Thin seam working face coal mining scheme evaluation method, device and equipment and storage medium

Abstract

The invention provides a thin seam working face coal mining scheme evaluation method and device, equipment and a storage medium, and relates to the technical field of coal mining. In some embodiments of the invention, basic parameters of the working face of the thin coal seam are obtained through a multi-source sensing device; constructing a surrounding rock stability sensitivity evaluation index based on the basic parameters and the rock mass mechanical parameters; based on the dynamic rock stratum response mechanism and the surrounding rock stability sensitivity evaluation index, a mining influence range dynamic coefficient is calculated; based on the mining influence range dynamic coefficient, establishing a mining efficiency comprehensive evaluation function; processing the mining efficiency comprehensive evaluation function and the mining influence range dynamic coefficient through a nonlinear combination algorithm, and generating a feasibility index of the coal mining scheme of the thin seam working face; evaluating the feasibility index according to a third-level threshold standard; correcting model parameters corresponding to the coal mining scheme according to the evaluation result; the evaluation accuracy of the coal mining scheme is improved, and the model parameter accuracy corresponding to the coal mining scheme is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of coal mining technology, and in particular to a method, device, equipment and storage medium for evaluating a coal mining plan for a thin coal seam working face. Background Art

[0002] Currently, the evaluation of mining plans for thin coal seam working faces primarily relies on traditional empirical judgment and analysis of field data. Engineers typically develop mining plans based on a comprehensive analysis of coal seam occurrence conditions, mining process suitability, geological structure distribution, and existing working face recovery. They then use simulation software to perform physical or numerical simulations to estimate mining efficiency, safety risks, and resource recovery rates.

[0003] However, on the one hand, the evaluation results rely on expert experience and subjective judgment, and lack a standardized quantitative indicator system, which leads to a certain degree of subjectivity and non-replicability in the evaluation results; on the other hand, in the simulation and parameter setting process, the characteristics of thin coal seam mining, such as the small impact range, drastic spatial changes, and the sensitivity of mining disturbances to surrounding rock stability, are often not fully considered, which can easily lead to deviations in scheme evaluation.

[0004] At present, the evaluation accuracy of coal mining plans is low, and the accuracy of model parameters corresponding to coal mining plans is low.

[0005] Public content

[0006] The present disclosure provides a method, device, equipment and storage medium for evaluating a coal mining plan for a thin coal seam working face, so as to at least solve the problem that the evaluation accuracy of existing coal mining plans is low and the accuracy of model parameters corresponding to the coal mining plans is low.

[0007] The technical solutions disclosed in this disclosure are as follows:

[0008] The present disclosure provides a method for evaluating a coal mining plan for a thin coal seam working face, comprising:

[0009] Obtain basic parameters of thin coal seam working face through multi-source sensing device;

[0010] Based on the basic parameters and rock mass mechanical parameters, construct a surrounding rock stability sensitivity evaluation index;

[0011] Calculate the dynamic coefficient of the mining impact range based on the dynamic rock response mechanism and the surrounding rock stability sensitivity evaluation index;

[0012] Based on the dynamic coefficient of the mining impact range, a comprehensive evaluation function of mining efficiency is established;

[0013] Processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme of the thin coal seam working face;

[0014] Evaluate the feasibility index according to the three-level threshold standard to obtain an evaluation result;

[0015] The model parameters corresponding to the coal mining scheme are modified according to the evaluation results to obtain an updated model.

[0016] Optionally, the basic parameters include: coal seam thickness, roof and floor lithology, depth, inclination, and geological structure complexity; the rock mass mechanics parameters include: surrounding rock compressive strength and surrounding rock tensile strength; based on the basic parameters and rock mass mechanics parameters, a surrounding rock stability sensitivity evaluation index is constructed, including:

[0017] linearly combining a parameter of a product of the coal seam thickness and the lithology of the roof and floor with a parameter of a ratio of a sine function of the mining depth and the inclination angle to obtain a value of the linear combination;

[0018] The linear combination value is combined with a first correction coefficient and an exponential decay of the geological structure complexity to perform correction to obtain a sensitivity factor;

[0019] Correcting the sensitivity factor according to a second correction coefficient, a ratio parameter of the surrounding rock compressive strength to the surrounding rock tensile strength, and a logarithmic relationship of elastic parameters to obtain a surrounding rock stability sensitivity evaluation index;

[0020] The calculation formula of the surrounding rock stability sensitivity evaluation index is:

[0021]

[0022] Among them, RSI is the sensitivity evaluation index of surrounding rock stability, k1 and k2 are the first correction coefficient and the second correction coefficient respectively, h is the thickness of the coal seam, r is the lithology of the roof and floor, d is the depth, α is the inclination angle, f is the complexity of the geological structure, σ c is the compressive strength of surrounding rock, σ t is the tensile strength of the surrounding rock, E is the elastic modulus, and μ is the Poisson's ratio.

[0023] Optionally, the method further includes:

[0024] A regression model was established using on-site surrounding rock mechanics test data;

[0025] Parameter calibration is performed based on the regression model in combination with historical working face stability monitoring data to obtain the first correction coefficient and the second correction coefficient.

[0026] Optionally, the calculation of the dynamic coefficient of the mining impact range based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index includes:

[0027] Integrating the surrounding rock stability sensitivity evaluation index and the square parameter of the coal seam thickness in the spatial domain to obtain a spatial disturbance potential energy term;

[0028] Combined with the time gradient parameters of the stope stress field, the ring integral operation is performed in the surface domain to determine the ring integral term of the time derivative of the stress disturbance;

[0029] Dynamically coupling the spatial disturbance potential energy term and the time derivative loop integral term through preset weights to obtain the dynamic coefficient of the mining influence range;

[0030] The calculation formula of the dynamic coefficient of the mining impact range is:

[0031]

[0032] Among them, DIF is the dynamic coefficient of the mining influence range, β1 and β2 are the first weight and the second weight, p is the stope stress, t is time, x and s are the first spatial variable and the second spatial variable, respectively.

[0033] Optionally, establishing a comprehensive evaluation function of mining efficiency based on the dynamic coefficient of the mining impact range includes:

[0034] Obtaining a first ratio of a product parameter of the mining impact range dynamic coefficient and the advancing speed to the output;

[0035] The first ratio and a second ratio of the product of the cost and the recovery rate to the service time are weightedly combined to obtain the comprehensive evaluation function of mining efficiency.

[0036] Optionally, the processing of the comprehensive evaluation function of mining efficiency and the dynamic coefficient of the mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face includes:

[0037] Performing a nonlinear combination of the comprehensive evaluation function of mining efficiency and the exponential decay term of the surrounding rock stability index to obtain a value of the nonlinear combination;

[0038] The value of the nonlinear combination is combined with the power function correction of the dynamic coefficient of the mining impact range to obtain a corrected value;

[0039] The corrected value is superimposed on the weighted score of each evaluation indicator to obtain the feasibility index.

[0040] Optionally, the modifying the model parameters corresponding to the coal mining scheme according to the evaluation result to obtain an updated model includes:

[0041] Compare and analyze the monitoring data of the implementation phase with the forecast results to obtain the analysis results;

[0042] The model parameters are automatically modified according to the analysis results to obtain an updated model.

[0043] The present disclosure also provides a device for evaluating a coal mining plan for a thin coal seam working face, comprising:

[0044] An acquisition module is used to acquire basic parameters of the thin coal seam working face through a multi-source sensing device;

[0045] A construction module for constructing a surrounding rock stability sensitivity evaluation index based on the basic parameters and rock mass mechanics parameters;

[0046] A calculation module, configured to calculate a dynamic coefficient of a mining impact range based on a dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index;

[0047] Establishing a module for establishing a comprehensive evaluation function of mining efficiency based on the dynamic coefficient of the mining impact range;

[0048] A generating module, configured to process the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face;

[0049] An evaluation module, configured to evaluate the feasibility index according to a three-level threshold standard to obtain an evaluation result;

[0050] The correction module is used to correct the model parameters corresponding to the coal mining plan according to the evaluation results to obtain an updated model.

[0051] The present disclosure also provides an electronic device, including:

[0052] processor;

[0053] a memory for storing processor-executable instructions;

[0054] The processor is configured to execute instructions to implement each step in the above method.

[0055] The embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, each step in the above method is implemented.

[0056] The technical solutions provided by the embodiments of the present disclosure bring at least the following beneficial effects:

[0057] In some embodiments of the present disclosure, basic parameters of the thin coal seam working face are obtained through a multi-source sensing device; based on the basic parameters and rock mechanics parameters, a surrounding rock stability sensitivity evaluation index is constructed; based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index, the dynamic coefficient of the mining influence range is calculated; based on the dynamic coefficient of the mining influence range, a comprehensive evaluation function of mining efficiency is established; the comprehensive evaluation function of mining efficiency and the dynamic coefficient of the mining influence range are processed by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face; the feasibility index is evaluated according to the three-level threshold standard to obtain an evaluation result; according to the evaluation result, the model parameters corresponding to the coal mining scheme are corrected to obtain an updated model; the present disclosure performs a multi-dimensional evaluation of the coal mining scheme through the surrounding rock stability sensitivity evaluation index, the mining influence range dynamic coefficient, the mining efficiency comprehensive evaluation function and the feasibility index, so as to improve the evaluation accuracy of the coal mining scheme and improve the accuracy of the model parameters corresponding to the coal mining scheme.

[0058] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute an improper limitation of the present disclosure.

[0060] Figure 1 A scenario diagram of a method for evaluating a coal mining plan for a thin coal seam working face provided by the present disclosure;

[0061] Figure 2 A flow chart of a method for evaluating a coal mining plan for a thin coal seam working face provided by the present disclosure;

[0062] Figure 3 This is a schematic structural diagram of a thin coal seam working face mining plan evaluation device provided by the present disclosure;

[0063] Figure 4 A schematic diagram of an electronic device according to an embodiment of the present disclosure;

[0064] Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0065] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0066] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0067] It should be noted that the user information involved in this disclosure includes but is not limited to: user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure comply with the relevant laws and regulations and do not violate public order and good morals.

[0068] In response to the above technical problems, in some embodiments of the present disclosure, basic parameters of the thin coal seam working face are obtained through a multi-source sensing device; based on the basic parameters and rock mechanics parameters, a surrounding rock stability sensitivity evaluation index is constructed; based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index, the dynamic coefficient of the mining influence range is calculated; based on the dynamic coefficient of the mining influence range, a comprehensive evaluation function of mining efficiency is established; the comprehensive evaluation function of mining efficiency and the dynamic coefficient of the mining influence range are processed by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face; the feasibility index is evaluated according to the three-level threshold standard to obtain an evaluation result; according to the evaluation result, the model parameters corresponding to the coal mining scheme are corrected to obtain an updated model; the present disclosure conducts a multi-dimensional evaluation of the coal mining scheme through the surrounding rock stability sensitivity evaluation index, the mining influence range dynamic coefficient, the mining efficiency comprehensive evaluation function and the feasibility index, so as to improve the evaluation accuracy of the coal mining scheme and improve the accuracy of the model parameters corresponding to the coal mining scheme.

[0069] Figure 1 This is a scenario diagram of a thin coal seam working face mining plan evaluation method provided by the present disclosure. Figure 1 As shown, the terminal and server are connected via a network, such as a wired or wireless network. Terminals include, but are not limited to, portable devices such as mobile phones and tablets installed with various network platform applications, as well as fixed devices such as computers, kiosks, and advertising machines. The server provides various business services to users, including service push servers and user recommendation servers.

[0070] It should be noted that Figure 1The scenario diagram of a thin coal seam working face mining plan evaluation method shown is only an example. The terminal, server and application scenario described in the embodiment of the present disclosure are intended to more clearly illustrate the technical solution of the embodiment of the present disclosure, and do not generate any limitation on the technical solution provided by the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system and the emergence of new business scenarios, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0071] Among them, the terminal can be used to:

[0072] Obtain basic parameters of thin coal seam working face through multi-source sensing device;

[0073] Based on basic parameters and rock mass mechanical parameters, a sensitivity evaluation index of surrounding rock stability is constructed;

[0074] Calculate the dynamic coefficient of mining impact range based on dynamic rock response mechanism and surrounding rock stability sensitivity evaluation index;

[0075] Based on the dynamic coefficient of mining impact range, a comprehensive evaluation function of mining efficiency is established;

[0076] The feasibility index of the mining scheme for thin coal seam working face is generated by processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range through nonlinear combination algorithm;

[0077] The feasibility index is evaluated according to the three-level threshold standard to obtain the evaluation results;

[0078] According to the evaluation results, the model parameters corresponding to the coal mining plan are modified to obtain an updated model.

[0079] Figure 2 A flow chart of a method for evaluating a coal mining plan for a thin coal seam working face provided by the present disclosure includes the following steps:

[0080] Step 201: Obtain basic parameters of the thin coal seam working face through a multi-source sensing device;

[0081] Step 202: constructing a surrounding rock stability sensitivity evaluation index based on basic parameters and rock mass mechanical parameters;

[0082] Step 203: Calculate the dynamic coefficient of the mining impact range based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index;

[0083] Step 204: establishing a comprehensive evaluation function of mining efficiency based on the dynamic coefficient of the mining impact range;

[0084] Step 205: Processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face;

[0085] Step 206: Evaluate the feasibility index according to the three-level threshold standard to obtain an evaluation result;

[0086] Step 207: Modify the model parameters corresponding to the coal mining plan according to the evaluation results to obtain an updated model.

[0087] In this embodiment, the basic parameters of the thin coal seam working face are obtained through a multi-source sensing device; based on the basic parameters and rock mechanics parameters, a surrounding rock stability sensitivity evaluation index is constructed; based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index, the dynamic coefficient of the mining influence range is calculated; based on the dynamic coefficient of the mining influence range, a comprehensive evaluation function of mining efficiency is established; the comprehensive evaluation function of mining efficiency and the dynamic coefficient of the mining influence range are processed by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face; the feasibility index is evaluated according to the three-level threshold standard to obtain an evaluation result; according to the evaluation result, the model parameters corresponding to the coal mining scheme are corrected to obtain an updated model; the present disclosure performs a multi-dimensional evaluation of the coal mining scheme through the surrounding rock stability sensitivity evaluation index, the mining influence range dynamic coefficient, the mining efficiency comprehensive evaluation function and the feasibility index, so as to improve the evaluation accuracy of the coal mining scheme and improve the accuracy of the model parameters corresponding to the coal mining scheme.

[0088] Step 201: Obtain basic parameters of the thin coal seam working face through a multi-source sensing device.

[0089] Specifically, by deploying various types of sensors, we can achieve real-time, high-precision perception of key geological and engineering parameters of thin coal seam working faces, and form a data set for model calculation. The acquired content includes but is not limited to:

[0090] Coal seam thickness (h): using geological radar, ultrasonic thickness gauge, etc.;

[0091] Roof and floor lithology (r): combined with sonic logging, resistivity sensors, seismic wave inversion and other methods;

[0092] Depth (d): Automatically converted by combining 3D geological modeling and absolute elevation information;

[0093] Tilt angle (α): measured by inertial measurement unit (IMU) or borehole inclinometer;

[0094] Geological structural complexity (f): based on geological structure recognition algorithm and tension / stress disturbance perception (stress sensor array);

[0095] Mechanical parameters of surrounding rock (σ c , σ t , E, μ): Confirmed by core testing and field inversion.

[0096] The above datasets are multi-source and heterogeneous, coming from different types of sensing equipment; they are spatiotemporally coupled, with clear timestamps and spatial coordinates; they can be dynamically updated, and are collected and updated in real time as mining progresses, facilitating subsequent closed-loop optimization of the model.

[0097] Step 202: Construct a surrounding rock stability sensitivity evaluation index based on basic parameters and rock mass mechanics parameters.

[0098] In some embodiments, step 202 may include:

[0099] The product parameter of the coal seam thickness and the lithology of the roof and floor is linearly combined with the ratio parameter of the sine function of the coal mining depth and the inclination angle to obtain the value of the linear combination;

[0100] The linear combination value is combined with the first correction coefficient and the exponential decay of the geological structure complexity to obtain the sensitivity factor;

[0101] The sensitivity factor is corrected according to the second correction coefficient, the ratio parameter of the surrounding rock compressive strength to the surrounding rock tensile strength, and the logarithmic relationship of the elastic parameters to obtain the surrounding rock stability sensitivity evaluation index.

[0102] In some embodiments, the surrounding rock stability sensitivity evaluation index can be expressed as:

[0103]

[0104] Among them, RSI is the sensitivity evaluation index of surrounding rock stability, k1 and k2 are the first correction coefficient and the second correction coefficient respectively, h is the thickness of the coal seam, r is the lithology of the roof and floor, d is the depth, α is the inclination angle, f is the complexity of the geological structure, σ c is the compressive strength of surrounding rock, σ t is the tensile strength of the surrounding rock, E is the elastic modulus, and μ is the Poisson's ratio.

[0105] In some embodiments, a regression model can be established using on-site surrounding rock mechanics test data; parameter calibration is performed based on the regression model combined with historical working face stability monitoring data to obtain a first correction coefficient and a second correction coefficient.

[0106] In the specific implementation, the first part is the geometry-structure sensitivity factor This item expresses the sensitivity of structural parameters to the stability of surrounding rock. is the structural sensitivity ratio term, h is the thickness of the coal seam, the thicker the surrounding rock, the more stable it is (the larger the support space); r is the lithologic strength grade of the roof and floor (usually a quantitative assignment, such as sandstone = 1.0, shale = 0.6, etc.), the stronger the surrounding rock, the more stable it is; d is the burial depth, the deeper the depth, the greater the ground stress and the worse the stability; sinα is the coal seam inclination factor, the greater the inclination, the more severe the slip and disturbance during mining.

[0107] is a structural complexity adjustment term, f is the geological structural complexity, and represents a structural complexity index, typically calculated based on indicators such as fault density and joint development. The exponential function e is used to exponentially weaken the stability contribution of these structural parameters. When the structure is complex, the stability of the surrounding rock can be significantly reduced even in favorable geometric conditions. k1, based on regional experience or field calibration, is used to adjust the overall contribution of this component to the RSI.

[0108] The second part is the mechanical performance response Compression and tensile strength ratio Reflects the brittleness of the rock mass. The larger the ratio, the more "compressive-resistant but easily tensile-fractured" the rock mass is, and the more fragile the surrounding rock is. It is used to express the tendency of the surrounding rock to "burst" or "break" when disturbed. Deformation resistance symmetry E is the elastic modulus; a larger value indicates a stiffer rock mass. μ is the Poisson's ratio; a larger value indicates greater lateral strain and a weaker structure. A logarithmic function is used to normalize and smooth this ratio, representing the rock mass's "rigid" response. k² represents the degree to which this mechanical property modulates the overall RSI, and can also be obtained through engineering calibration.

[0109] It can be understood that a higher RSI indicates greater surrounding rock stability and greater mining safety; a lower RSI indicates greater surrounding rock fragility and sensitivity to mining and geological disturbances. This index is essentially a sensitivity trade-off model. By combining physical and structural factors, it reflects both the weakening effect of geological tectonic influences and the supporting role of rock mass mechanical properties in stability.

[0110] In summary, the RSI disclosed in the present invention can be used for working face design, support parameter adjustment, and mining sequence optimization; it is suitable for deployment in thin coal seam areas with complex geological conditions to improve the scientific nature of prediction and risk control; and it can be integrated into mine intelligent decision-making systems or geological engineering simulation platforms as an important input parameter.

[0111] Step 203: Calculate the dynamic coefficient of the mining impact range based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index.

[0112] In some embodiments, step 203 may include:

[0113] The sensitivity evaluation index of surrounding rock stability and the square parameter of coal seam thickness are integrated in the spatial domain to obtain the spatial disturbance potential energy term.

[0114] Combined with the time gradient parameters of the stope stress field, the ring integral operation is performed in the surface domain to determine the ring integral term of the time derivative of the stress disturbance;

[0115] The spatial disturbance potential energy term and the time derivative loop integral term are dynamically coupled by preset weights to obtain the dynamic coefficient of the mining influence range.

[0116] In some embodiments, the dynamic coefficient of the mining impact range can be expressed as:

[0117]

[0118] Among them, DIF is the dynamic coefficient of the mining influence range, β1 and β2 are the first weight and the second weight, p is the stope stress, t is time, x and s are the first spatial variable and the second spatial variable, respectively.

[0119] In the specific implementation, the spatial perturbation potential energy term β1∫(RSI·h 2 )dx,RSI·h 2 is the product of surrounding rock stability and thickness square, RSI represents the sensitivity of surrounding rock to disturbance; h 2 is the square of the coal seam thickness; thicker coal seams have a greater impact on the range of disturbances in the overlying rock. The product of the two represents the magnitude of the destabilizing potential energy caused by the disturbance on the surrounding rock at a specific spatial point. ∫dx represents the spatially distributed impact along the working face (e.g., the thrust line). In practical applications, this can be calculated piecewise (discretely), reflecting the cumulative effect of disturbances in different sections. β1 is the first weight, which adjusts its contribution to the overall DIF. This can be empirically modified using field monitoring data or numerical simulations.

[0120] Stress perturbation time derivative loop integral term ds is the stress change rate, representing the temporal trend of stress at a specific point in the mining area. Rapid stress changes indicate severe disturbances, which can easily lead to rock failure. It is often used to identify sources of risk such as mine tremors, rock bursts, and roof falls. ∮ds is the disturbance boundary ring integral, which represents the accumulation of the overall disturbance trend at the boundary of the disturbance area. Similar to the concept of "boundary response" in field theory, it can reflect the propagation trend and intensity of disturbances at spatial boundaries. β2 is the second weight, which adjusts the proportion of the stress dynamic term in the DIF. In areas with active tectonics and high rock burst risk, it is recommended to increase this weight.

[0121] β1∫(RSI·h 2 )dx is used for static disturbance assessment to describe the amplification effect of surrounding rock structural factors and spatial distribution on disturbance. Used for dynamic disturbance assessment, it reflects the intensity of stress disturbances and boundary feedback capabilities over time. A larger DIF indicates a wider mining impact, stronger disturbances, and higher support difficulty, roof collapse risk, and control costs.

[0122] This disclosure can be used to determine whether mining disturbances exceed the surrounding rock tolerance; optimize the matching of advancement speed and support schemes; serve as a key intermediary variable in MEF and FSI calculations, reflecting the transmission effect of disturbance intensity in system evaluation; and integrate with microseismic monitoring data and stress field simulation results to achieve real-time dynamic early warning and regulation. Thus, this disclosure balances static structural effects with dynamic disturbance feedback. It is adaptable to the disturbance coupling problem of thin coal seams in complex structural areas, supports model-based calculation and sensor-based measurement linkage evaluation, and can serve as a core disturbance control parameter in intelligent mining systems.

[0123] Step 204: Based on the dynamic coefficient of the mining impact range, a comprehensive evaluation function of mining efficiency is established.

[0124] In some embodiments, step 204 may include:

[0125] Obtaining a first ratio of a product parameter of a dynamic coefficient of a mining impact range and a propulsion speed to production;

[0126] The first ratio and the second ratio of the product of the cost and the recovery rate to the service time are weightedly combined to obtain a comprehensive evaluation function of mining efficiency.

[0127] In some embodiments, the comprehensive evaluation function of mining efficiency can be expressed as:

[0128]

[0129] Among them, MEF is the comprehensive evaluation function of mining efficiency, λ1 and λ2 are the first and second balance coefficients, v is the advancement speed, Q is the output, c is the cost, η is the recovery rate, and T is the service time.

[0130] In the specific implementation, the perturbation efficiency index term is It represents the disturbance advancement efficiency under unit output conditions; the smaller the value, the smaller the disturbance and the higher the advancement efficiency achieved under the premise of ensuring output, which represents a better mining strategy. DIF is the dynamic coefficient of the mining influence range, which indicates the degree of disturbance caused by the current working face mining activities on the surrounding rock; the larger the value, the more severe the disturbance and the higher the difficulty of control. v represents the excavation length of the working face per unit time; the faster the advancement, the higher the mining efficiency, but the risk may also be greater. Q is the output, which refers to the amount of raw coal produced per unit time; it is an important indicator for measuring actual benefits. λ1 is the first balance coefficient, which is used to adjust the proportion of the "disturbance-advancement" factor in the overall efficiency evaluation; if the mining area has complex geology or high requirements for surrounding rock stability, the weight can be appropriately increased.

[0131] The cost recovery efficiency term is Reflects the cost efficiency per unit of recovered value per unit of time; it helps identify the economic rationality of mining under cost control. c is cost, which includes direct costs (materials, labor, support, etc.) and indirect costs (maintenance, safety, etc.); it is one of the constraints on mining efficiency. η is the recovery rate, which represents the actual proportion of coal resources recovered; a high recovery rate indicates good resource utilization efficiency and high economic value. T is the service time, which refers to the total duration of operations from the start to the end of the working face; the shorter the time, the higher the efficiency, but safety and quality must also be guaranteed. λ2 is the second balance coefficient, which controls the contribution of the economic component to the overall MEF; if the company places greater emphasis on resource utilization and cost-effectiveness, this coefficient can be appropriately increased. A smaller MEF value represents higher efficiency.

[0132] In summary, this paper quantifies mining efficiency, transcending traditional empirical judgments by using parameter formulas to precisely describe the efficiency advantages and disadvantages of different options. It correlates disturbance and cost, using the MEF as a bridge between disturbance (DIF) and resource utilization (η), to construct a ternary evaluation model: safety, efficiency, and cost. This model guides optimization and regulation, serving as the objective function in optimization algorithms for option selection, speed control, and cost decomposition analysis. It supports integration with intelligent evaluation systems, and standardized parameters can be directly input into decision-making systems, enabling automated efficiency evaluation.

[0133] Step 205: Process the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range through a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face.

[0134] In some embodiments, step 205 may include:

[0135] The comprehensive evaluation function of mining efficiency is nonlinearly combined with the exponential decay term of the surrounding rock stability index to obtain the value of the nonlinear combination;

[0136] The value of the nonlinear combination is combined with the power function correction of the dynamic coefficient of the mining impact range to obtain the corrected value;

[0137] The corrected value is superimposed on the weighted score of each evaluation indicator to obtain the feasibility index.

[0138] In some embodiments, the feasibility index may be expressed as:

[0139]

[0140] Among them, FSI is the feasibility index, ω i is the weight of the i-th indicator, p i is the score of the ith indicator.

[0141] In the specific implementation, the product term [MEF·(1-e -RSI)], MEF is the mining efficiency evaluation function, which describes the efficiency performance of the current mining strategy; the smaller the value, the higher the efficiency; it is the basic evaluation quantity of the efficiency dimension.

[0142] (1-e -RSI ) is the surrounding rock response factor (stability function). The larger the RSI (more unstable the surrounding rock), the closer this term is to 1; the smaller the RSI (more stable the surrounding rock), the closer this term is to 0. Therefore, this function reflects the "regulatory effect" of the surrounding rock on mining efficiency: stable surrounding rock reduces the efficiency impact, while unstable surrounding rock amplifies the efficiency pressure. This product reflects the "true efficiency" factor affecting mining efficiency under the regulation of surrounding rock stability and can be considered the basic reliability expression of the solution.

[0143] Index term The DIF (Mining Disturbance Factor) controls the degree to which this product term is amplified or weakened. A large DIF (strong disturbance, high risk) results in a large exponent, which amplifies negative effects. A small DIF (weak disturbance, manageable risk) results in a small exponent, which preserves the efficiency advantage. Using π as a normalization factor keeps the exponent within a reasonable engineering scale. This exponential term structurally transforms the first product term into a power, creating a nonlinear response. In the case of severe disturbances, the exponent weakens the efficiency contribution; in the case of mild disturbances, the exponent retains the efficiency advantage.

[0144] ∑(ω i ·p i ) represents the comprehensive score of multiple evaluation indicators (such as safety, economy, recovery rate, support adaptability, etc.); ω i is the weight of the i-th indicator, p i It is the score of the i-th indicator (such as expert evaluation or model output score); it is an important part of achieving the fusion of subjective and objective evaluation, and improving the adaptability and practicality of the model.

[0145] In summary, the integrated indicator integration disclosed in this paper, FSI, effectively integrates efficiency, safety, disturbance, stability and scoring dimensions to form an integrated evaluation framework. Nonlinear response expression, through exponential and product coupling, depicts the nonlinear compound effect of disturbance and stability on efficiency. Supports subjective scoring adjustment, introduces (ω i ·p i ) item, supporting the injection of expert experience, multi-source perception systems, or AI-scored data. Standardized output with clear output value ranges facilitates standardized integration into actual coal mine scheduling decision-making systems. Multiple-scheme comparison is supported, and FSI values ​​can be used for horizontal comparison and optimal ranking of different coal mining plans.

[0146] Step 206: Evaluate the feasibility index according to the three-level threshold standard to obtain an evaluation result, and execute an optimization decision of the coal mining plan according to the evaluation result.

[0147] In specific implementation, if FSI ≥ 0.75, the efficiency is high, the disturbance is controllable, the surrounding rock is stable, the score is excellent, and the scheme is feasible; if 0.5 ≤ FSI < 0.75, the efficiency and stability are acceptable but there are problems, the parameters need to be adjusted, and the scheme needs to be optimized; if FSI < 0.5, the efficiency is low, the disturbance is strong, the stability is poor, the score is low, and the scheme needs to be redesigned.

[0148] Step 207: Based on the evaluation results, the model parameters corresponding to the coal mining plan are modified to obtain an updated model. One possible implementation method is to compare and analyze the monitoring data from the implementation phase with the prediction results to obtain analysis results; automatically modify the model parameters based on the analysis results to obtain an updated model; and update the evaluation index system based on the updated model to form a closed-loop optimization mechanism.

[0149] Specifically, during the coal mining process, key monitoring data such as advancement speed, surrounding rock response, stress changes, production, and disturbance range can be collected in real time; these data can be compared with the model prediction values ​​to identify deviations or trend anomalies; and analysis results can be obtained to evaluate the prediction accuracy and adaptability of the current model.

[0150] Based on the analysis results, the system automatically adjusts the key parameters in the model (such as lithology r in RSI, strength σ_c, weight β1 in disturbance DIF, etc.); the correction strategy adopts adaptive learning or optimization algorithms (such as least squares, Kalman filtering, etc.) based on the direction and amplitude of the deviation; and outputs a new updated model to make the model more compatible with the actual working conditions.

[0151] Finally, the updated model parameters can be substituted into the original formula system to recalculate core indicators such as RSI, DIF, MEF and FSI; achieve real-time re-judgment of scheme evaluation, enhance the sensitivity and accuracy of the evaluation system; and the evaluation indicators dynamically reflect the actual status on site.

[0152] Figure 3 This is a schematic diagram of the structure of a thin coal seam working face coal mining plan evaluation device provided by the present disclosure. Figure 3 As shown, a thin coal seam working face mining plan evaluation device 30 proposed in an embodiment of the present disclosure includes: an acquisition module 31, a construction module 32, a calculation module 33, an establishment module 34, a generation module 35, an evaluation module 36 and a correction module 37.

[0153] An acquisition module 31 is used to acquire basic parameters of a thin coal seam working face through a multi-source sensing device;

[0154] A construction module 32 is used to construct a surrounding rock stability sensitivity evaluation index based on basic parameters and rock mass mechanics parameters;

[0155] A calculation module 33 is used to calculate the dynamic coefficient of the mining impact range based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index;

[0156] Establishing module 34 for establishing a comprehensive evaluation function of mining efficiency based on the dynamic coefficient of the mining impact range;

[0157] A generation module 35 is used to process the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range through a nonlinear combination algorithm to generate a feasibility index of the coal mining plan for the thin coal seam working face;

[0158] An evaluation module 36 is used to evaluate the feasibility index according to the three-level threshold standard to obtain an evaluation result;

[0159] The correction module 37 is used to correct the model parameters corresponding to the coal mining plan according to the evaluation results to obtain an updated model.

[0160] It should be noted that for the specific embodiments and beneficial effects of the above modules 31-37, please refer to the above description of steps 201-206, which will not be repeated here.

[0161] Figure 4 Schematic diagram of an electronic device provided by an embodiment of the present disclosure. Figure 4 As shown, an embodiment of the present disclosure provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0162] Obtain basic parameters of thin coal seam working face through multi-source sensing device;

[0163] Based on basic parameters and rock mass mechanical parameters, a sensitivity evaluation index of surrounding rock stability is constructed;

[0164] Calculate the dynamic coefficient of mining impact range based on dynamic rock response mechanism and surrounding rock stability sensitivity evaluation index;

[0165] Based on the dynamic coefficient of mining impact range, a comprehensive evaluation function of mining efficiency is established;

[0166] The feasibility index of the mining scheme for thin coal seam working face is generated by processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range through nonlinear combination algorithm;

[0167] The feasibility index is evaluated according to the three-level threshold standard to obtain the evaluation results;

[0168] According to the evaluation results, the model parameters corresponding to the coal mining plan are modified to obtain an updated model.

[0169] Figure 5 Schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present disclosure. Figure 5 As shown, this embodiment provides a computer-readable storage medium 500 on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented:

[0170] Obtain basic parameters of thin coal seam working face through multi-source sensing device;

[0171] Based on basic parameters and rock mass mechanical parameters, a sensitivity evaluation index of surrounding rock stability is constructed;

[0172] Calculate the dynamic coefficient of mining impact range based on dynamic rock response mechanism and surrounding rock stability sensitivity evaluation index;

[0173] Based on the dynamic coefficient of mining impact range, a comprehensive evaluation function of mining efficiency is established;

[0174] The feasibility index of the mining scheme for thin coal seam working face is generated by processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range through nonlinear combination algorithm;

[0175] The feasibility index is evaluated according to the three-level threshold standard to obtain the evaluation results;

[0176] According to the evaluation results, the model parameters corresponding to the coal mining plan are modified to obtain an updated model.

[0177] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0178] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0179] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or boxes.

[0180] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system that is implemented in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0182] Although the preferred embodiments of the present disclosure have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present disclosure.

[0183] Obviously, those skilled in the art may make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is intended to include these modifications and variations.

Claims

1. A method for evaluating coal mining plans in a thin coal seam working face, characterized in that: include: Obtain basic parameters of thin coal seam working face through multi-source sensing device; Based on the basic parameters and rock mass mechanical parameters, construct a surrounding rock stability sensitivity evaluation index; Calculate the dynamic coefficient of the mining impact range based on the dynamic rock response mechanism and the surrounding rock stability sensitivity evaluation index; Based on the dynamic coefficient of the mining impact range, a comprehensive evaluation function of mining efficiency is established; Processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme of the thin coal seam working face; Evaluate the feasibility index according to the three-level threshold standard to obtain an evaluation result; The model parameters corresponding to the coal mining scheme are modified according to the evaluation results to obtain an updated model.

2. The method according to claim 1, characterized in that The basic parameters include: coal seam thickness, roof and floor lithology, depth, inclination and geological structure complexity; the rock mass mechanical parameters include: surrounding rock compressive strength and surrounding rock tensile strength; based on the basic parameters and rock mass mechanical parameters, a surrounding rock stability sensitivity evaluation index is constructed, including: linearly combining a parameter of a product of the coal seam thickness and the lithology of the roof and floor with a parameter of a ratio of a sine function of the mining depth and the inclination angle to obtain a value of the linear combination; The linear combination value is combined with a first correction coefficient and an exponential decay of the geological structure complexity to perform correction to obtain a sensitivity factor; Correcting the sensitivity factor according to a second correction coefficient, a ratio parameter of the surrounding rock compressive strength to the surrounding rock tensile strength, and a logarithmic relationship of elastic parameters to obtain a surrounding rock stability sensitivity evaluation index; The calculation formula of the surrounding rock stability sensitivity evaluation index is: Among them, RSI is the sensitivity evaluation index of surrounding rock stability, k1 and k2 are the first correction coefficient and the second correction coefficient respectively, h is the thickness of the coal seam, r is the lithology of the roof and floor, d is the depth, α is the inclination angle, f is the complexity of the geological structure, σ c is the compressive strength of surrounding rock, σ t is the tensile strength of the surrounding rock, E is the elastic modulus, and μ is the Poisson's ratio.

3. The method according to claim 2, characterized in that The method further comprises: A regression model was established using on-site surrounding rock mechanics test data; Parameter calibration is performed based on the regression model in combination with historical working face stability monitoring data to obtain the first correction coefficient and the second correction coefficient.

4. The method according to claim 1, wherein The calculation of the dynamic coefficient of the mining impact range based on the dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index includes: Integrating the surrounding rock stability sensitivity evaluation index and the square parameter of the coal seam thickness in the spatial domain to obtain a spatial disturbance potential energy term; Combined with the time gradient parameters of the stope stress field, the ring integral operation is performed in the surface domain to determine the ring integral term of the time derivative of the stress disturbance; Dynamically coupling the spatial disturbance potential energy term and the time derivative loop integral term through preset weights to obtain the dynamic coefficient of the mining influence range; The calculation formula of the dynamic coefficient of the mining impact range is: Among them, DIF is the dynamic coefficient of the mining influence range, β1 and β2 are the first weight and the second weight, p is the stope stress, t is time, x and s are the first spatial variable and the second spatial variable, respectively.

5. The method according to claim 1, characterized in that The mining efficiency comprehensive evaluation function is established based on the dynamic coefficient of the mining impact range, including: Obtaining a first ratio of a product parameter of the mining impact range dynamic coefficient and the advancing speed to the output; The first ratio and a second ratio of the product of the cost and the recovery rate to the service time are weightedly combined to obtain the comprehensive evaluation function of mining efficiency.

6. The method according to claim 1, characterized in that The step of processing the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face includes: Performing a nonlinear combination of the comprehensive evaluation function of mining efficiency and the exponential decay term of the surrounding rock stability index to obtain a value of the nonlinear combination; The value of the nonlinear combination is combined with the power function correction of the dynamic coefficient of the mining impact range to obtain a corrected value; The corrected value is superimposed on the weighted score of each evaluation indicator to obtain the feasibility index.

7. The method according to claim 1, characterized in that The step of modifying the model parameters corresponding to the coal mining scheme according to the evaluation result to obtain an updated model includes: Compare and analyze the monitoring data of the implementation phase with the forecast results to obtain the analysis results; The model parameters are automatically modified according to the analysis results to obtain an updated model.

8. A device for evaluating coal mining plans for a thin coal seam working face, characterized in that: include: An acquisition module is used to acquire basic parameters of the thin coal seam working face through a multi-source sensing device; A construction module for constructing a surrounding rock stability sensitivity evaluation index based on the basic parameters and rock mass mechanics parameters; A calculation module, configured to calculate a dynamic coefficient of a mining impact range based on a dynamic rock formation response mechanism and the surrounding rock stability sensitivity evaluation index; Establishing a module for establishing a comprehensive evaluation function of mining efficiency based on the dynamic coefficient of the mining impact range; A generating module, configured to process the comprehensive evaluation function of mining efficiency and the dynamic coefficient of mining influence range by a nonlinear combination algorithm to generate a feasibility index of the coal mining scheme for the thin coal seam working face; An evaluation module, configured to evaluate the feasibility index according to a three-level threshold standard to obtain an evaluation result; The correction module is used to correct the model parameters corresponding to the coal mining plan according to the evaluation results to obtain an updated model.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute instructions to implement each step in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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