is a correction term for the dynamic growth of filling body strength and is used to describe the current strength of the filling body. Its theoretical maximum strength The relationship between. The filling body has a solid mass concentration of The maximum theoretical intensity at , is determined by the intensity model of Example 6. The ratio in the exponential term Indicates the ratio of the current intensity to the theoretical maximum intensity: near When , indicating that the strength of the filling body has approached its theoretical limit, and further enhancement has limited impact on stability; Much smaller than , the value of the exponential term is close to 1, indicating that the current intensity is still in a rapid growth stage, and its impact on stability is more significant.

[0041] Embodiment 9: The filling control and analysis unit uses the following formula to calculate the current optimal filling speed based on the stability coefficient, filling body strength and pore water pressure using a preset filling speed control model: : .

[0042] Specifically, the first correction term of the formula It is the square root of the ratio of the filling body strength to the ore body stress, which directly describes the bearing capacity of the filling body under the current external stress conditions. The time for the filling paste to solidify The compressive strength at , calculated by the strength prediction model of Example 6, is affected by the hydration reaction, solid phase concentration and environmental conditions. It is the three-dimensional stress distribution formed by external forces during the mining process of the ore body, which is obtained by the stress tensor field calculation of Example 2. The larger the ratio, the stronger the compressive capacity of the filling body is, and it can withstand a higher construction speed; on the contrary, when the ratio is small, the filling body is in a weak state, and the construction speed needs to be appropriately reduced to avoid excessive load on the filling body. The second correction term It combines the velocity limitation of pressure loss and ore displacement field. It is the energy loss caused by the friction of the inner wall of the pipeline and the viscosity of the slurry during transportation, which is closely related to the construction parameters and the geometric characteristics of the pipeline. It is a preset safety upper limit used to limit the adverse effects of high pressure loss on construction. When the pressure loss approaches or exceeds the critical value, Approaching 1, the effect of the correction term will significantly reduce the filling speed, preventing excessive delivery pressure from causing pipeline blockage or limited slurry fluidity. The internal displacement field of the ore body is further considered. The displacement field is determined by the ore body stress and external forces. Large displacement indicates that the ore body structure may have a potential risk of instability. At this time, the construction speed needs to be appropriately reduced to avoid further disturbance to the ore body structure. The ratio of the filling strength to its theoretical ultimate strength and the solid mass concentration are introduced. Impact on construction speed. Theoretical ultimate strength The filling slurry has a solid mass concentration of The maximum strength when cured to the complete state under the conditions is predetermined by the model of Example 6. It indicates the ratio of current strength to ultimate strength, reflecting the curing process of the filling body. When the current strength is close to the theoretical limit, there is limited room for increasing the construction speed; in the early stage of curing, this ratio is small, and the speed needs to be appropriately reduced to provide sufficient consolidation time for the slurry. This describes the combined effect of solid mass concentration and pressure loss. When the velocity is higher, the density and strength of the slurry increase faster, but the pressure loss during transportation will also increase accordingly; at this time, the velocity needs to be moderately reduced to balance the contradiction between strength formation and transportation efficiency. Through the permeability and water density Describes the effect of pore water pressure on velocity. Permeability It is a function of the strength of the filling body and gradually decreases with the increase of strength, reflecting the dynamic change of water migration capacity. When the permeability coefficient is low, the pore water pressure inside the slurry is more difficult to dissipate. Excessive construction speed may lead to the accumulation of internal pressure, which will have an adverse effect on the stability and uniformity of the filling body.

[0043] The present invention is described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. Intelligent data acquisition and optimization control system applied to mine filling system, characterized by: The system comprises: an ore body stress analysis unit, a filling slurry solid phase quality analysis unit, a filling body physical property analysis unit and a filling control and analysis unit; the ore body stress analysis unit is used to establish a three-dimensional ore body geometric model according to the geological exploration results of the ore body, divide the three-dimensional ore body geometric model into finite element grids, and calculate the three-dimensional stress tensor field of the ore body; the filling slurry solid phase quality analysis unit is used to calculate the solid phase mass concentration of the filling slurry according to the three-dimensional stress tensor field of the ore body; the filling body physical property analysis unit is used to establish a rheological model of the filling slurry according to the solid phase mass concentration of the filling slurry; and a filling body strength prediction model is constructed by combining the solid phase mass concentration of the filling slurry and the rheological model of the filling slurry. , predict the filling body strength of the filling slurry at each time; and calculate the pore water pressure of the filling slurry at each time based on the predicted filling body strength of the filling slurry at each time; the filling control and analysis unit is used to calculate the stability of the filling according to the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry, and obtain the stability coefficient; the stability coefficient describes the ability of the ore body and the filling body to withstand external stress, and the higher the value, the stronger the ability of the ore body and the filling body to withstand external stress; according to the stability coefficient, the filling body strength and the pore water pressure, the preset filling speed control model is used to calculate the current optimal filling speed, and the optimal filling speed is used to control the filling slurry for filling.

2. The intelligent data acquisition and optimization control system for mine filling system according to claim 1, characterized in that: Assume an ore body stress analysis unit and divide the three-dimensional ore body geometric model into finite element grids. The unit volume of each finite element grid is ; The three-dimensional stress tensor field of the ore body is calculated by the following formula : ； in, is the rock mass density of the ore body, which indicates the weight per unit volume of rock in the ore body; is the burial depth, which indicates the thickness of the rock layer covering the ore body; It represents the initial geostress coefficient, the ratio of horizontal stress to vertical stress, obtained through geostress measurement; The elastic modulus of the ore body is a material property that reflects the ability of the rock in the ore body to resist deformation. It is measured by laboratory uniaxial compression tests of rocks or by the sonic method. is Poisson's ratio, which describes the ratio of the lateral deformation to the longitudinal deformation of the rock, and takes a value of 0.2 or 0.4, which is determined by triaxial loading experiments; The position coordinates are The displacement at is obtained by numerical simulation based on the finite element method; is the Laplace operator The position coordinates are stress at is the divergence operator; The total volume of all finite element meshes.

3. The intelligent data acquisition and optimization control system for mine filling system according to claim 2, characterized in that: The filling slurry solid phase mass analysis unit calculates the solid phase mass concentration of the filling slurry according to the three-dimensional stress tensor field of the ore body through the following formula: : ； in, is temperature; is the temperature influence coefficient, which is the preset value; is the residual yield stress, which describes the residual shear stress generated by the contact force of particles in the filling slurry and is determined by rheological experiments; is the maximum yield stress, is the maximum allowable shear stress, and is the set value; is the pressure influence coefficient, is the set value; is the critical pressure, indicating the maximum allowable pressure; is the porosity of the filling slurry; is the water density; is the solid phase density; is the standard pressure, is the set value; for The maximum value of is the median particle size, measured by laser particle size analyzer or sieving method; is the reference particle size; For pressure.

4. The intelligent data acquisition and optimization control system for mine filling system according to claim 3, characterized in that: The filling body physical property analysis unit establishes a rheological model of the filling slurry according to the solid mass concentration of the filling slurry through the following formula; ； in, For time Shear stress at is the flow index; is the pressure loss; is the length of the pipeline; For time The filling speed of the filling slurry at ; is the pipe radius; is the solid phase volume fraction, which indicates the proportion of solid particles in the volume of the filling slurry; is the preset maximum solid volume fraction; is the preset minimum porosity; is the activation energy of the filling slurry.

5. The intelligent data acquisition and optimization control system for mine filling system according to claim 4, characterized in that: Pressure loss Calculated using the following formula: ； in, is the gas constant.

6. The intelligent data acquisition and optimization control system for mine filling system according to claim 5, characterized in that: The filling body physical property analysis unit constructs a filling body strength prediction model by combining the solid phase mass concentration of the filling slurry and the rheological model of the filling slurry through the following formula: ； in, Indicates that the solid mass concentration of the filling slurry is Maximum filling strength at ; is the characteristic time of the hydration reaction of the filling slurry, and the time when the hydration reaction of the filling slurry reaches 50% is determined by the hydration heat release experiment; Indicates when When the shear stress is , the temperature is The hydration rate at ; is the baseline hydration rate.

7. The intelligent data acquisition and optimization control system for mine filling system according to claim 6, characterized in that: The filling body physical property analysis unit calculates the pore water pressure of the filling slurry at each time according to the predicted filling body strength of the filling slurry at each time by the following formula: ； in, For time The pore water pressure at The filling strength is The permeability coefficient at the time of filling is obtained according to the pre-established relationship between the filling body strength and the permeability coefficient; is the volume compression coefficient of the filling slurry, which indicates the ratio of the actual volume of the filling slurry to the volume of the pipeline; is the specific gravity of water.

8. The intelligent data acquisition and optimization control system for mine filling system according to claim 7, characterized in that: The filling control and analysis unit uses the following formula to calculate the filling stability based on the three-dimensional stress tensor field of the ore body and the pore water pressure of the filling slurry to obtain the stability coefficient : ； in, is the critical pore water pressure, is the set value.

9. The intelligent data acquisition and optimization control system for mine filling system according to claim 8, characterized in that: The filling control and analysis unit uses the following formula to calculate the current optimal filling speed based on the stability coefficient, filling body strength and pore water pressure using a preset filling speed control model: : 。

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