Method and system for predicting incoming pressure in stope mines based on pressure arch and thick hard rock layer

Abstract

The present invention discloses a method and system for predicting mine pressure in a mining area based on pressure arch and thick hard rock layer, and specifically relates to the technical field of mine pressure data processing, including a mining area three-dimensional geological model construction module, a mining area geological data acquisition module, a mining area pressure arch formation range theoretical analysis module, a mining area thick hard rock layer fissure risk management module, a mining area mine pressure intensity prediction model display module, a mining area mine pressure intensity prediction model optimization module and a mining area mine pressure early warning module. The present invention collects geological data of each monitoring sub-area of ​​the mining area mine rock layer, calculates the mining area mine safety production stability index and the thick hard rock layer fissure risk assessment index, analyzes the mining area mine pressure intensity prediction coefficient, and obtains the optimal model through model training and compares it with the preset value, thereby optimizing the model, improving the accuracy of the prediction, and realizing the monitoring and early warning of the mine pressure intensity, so as to take timely measures to ensure safety.

Description

Technical Field

[0001] The present invention relates to the technical field of mine pressure data processing, and more particularly to a method and system for predicting mine pressure in a stope based on pressure arches and thick hard rock layers. Background Art

[0002] During the mining process, the safety issues caused by mine pressure in the mine are becoming increasingly prominent. The formation of mine pressure is usually closely related to the stress distribution of the rock strata, the formation of pressure arches, and the stability of thick and hard rock strata. Accurately predicting mine pressure in the mine based on pressure arches and thick and hard rock strata is of great significance for the rational arrangement of mining operations, optimization of support design, and ensuring the safety of personnel and equipment.

[0003] In traditional shallow mining, the overburden pressure in the mining area is relatively small, and the formation and evolution of the pressure arch is relatively simple. However, as mining extends to deeper areas, the occurrence state of thick and hard rock strata becomes more complex, and their mechanical behavior under the influence of mining has an increasingly significant impact on the stability of the mining area. The fracture of the thick and hard sandstone roof often triggers strong mine pressure, leading to accidents such as roof collapse and support damage, which seriously threaten safe production.

[0004] However, it still has some shortcomings in actual use. For example, as the mining depth increases, the thick and hard rock layer forms a pressure arch structure, which leads to stress concentration and then causes pressure. Traditional pressure prediction methods mostly rely on empirical formulas or single geological parameters, which makes it difficult to achieve accurate pressure prediction in the stope, resulting in insufficient accuracy of the prediction results.

[0005] The existing mine pressure prediction model for stopes has limitations in acquiring and processing data related to pressure arches and thick hard rock formations. It is difficult to effectively extract characteristic information related to mine pressure from the data, and the real-time updating of model parameters is not considered, resulting in large deviations between the prediction results and the actual situation. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and system for predicting incoming pressure in a stope mine based on pressure arch and thick hard rock formations, which are used to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: a stope mine pressure prediction system based on pressure arch and thick hard rock formations, comprising:

[0008] Module for constructing three-dimensional geological model of stope mine: Use three-dimensional modeling software to construct a three-dimensional spatial distribution model of the stope mine rock strata, divide the stope mine rock strata into various monitoring sub-areas according to the equal height division method, and number each monitoring sub-area of ​​the stope mine rock strata.

[0009] Stope mine geological data acquisition module: used to collect geological data of each monitoring sub-area of ​​the stope mine rock layer. The stope mine geological data acquisition module includes a pressure arch formation data acquisition unit and a thick hard rock layer fracture data acquisition unit.

[0010] Theoretical analysis module of the range of pressure arch formation in stope mines: used to calculate the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock strata.

[0011] Thick hard rock strata fissure risk management module for stope mines: used to calculate the thick hard rock strata fissure risk assessment index for each monitoring sub-area of ​​the stope mine rock strata.

[0012] The mine pressure intensity prediction model display module of the stope mine is used to calculate the mine pressure intensity prediction coefficient of the stope mine rock stratum based on the mine safety production stability index of each monitoring sub-area of ​​the stope mine rock stratum and the thick hard rock stratum crack risk assessment index.

[0013] Mining pressure intensity prediction model optimization module: Setting It is the initial model for predicting the pressure strength of the mine in the stope. The prediction results of each initial model are recorded, and the optimal model is obtained through model training.

[0014] Stope mine pressure warning module: obtains the stope mine pressure intensity update coefficient of the stope mine rock stratum, compares it with the preset stope mine pressure intensity classification warning coefficient, and processes it.

[0015] Preferably, the stope mine three-dimensional geological model construction module is specifically:

[0016] S21: Use 3D modeling software to construct a 3D spatial distribution model of the mine rock strata and dynamically update the compressive strength prediction model;

[0017] S22: Divide the mining strata in the stope into monitoring sub-areas according to a division method of equal height, and number the monitoring sub-areas of the mining strata in the stope as 1, 2, ..., i, ..., n in sequence from the top of the stratum.

[0018] Preferably, the stope mine geological data acquisition module is specifically:

[0019] Pressure arch formation data acquisition unit: collects the stope span, internal friction angle of thick hard rock layer, groundwater level depth, and temperature of thick hard rock layer in each monitoring sub-area of ​​the stope mine rock layer, and marks them as 、 、 、 , where i=1,2,...n, i represents the number of the i-th monitoring sub-area;

[0020] Thick hard rock fracture data acquisition unit: The vertical thickness of the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer is measured by geological radar, marked as ;Using ultrasonic testing equipment, transmitting probes and receiving probes are arranged on the rock surface of each monitoring sub-area to measure the compressive strength of the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer, marked as ; Collect the density and direction of the cracks in the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer in the stope, and mark them as 、 .

[0021] Preferably, the stope mine pressure arch formation range theoretical analysis module is specifically:

[0022] S41: Calculate the pressure arch formation range of each monitoring sub-area based on the stope span and the internal friction angle of the thick hard rock layer:

[0023]

[0024] in, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the stope span of the ith monitoring sub-area, It is expressed as the internal friction angle of thick hard rock layer in the i-th monitoring sub-area;

[0025] S42: Based on the actual mining depth of the stope mine rock layer, the mechanical property relaxation of the thick hard rock layer in each monitoring sub-area is calculated through the stope span, groundwater level depth, and thick hard rock layer temperature:

[0026]

[0027] in, It is expressed as the mechanical property relaxation of thick hard rock formation in the i-th monitoring sub-area, is the groundwater level depth of the ith monitoring sub-area, H is the actual mining depth, is the temperature of the thick hard rock layer in the ith monitoring sub-area, e is a natural constant, Expressed as temperature impact factor;

[0028] S43: The calculation formula of the mine safety production stability index is:

[0029]

[0030] in, It is expressed as the mine safety production stability index of the i-th monitoring sub-area, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the maximum value of the pressure arch formation range, It is expressed as the mechanical property relaxation of thick hard rock formation in the i-th monitoring sub-area.

[0031] Preferably, the calculation formula for the thick hard rock layer fissure risk assessment index is:

[0032]

[0033] in, It is expressed as the risk assessment index of thick hard rock fracture in the i-th monitoring sub-area, It is expressed as the vertical thickness of the thick hard rock layer in the i-th monitoring sub-area, It is expressed as the compressive strength of thick hard rock layer in the i-th monitoring sub-area, It is expressed as the crack density of thick hard rock layer in the i-th monitoring sub-area, It is represented as the crack direction of thick hard rock layer in the i-th monitoring sub-area, It is expressed as the mean value of the crack density in thick hard rock layers, 、 They are respectively expressed as the compressive strength of thick hard rock layers and the attenuation coefficient in the crack direction of thick hard rock layers, and e is expressed as a natural constant.

[0034] Preferably, the calculation formula for the prediction coefficient of the mine pressure intensity of the stope is:

[0035]

[0036] in, It is expressed as the prediction coefficient of the mine pressure intensity at the stope. It is expressed as the mine safety production stability index of the i-th monitoring sub-area, It is expressed as the mine safety production stability index of the i-1th monitoring sub-area, It is expressed as the risk assessment index of thick hard rock fracture in the i-th monitoring sub-area, It is expressed as the thick hard rock fracture risk assessment index of the i-1th monitoring sub-area, It is represented as the pressure time of the i-th monitoring sub-area, It is represented as the division height of the monitoring sub-area, 、 They are the weight coefficients of the mine safety production stability index and the thick hard rock stratum fissure risk assessment index, respectively, and n is the number of monitoring sub-areas.

[0037] Preferably, the stope mine pressure intensity prediction model optimization module is specifically:

[0038] S71: using the stope mine compressive strength prediction coefficient of the stope mine rock layer as the initial model, recording the prediction result of the initial model of the jth sample, and preliminarily setting the weight w according to expert opinion;

[0039] S72: Use the loss function to adjust the weights. The formula is:

[0040] ,

[0041] in, It is expressed as the loss function of the prediction coefficient of the mine pressure strength of the stope, m is the number of samples, It is expressed as the prediction coefficient of the mine pressure intensity of the j-th sample, It represents the preset stope mine pressure intensity prediction coefficient, w represents the initial set weight, Represents the updated weight, and y represents the learning rate;

[0042] S73: Use k-fold cross validation to evaluate the stability of the model. Divide the sample data set into k subsets, train the model with k-1 subsets each time, and use the remaining subset for validation. Calculate the model optimization coefficient:

[0043] ,in, Expressed as the model optimization coefficient of the j-th sample;

[0044] S74: The optimal model is formulated as follows:

[0045] ,in, Expressed as the mean of the model optimization coefficients, ;

[0046] S75: According to the updated optimal model, Set as the update coefficient of the mine pressure intensity in the stope.

[0047] Preferably, the stope mine pressure warning module is specifically:

[0048] Set a preset low-risk warning coefficient for the mine pressure intensity of the mine, a preset medium-risk warning coefficient for the mine pressure intensity of the mine, and a preset high-risk warning coefficient for the mine pressure intensity of the mine. When the mine pressure intensity update coefficient of the mine rock stratum is less than or equal to the preset low-risk warning coefficient for the mine pressure intensity of the mine, it indicates that the mine pressure intensity of the mine rock stratum is in a low-risk state, the production safety is high, and only routine monitoring and maintenance are required; when the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset low-risk warning coefficient for the mine pressure intensity of the mine and is less than or equal to the preset medium-risk warning coefficient for the mine pressure intensity of the mine, it indicates that the mine rock stratum is in a low-risk state, the production safety is high, and only routine monitoring and maintenance are required; when the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset low-risk warning coefficient for the mine pressure intensity of the mine and is less than or equal to the preset medium-risk warning coefficient for the mine pressure intensity of the mine, it indicates that the mine rock stratum is in a high-risk state The pressure intensity of the mine layer is in a medium-risk state, and monitoring needs to be strengthened to prevent potential safety accidents; when the mine pressure intensity update coefficient of the mine rock layer is greater than the preset mine pressure intensity medium-risk warning coefficient and is less than or equal to the preset mine pressure intensity high-risk warning coefficient, it indicates that the pressure intensity of the mine rock layer is in a high-risk state, and emergency measures must be taken immediately; when the mine pressure intensity update coefficient of the mine rock layer is greater than the preset mine pressure intensity high-risk warning coefficient, it indicates that the pressure intensity of the mine rock layer is extremely high, there are serious safety hazards, and an immediate full shutdown must be carried out to trigger a red warning.

[0049] Preferably, the method for predicting incoming pressure in a stope mine based on pressure arch and thick hard rock layer comprises the following steps:

[0050] Step S01: Construction of a three-dimensional geological model of the stope mine: Using three-dimensional modeling software, a three-dimensional spatial distribution model of the stope mine rock strata is constructed, and the stope mine rock strata is divided into various monitoring sub-areas according to the equal height division method, and each monitoring sub-area of ​​the stope mine rock strata is numbered;

[0051] Step S02: stope mine geological data collection: used to collect geological data of each monitoring sub-area of ​​the stope mine rock strata, the stope mine geological data collection includes a pressure arch formation data collection sub-step and a thick hard rock stratum fissure data collection sub-step, and the geological data includes pressure arch formation data and thick hard rock stratum fissure data;

[0052] Step S03: Theoretical analysis of the range of pressure arch formation in the stope mine: used to receive the geological data transmitted in the stope mine geological data acquisition step, and calculate the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock layer based on the pressure arch formation data acquired in the pressure arch formation data acquisition sub-step;

[0053] Step S04: Thick hard rock stratum fissure risk management in the stope mine: used to receive the geological data transmitted in the stope mine geological data collection step, and calculate the thick hard rock stratum fissure risk assessment index for each monitoring sub-area of ​​the stope mine rock stratum based on the thick hard rock stratum fissure data collected in the thick hard rock stratum fissure data collection sub-step;

[0054] Step S05: Display of stope mine pressure intensity prediction model: Calculate the stope mine pressure intensity prediction coefficient of the stope mine rock stratum based on the stope mine production safety stability index and thick hard rock stratum fissure risk assessment index of each monitoring sub-area of ​​the stope mine rock stratum;

[0055] Step S06: Optimization of the prediction model for the mine pressure intensity of the stope: Setting It is the initial model for predicting the pressure strength of the mine in the stope. The prediction results of each initial model are recorded and the optimal model is obtained through model training.

[0056] Step S07: Stope mine pressure warning: obtain the stope mine pressure intensity update coefficient of the stope mine rock layer, compare it with the preset stope mine pressure intensity classification warning coefficient, and process it.

[0057] Technical effects and advantages of the present invention:

[0058] 1. The present invention provides a method and system for predicting mine pressure in a stope mine based on pressure arch and thick hard rock strata. The method collects geological data of each monitoring sub-area of ​​the stope mine rock strata, calculates the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock strata based on the pressure arch formation data collected by the pressure arch formation data collection unit, calculates the thick hard rock stratum fissure risk assessment index of each monitoring sub-area of ​​the stope mine rock strata based on the thick hard rock stratum fissure data collection unit, further analyzes to obtain a stope mine pressure intensity prediction coefficient of the stope mine rock strata, calculates the index using the monitoring sub-area as a unit, and achieves accurate prediction based on the characteristics of each sub-area, thereby improving the accuracy of the prediction. The method collects geological data of each monitoring sub-area of ​​the stope mine rock strata, and combines the pressure arch formation data and the thick hard rock stratum fissure data to calculate the stope mine safety production stability index and the thick hard rock stratum fissure risk assessment index, thereby more accurately predicting the stope mine pressure intensity.

[0059] 2. The present invention provides a method and system for predicting the pressure coming from a stope mine based on pressure arch and thick hard rock layer, and uses the stope mine pressure intensity prediction model optimization module to set It is an initial model for predicting the intensity of mine pressure in the mine stope. The results of each prediction of the initial model are recorded. After the optimal model is obtained through model training, a preset low-risk warning coefficient of the mine pressure intensity, a preset medium-risk warning coefficient of the mine pressure intensity, and a preset high-risk warning coefficient of the mine pressure intensity are set. These are compared with the mine pressure intensity update coefficient of the mine rock stratum in the mine stope to carry out mine risk processing. By comparing with the preset graded warning coefficient, real-time monitoring and early warning of the mine pressure intensity are achieved, which helps to take timely measures to ensure production safety. By using the loss function and k-fold cross-validation to evaluate the stability of the model, the prediction results are optimized, the safety of personnel and equipment is further guaranteed, and safety accidents caused by mine pressure are reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a structural schematic diagram of the stope mine pressure prediction system based on pressure arch and thick hard rock layer of the present invention.

[0061] Figure 2 It is a flow chart of the method for predicting incoming pressure in a stope mine based on pressure arch and thick hard rock layer according to the present invention. DETAILED DESCRIPTION

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 making creative efforts are within the scope of protection of the present invention.

[0063] See also Figure 1 As shown, the present invention provides a mine pressure prediction system based on pressure arch and thick hard rock layer, including a mine three-dimensional geological model construction module, a mine geological data acquisition module, a mine pressure arch formation range theoretical analysis module, a mine thick hard rock layer fissure risk management module, a mine pressure intensity prediction model display module, a mine pressure intensity prediction model optimization module and a mine pressure warning module.

[0064] The three-dimensional geological model construction module of the mining area is connected to the mining area geological data acquisition module, the mining area geological data acquisition module is connected to the mining area pressure arch formation range theoretical analysis module and the mining area thick hard rock layer fissure risk management module, the mining area pressure arch formation range theoretical analysis module and the mining area thick hard rock layer fissure risk management module are connected to the mining area pressure intensity prediction model display module, the mining area pressure intensity prediction model display module is connected to the mining area pressure intensity prediction model optimization module, and the mining area pressure intensity prediction model optimization module is connected to the mining area pressure early warning module.

[0065] The stope mine three-dimensional geological model construction module uses three-dimensional modeling software to construct a three-dimensional spatial distribution model of the stope mine rock strata, and divides the stope mine rock strata into various monitoring sub-areas according to the equal height division method, and number each monitoring sub-area of ​​the stope mine rock strata.

[0066] In a possible design, the stope mine 3D geological model construction module is specifically:

[0067] S01: Use 3D modeling software to construct a 3D spatial distribution model of the mine rock strata and dynamically update the compressive strength prediction model;

[0068] S02: Divide the mining strata in the stope into monitoring sub-areas according to the equal height division method, and number the monitoring sub-areas of the mining strata in the stope as 1, 2, ..., i, ..., n in sequence from the top of the stratum.

[0069] The stope mine geological data acquisition module is used to collect geological data of each monitoring sub-area of ​​the stope mine rock strata. The stope mine geological data acquisition module includes a pressure arch formation data acquisition unit and a thick hard rock stratum crack data acquisition unit. The geological data includes pressure arch formation data and thick hard rock stratum crack data.

[0070] In one possible design, the stope mine geological data acquisition module is specifically:

[0071] Pressure arch formation data acquisition unit: collects the stope span, internal friction angle of thick hard rock layer, groundwater level depth, and temperature of thick hard rock layer in each monitoring sub-area of ​​the stope mine rock layer, and marks them as 、 、 、 , where i=1,2,...n, i represents the number of the i-th monitoring sub-area;

[0072] Thick hard rock fracture data acquisition unit: The vertical thickness of the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer is measured by geological radar, marked as ;Using ultrasonic testing equipment, transmitting probes and receiving probes are arranged on the rock surface of each monitoring sub-area to measure the compressive strength of the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer, marked as ; Collect the density and direction of the cracks in the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer in the stope, and mark them as 、 .

[0073] The stope mine pressure arch formation range theoretical analysis module is used to receive geological data transmitted by the stope mine geological data acquisition module, and calculate the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock layer based on the pressure arch formation data collected by the pressure arch formation data acquisition unit.

[0074] In a possible design, the stope mine pressure arch formation range theoretical analysis module is specifically:

[0075] S01: Calculate the pressure arch formation range of each monitoring sub-area based on the stope span and the internal friction angle of thick hard rock strata:

[0076]

[0077] in, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the stope span of the ith monitoring sub-area, It is expressed as the internal friction angle of thick hard rock layer in the i-th monitoring sub-area;

[0078] The span of the stope directly affects the range of pressure arch formation. When the span is larger, the height of the pressure arch is higher. When the internal friction angle is smaller, the range of pressure arch formation is larger. Conversely, the range of pressure arch formation is smaller.

[0079] S02: Based on the actual mining depth of the stope mine rock layer, the mechanical properties relaxation of the thick hard rock layer in each monitoring sub-area is calculated through the stope span, groundwater level depth, and thick hard rock layer temperature:

[0080]

[0081] in, It is expressed as the mechanical property relaxation of thick hard rock formation in the i-th monitoring sub-area, is the groundwater level depth of the ith monitoring sub-area, H is the actual mining depth, is the temperature of the thick hard rock layer in the ith monitoring sub-area, e is a natural constant, Expressed as temperature impact factor;

[0082] When the stope span is larger, the stress on the rock mass is more concentrated, resulting in more significant rock mass relaxation and greater relaxation of the mechanical properties of thick and hard rock formations. When the groundwater level is shallower and the water content of the rock mass is higher, the rock mass relaxation is more significant and greater relaxation of the mechanical properties of thick and hard rock formations is. When the temperature of thick and hard rock formations is higher, the viscous deformation of the rock mass is accelerated, resulting in more significant rock mass relaxation and greater relaxation of the mechanical properties of thick and hard rock formations. Conversely, when the stope span is smaller, the groundwater level is deeper, and the temperature of thick and hard rock formations is lower, the rock mass relaxation is not significant and the relaxation of the mechanical properties of thick and hard rock formations is smaller.

[0083] S03: The calculation formula of the mine safety production stability index is:

[0084]

[0085] in, It is expressed as the mine safety production stability index of the i-th monitoring sub-area, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the maximum value of the pressure arch formation range, It is expressed as the relaxation of mechanical properties of thick hard rock formation in the i-th monitoring sub-area;

[0086] The larger the range of pressure arch formation, the worse the mine stability and the larger the mine safety production stability index. The greater the relaxation of the mechanical properties of thick and hard rock layers and the more significant the deformation of the rock mass, the worse the mine stability and the larger the mine safety production stability index. Conversely, the better the mine stability, the smaller the mine safety production stability index.

[0087] The stope mine thick hard rock stratum fissure risk management module is used to receive geological data transmitted by the stope mine geological data acquisition module, and calculate the thick hard rock stratum fissure risk assessment index of each monitoring sub-area of ​​the stope mine rock stratum based on the thick hard rock stratum fissure data collected by the thick hard rock stratum fissure data acquisition unit.

[0088] In a possible design, the calculation formula for the thick hard rock formation fracture risk assessment index is:

[0089]

[0090] in, It is expressed as the risk assessment index of thick hard rock fracture in the i-th monitoring sub-area, It is expressed as the vertical thickness of the thick hard rock layer in the i-th monitoring sub-area, It is expressed as the compressive strength of thick hard rock layer in the i-th monitoring sub-area, It is expressed as the crack density of thick hard rock layer in the i-th monitoring sub-area, It is represented as the crack direction of thick hard rock layer in the i-th monitoring sub-area, It is expressed as the mean value of the crack density in thick hard rock layers, 、 They are respectively expressed as the compressive strength of thick hard rock layer and the attenuation coefficient of the crack direction of thick hard rock layer, and e is expressed as a natural constant;

[0091] The density of cracks in thick hard rock formations is positively correlated with risk. The higher the density, the greater the risk assessment index of cracks in thick hard rock formations. The compressive strength of thick hard rock formations has a suppressive effect on risk. The higher the strength, the attenuated risk assessment index of cracks in thick hard rock formations. The direction of cracks is positively correlated with risk. The greater the direction, the greater the risk assessment index of cracks in thick hard rock formations. The greater the vertical thickness of thick hard rock formations, the greater the barrier effect on the expansion of rock formation cracks.

[0092] in, , n represents the number of monitoring sub-areas.

[0093] The stope mine pressure intensity prediction model display module calculates the stope mine pressure intensity prediction coefficient of the stope mine rock stratum based on the stope mine production safety stability index and thick hard rock stratum crack risk assessment index of each monitoring sub-area of ​​the stope mine rock stratum.

[0094] In a possible design, the calculation formula for the stope mine pressure intensity prediction coefficient is:

[0095]

[0096] in, It is expressed as the prediction coefficient of the mine pressure intensity at the stope. It is expressed as the mine safety production stability index of the i-th monitoring sub-area, It is expressed as the mine safety production stability index of the i-1th monitoring sub-area, It is expressed as the risk assessment index of thick hard rock fracture in the i-th monitoring sub-area, It is expressed as the thick hard rock fracture risk assessment index of the i-1th monitoring sub-area, It is represented as the pressure time of the i-th monitoring sub-area, It is represented as the division height of the monitoring sub-area, 、 They are the weight coefficients of the mine safety production stability index and the thick hard rock stratum fissure risk assessment index, respectively, and n is the number of monitoring sub-areas.

[0097] In this embodiment, it should be specifically explained that the calculation formula for the pressure time is:

[0098]

[0099] in, It is represented as the pressure time of the i-th monitoring sub-area, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the stope span of the ith monitoring sub-area, Expressed as the viscosity coefficient of the rock formation.

[0100] The stope mine pressure intensity prediction model optimization module: setting It is the initial model for predicting the pressure strength of the mine in the stope. The prediction results of each initial model are recorded, and the optimal model is obtained through model training.

[0101] In one possible design, the stope mine pressure intensity prediction model optimization module is specifically:

[0102] S01: Use the stope mine compressive strength prediction coefficient of the stope mine rock layer as the initial model, record the prediction results of the initial model of the jth sample, and preliminarily set the weight w according to expert opinions;

[0103] S02: Use the loss function to adjust the weights. The formula is:

[0104] ,

[0105] in, It is expressed as the loss function of the prediction coefficient of the mine pressure strength of the stope, m is the number of samples, It is expressed as the prediction coefficient of the mine pressure intensity of the j-th sample, It represents the preset stope mine pressure intensity prediction coefficient, w represents the initial set weight, Represents the updated weight, and y represents the learning rate;

[0106] S03: Use k-fold cross validation to evaluate the stability of the model. Divide the sample data set into k subsets, train the model with k-1 subsets each time, and use the remaining subset for validation. Calculate the model optimization coefficient:

[0107] ,in, Expressed as the model optimization coefficient of the j-th sample;

[0108] S04: The optimal model is as follows:

[0109] ,in, Expressed as the mean of the model optimization coefficients, ;

[0110] S05: According to the updated optimal model, Set as the update coefficient of the mine pressure intensity in the stope.

[0111] The stope mine pressure warning module obtains the stope mine pressure intensity update coefficient of the stope mine rock layer, compares it with the preset stope mine pressure intensity classification warning coefficient, and processes it.

[0112] In one possible design, the stope mine pressure warning module is specifically:

[0113] Set a preset low-risk warning coefficient for the mine pressure intensity of the mine, a preset medium-risk warning coefficient for the mine pressure intensity of the mine, and a preset high-risk warning coefficient for the mine pressure intensity of the mine. When the mine pressure intensity update coefficient of the mine rock stratum is less than or equal to the preset low-risk warning coefficient for the mine pressure intensity of the mine, it indicates that the mine pressure intensity of the mine rock stratum is in a low-risk state, the production safety is high, and only routine monitoring and maintenance are required; when the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset low-risk warning coefficient for the mine pressure intensity of the mine and is less than or equal to the preset medium-risk warning coefficient for the mine pressure intensity of the mine, it indicates that the mine rock stratum is in a low-risk state, the production safety is high, and only routine monitoring and maintenance are required; when the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset low-risk warning coefficient for the mine pressure intensity of the mine and is less than or equal to the preset medium-risk warning coefficient for the mine pressure intensity of the mine, it indicates that the mine rock stratum is in a high-risk state The pressure intensity of the mine layer is in a medium-risk state, and monitoring needs to be strengthened to prevent potential safety accidents; when the mine pressure intensity update coefficient of the mine rock layer is greater than the preset mine pressure intensity medium-risk warning coefficient and is less than or equal to the preset mine pressure intensity high-risk warning coefficient, it indicates that the pressure intensity of the mine rock layer is in a high-risk state, and emergency measures must be taken immediately; when the mine pressure intensity update coefficient of the mine rock layer is greater than the preset mine pressure intensity high-risk warning coefficient, it indicates that the pressure intensity of the mine rock layer is extremely high, there are serious safety hazards, and an immediate full shutdown must be carried out to trigger a red warning.

[0114] See also Figure 2 As shown, in this embodiment, it should be specifically explained that the present invention provides a method for predicting incoming pressure in a stope mine based on pressure arch and thick hard rock layer, comprising the following steps:

[0115] Step S01: Construction of a three-dimensional geological model of the stope mine: Using three-dimensional modeling software, a three-dimensional spatial distribution model of the stope mine rock strata is constructed, and the stope mine rock strata is divided into various monitoring sub-areas according to the equal height division method, and each monitoring sub-area of ​​the stope mine rock strata is numbered;

[0116] Step S02: stope mine geological data collection: used to collect geological data of each monitoring sub-area of ​​the stope mine rock strata, the stope mine geological data collection includes a pressure arch formation data collection sub-step and a thick hard rock stratum fissure data collection sub-step, and the geological data includes pressure arch formation data and thick hard rock stratum fissure data;

[0117] Step S03: Theoretical analysis of the range of pressure arch formation in the stope mine: used to receive the geological data transmitted in the stope mine geological data acquisition step, and calculate the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock layer based on the pressure arch formation data acquired in the pressure arch formation data acquisition sub-step;

[0118] Step S04: Thick hard rock stratum fissure risk management in the stope mine: used to receive the geological data transmitted in the stope mine geological data collection step, and calculate the thick hard rock stratum fissure risk assessment index for each monitoring sub-area of ​​the stope mine rock stratum based on the thick hard rock stratum fissure data collected in the thick hard rock stratum fissure data collection sub-step;

[0119] Step S05: Display of stope mine pressure intensity prediction model: Calculate the stope mine pressure intensity prediction coefficient of the stope mine rock stratum based on the stope mine production safety stability index and thick hard rock stratum fissure risk assessment index of each monitoring sub-area of ​​the stope mine rock stratum;

[0120] Step S06: Optimization of the prediction model for the mine pressure intensity of the stope: Setting It is the initial model for predicting the pressure strength of the mine in the stope. The prediction results of each initial model are recorded and the optimal model is obtained through model training.

[0121] Step S07: Stope mine pressure warning: obtain the stope mine pressure intensity update coefficient of the stope mine rock layer, compare it with the preset stope mine pressure intensity classification warning coefficient, and process it.

[0122] In this embodiment, it should be specifically explained that the present invention collects geological data of each monitoring sub-area of ​​the mine rock formation in the mine field, calculates the mine safety production stability index of each monitoring sub-area of ​​the mine rock formation in the mine field based on the pressure arch formation data collected by the pressure arch formation data collection unit, calculates the thick hard rock layer fracture risk assessment index of each monitoring sub-area of ​​the mine rock formation in the mine field based on the thick hard rock layer fracture data collected by the thick hard rock layer fracture data collection unit, further analyzes to obtain the mine pressure intensity prediction coefficient of the mine rock formation in the mine field, calculates the index calculation based on the monitoring sub-area, and realizes accurate prediction based on the characteristics of each sub-area, thereby improving the accuracy of the prediction, and collects geological data of each monitoring sub-area of ​​the mine rock formation in the mine field, and combines the pressure arch formation data and the thick hard rock layer fracture data to calculate the mine safety production stability index and the thick hard rock layer fracture risk assessment index, thereby more accurately predicting the mine pressure intensity of the mine field;

[0123] The present invention uses the mining site to optimize the strength prediction model module, setting It is an initial model for predicting the intensity of mine pressure in the mine stope. The results of each prediction of the initial model are recorded. After the optimal model is obtained through model training, a preset low-risk warning coefficient of the mine pressure intensity, a preset medium-risk warning coefficient of the mine pressure intensity, and a preset high-risk warning coefficient of the mine pressure intensity are set. These are compared with the mine pressure intensity update coefficient of the mine rock stratum in the mine stope to carry out mine risk processing. By comparing with the preset graded warning coefficient, real-time monitoring and early warning of the mine pressure intensity are achieved, which helps to take timely measures to ensure production safety. By using the loss function and k-fold cross-validation to evaluate the stability of the model, the prediction results are optimized, the safety of personnel and equipment is further guaranteed, and safety accidents caused by mine pressure are reduced.

[0124] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A mine pressure prediction system based on pressure arch and thick hard rock formations, characterized by: include: Module for constructing a three-dimensional geological model of the stope mine: Use three-dimensional modeling software to construct a three-dimensional spatial distribution model of the stope mine rock strata, divide the stope mine rock strata into various monitoring sub-areas according to the equal height division method, and number each monitoring sub-area of ​​the stope mine rock strata; Stope mine geological data acquisition module: used to collect geological data of each monitoring sub-area of ​​the stope mine rock layer, the stope mine geological data acquisition module includes a pressure arch formation data acquisition unit and a thick hard rock layer fracture data acquisition unit; Theoretical analysis module of the formation range of stope mine pressure arch: used to calculate the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock layer; Thick hard rock strata fissure risk management module for stope mines: used to calculate the thick hard rock strata fissure risk assessment index for each monitoring sub-area of ​​the stope mine rock strata; The stope mine pressure intensity prediction model display module calculates the stope mine pressure intensity prediction coefficient of the stope mine rock strata based on the stope mine safety production stability index and thick hard rock strata fissure risk assessment index of each monitoring sub-area of ​​the stope mine rock strata; Mining pressure intensity prediction model optimization module: Setting It is the initial model for predicting the pressure strength of the mine in the stope. The prediction results of each initial model are recorded and the optimal model is obtained through model training. The stope mine pressure intensity prediction model optimization module is specifically: S71: using the stope mine compressive strength prediction coefficient of the stope mine rock layer as the initial model, recording the prediction result of the initial model of the jth sample, and preliminarily setting the weight w according to expert opinion; S72: Use the loss function to adjust the weights. The formula is: ， in, It is expressed as the loss function of the prediction coefficient of the mine pressure strength of the stope, m is the number of samples, It is expressed as the prediction coefficient of the mine pressure intensity of the j-th sample, It represents the preset stope mine pressure intensity prediction coefficient, w represents the initial set weight, Represents the updated weight, and y represents the learning rate; S73: Use k-fold cross validation to evaluate the stability of the model. Divide the sample data set into k subsets, train the model with k-1 subsets each time, and use the remaining subset for validation. Calculate the model optimization coefficient: ,in, Expressed as the model optimization coefficient of the j-th sample; S74: The optimal model is formulated as follows: ,in, Expressed as the mean of the model optimization coefficients, ; S75: According to the updated optimal model, Set as the update coefficient of the mine pressure intensity in the stope; Stope mine pressure warning module: obtains the stope mine pressure intensity update coefficient of the stope mine rock stratum, compares it with the preset stope mine pressure intensity classification warning coefficient, and processes it.

2. The stope mine pressure prediction system based on pressure arch and thick hard rock layer according to claim 1 is characterized by: The stope mine 3D geological model construction module is specifically: S21: Use 3D modeling software to construct a 3D spatial distribution model of the mine rock strata and dynamically update the compressive strength prediction model; S22: Divide the mining strata in the stope into monitoring sub-areas according to a division method of equal height, and number the monitoring sub-areas of the mining strata in the stope as 1, 2, ..., i, ..., n in sequence from the top of the stratum.

3. The stope mine pressure prediction system based on pressure arch and thick hard rock layer according to claim 1 is characterized by: The stope mine geological data acquisition module is specifically: Pressure arch formation data acquisition unit: collects the stope span, internal friction angle of thick hard rock layer, groundwater level depth, and temperature of thick hard rock layer in each monitoring sub-area of ​​the stope mine rock layer, and marks them as 、 、 、 , where i=1,2,...n, i represents the number of the i-th monitoring sub-area; Thick hard rock fracture data acquisition unit: The vertical thickness of the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer is measured by geological radar, marked as ; By using ultrasonic testing equipment, transmitting probes and receiving probes are arranged on the rock surface of each monitoring sub-area to measure the compressive strength of the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer, marked as ; Collect the density and direction of the cracks in the thick hard rock layer in each monitoring sub-area of ​​the mine rock layer in the stope, and mark them as 、 .

4. The stope mine pressure prediction system based on pressure arch and thick hard rock layer according to claim 1 is characterized by: The theoretical analysis module of the range of pressure arch formation in the stope mine is specifically as follows: S41: Calculate the pressure arch formation range of each monitoring sub-area based on the stope span and the internal friction angle of the thick hard rock layer: in, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the stope span of the ith monitoring sub-area, It is expressed as the internal friction angle of thick hard rock layer in the i-th monitoring sub-area; S42: Based on the actual mining depth of the stope mine rock layer, the mechanical properties relaxation of the thick hard rock layer in each monitoring sub-area is calculated through the stope span, groundwater level depth, and thick hard rock layer temperature: in, It is expressed as the mechanical property relaxation of thick hard rock formation in the i-th monitoring sub-area, is the groundwater level depth of the ith monitoring sub-area, H is the actual mining depth, is the temperature of the thick hard rock layer in the ith monitoring sub-area, e is a natural constant, Expressed as temperature impact factor; S43: The calculation formula of the mine safety production stability index is: in, It is expressed as the mine safety production stability index of the i-th monitoring sub-area, It is expressed as the pressure arch formation range of the i-th monitoring sub-area, Expressed as the maximum value of the pressure arch formation range, It is expressed as the mechanical property relaxation of thick hard rock formation in the i-th monitoring sub-area.

5. The stope mine pressure prediction system based on pressure arch and thick hard rock layer according to claim 1 is characterized by: The calculation formula for the thick hard rock layer crack risk assessment index is: in, It is expressed as the risk assessment index of thick hard rock fracture in the i-th monitoring sub-area, It is expressed as the vertical thickness of the thick hard rock layer in the i-th monitoring sub-area, It is expressed as the compressive strength of thick hard rock layer in the i-th monitoring sub-area, It is expressed as the crack density of thick hard rock layer in the i-th monitoring sub-area, It is represented as the crack direction of thick hard rock layer in the i-th monitoring sub-area, It is expressed as the mean value of the crack density in thick hard rock layers, 、 They are respectively expressed as the compressive strength of thick hard rock layers and the attenuation coefficient in the crack direction of thick hard rock layers, and e is expressed as a natural constant.

6. The stope mine pressure prediction system based on pressure arch and thick hard rock layer according to claim 1, characterized in that: The calculation formula for the prediction coefficient of the mine pressure intensity of the stope is: in, It is expressed as the prediction coefficient of the mine pressure intensity at the stope. It is expressed as the mine safety production stability index of the i-th monitoring sub-area, It is expressed as the mine safety production stability index of the i-1th monitoring sub-area, It is expressed as the risk assessment index of thick hard rock fracture in the i-th monitoring sub-area, It is expressed as the thick hard rock fracture risk assessment index of the i-1th monitoring sub-area, It is represented as the pressure time of the i-th monitoring sub-area, It is represented as the division height of the monitoring sub-area, 、 They are the weight coefficients of the mine safety production stability index and the thick hard rock stratum fissure risk assessment index, respectively, and n is the number of monitoring sub-areas.

7. The stope mine pressure prediction system based on pressure arch and thick hard rock layer according to claim 1, characterized in that: The stope mine pressure warning module is specifically: Set a preset low-risk warning coefficient for the mine pressure intensity of the stope mine, a preset medium-risk warning coefficient for the mine pressure intensity of the stope mine, and a preset high-risk warning coefficient for the mine pressure intensity of the stope mine. When the mine pressure intensity update coefficient of the stope mine rock stratum is less than or equal to the preset low-risk warning coefficient for the mine pressure intensity of the stope mine, it indicates that the pressure intensity of the stope mine rock stratum is in a low-risk state, the production safety is relatively high, and only routine monitoring and maintenance are required; When the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset mine pressure intensity low risk warning coefficient and is less than or equal to the preset mine pressure intensity medium risk warning coefficient, it indicates that the mine pressure intensity of the mine rock stratum is in a medium risk state and needs to be strengthened to prevent potential safety accidents; when the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset mine pressure intensity medium risk warning coefficient and is less than or equal to the preset mine pressure intensity high risk warning coefficient, it indicates that the mine pressure intensity of the mine rock stratum is in a high risk state and emergency measures must be taken immediately; When the mine pressure intensity update coefficient of the mine rock stratum is greater than the preset mine pressure intensity high risk warning coefficient, it indicates that the mine rock stratum pressure intensity is extremely high and there are serious safety hazards. An immediate and comprehensive shutdown must be carried out, triggering a red warning.

8. A method for predicting incoming pressure in a stope mine based on pressure arch and thick hard rock strata, using a system for predicting incoming pressure in a stope mine based on pressure arch and thick hard rock strata according to any one of claims 1 to 7, characterized in that: The following steps are involved: Step S01: Construction of a three-dimensional geological model of the stope mine: Using three-dimensional modeling software, a three-dimensional spatial distribution model of the stope mine rock strata is constructed, and the stope mine rock strata is divided into various monitoring sub-areas according to the equal height division method, and each monitoring sub-area of ​​the stope mine rock strata is numbered; Step S02: stope mine geological data collection: used to collect geological data of each monitoring sub-area of ​​the stope mine rock strata, the stope mine geological data collection includes a pressure arch formation data collection sub-step and a thick hard rock stratum fissure data collection sub-step, and the geological data includes pressure arch formation data and thick hard rock stratum fissure data; Step S03: Theoretical analysis of the range of pressure arch formation in the stope mine: used to receive the geological data transmitted in the stope mine geological data acquisition step, and calculate the stope mine safety production stability index of each monitoring sub-area of ​​the stope mine rock layer based on the pressure arch formation data acquired in the pressure arch formation data acquisition sub-step; Step S04: Thick hard rock stratum fissure risk management in the stope mine: used to receive the geological data transmitted in the stope mine geological data collection step, and calculate the thick hard rock stratum fissure risk assessment index for each monitoring sub-area of ​​the stope mine rock stratum based on the thick hard rock stratum fissure data collected in the thick hard rock stratum fissure data collection sub-step; Step S05: Display of stope mine pressure intensity prediction model: Calculate the stope mine pressure intensity prediction coefficient of the stope mine rock stratum based on the stope mine production safety stability index and thick hard rock stratum fissure risk assessment index of each monitoring sub-area of ​​the stope mine rock stratum; Step S06: Optimization of the prediction model for the mine pressure intensity of the stope: Setting It is the initial model for predicting the pressure strength of the mine in the stope. The prediction results of each initial model are recorded and the optimal model is obtained through model training. Step S07: Stope mine pressure warning: obtain the stope mine pressure intensity update coefficient of the stope mine rock layer, compare it with the preset stope mine pressure intensity classification warning coefficient, and process it.

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