A method for ecological maintenance in mining areas based on simulated surface subsidence

Abstract

The present invention relates to the technical field of mining subsidence control, and in particular to a method for ecological maintenance of mining areas based on simulated surface subsidence. The method comprises: determining potential subsidence sources based on the distribution information of tunnels in a mine map; determining the surface subsidence classification at a first time point and a second time point; the interval between the first time point and the second time point is greater than six months; using a simulated annealing algorithm to determine a first subsidence model set based on the potential subsidence sources that matches the subsidence classification at the first time point; determining a second subsidence model set based on the first subsidence model set, the simulated annealing algorithm, and the surface subsidence classification at the second time point; determining potential subsidence disturbance areas where the collapse type has changed within the first time period based on the second subsidence model set, and applying ecological restoration measures. This solves the problem that existing technologies cannot quickly and efficiently identify subsidence disturbance areas in mining areas.

Description

Technical Field

[0001] The present invention relates to the technical field of mining subsidence control, and in particular to a method for ecological maintenance of mining areas based on simulated surface subsidence. Background Art

[0002] Mining can cause significant damage to the surface, especially coal mining, which can cause geological disasters such as surface collapse and crack development, and have a significant impact on soil moisture content, porosity, nutrients, enzyme activity, root microorganisms, etc.

[0003] Therefore, ecological restoration measures are often required in coal mining areas. However, fully restoring a mining area consumes enormous resources, and some areas with less severe subsidence can recover on their own. Ecological restoration measures are only required in areas experiencing significant subsidence disturbance. The geological conditions vary widely across mining areas, making the identification and prediction of areas with significant subsidence disturbances a hurdle for targeted ecological restoration measures.

[0004] In response to the above problems, this application uses a method for ecological maintenance of mining areas based on simulated surface subsidence, which can quickly and efficiently simulate the generation of subsidence disturbance zones, thereby determining areas with greater subsidence disturbances and implementing targeted ecological restoration measures, which can greatly reduce restoration costs. Summary of the Invention

[0005] In order to solve the problem that the existing technology cannot quickly, low and efficiently identify subsidence disturbance areas in mining areas, at least one aspect and advantage of the present invention will be partially explained in the following description, or can be obvious from the description, or can be obtained by practicing the subject matter of the present disclosure.

[0006] According to a first aspect of the present invention, a method for ecological maintenance in a mining area based on simulated surface subsidence comprises:

[0007] Determine potential subsidence sources based on the distribution information of tunnels in the mine map;

[0008] determining a subsidence classification of a ground surface at a first time point and a second time point, wherein the interval between the first time point and the second time point is greater than 6 months;

[0009] a first set of subsidence models based on potential subsidence source determination and subsidence classification matching at a first time point using a simulated annealing algorithm;

[0010] determining a second subsidence model set based on the first subsidence model set, a simulated annealing algorithm, and the surface subsidence classification at the second time point;

[0011] identifying potential subsidence disturbance areas where the collapse type changed within the first time period based on the second set of subsidence models and applying ecological restoration measures;

[0012] The subsidence classification includes original surface, self-repairing area and subsidence disturbance area;

[0013] The first subsidence model set and the second subsidence model set include a collapse area of ​​a subsidence source.

[0014] According to one embodiment of the present invention, the subsidence sources are divided into first-class subsidence sources, second-class subsidence sources and third-class subsidence sources according to the probability of subsidence occurrence;

[0015] The first type of subsidence sources includes fault intersection areas and coal pillar failure areas;

[0016] The second type of subsidence sources include historical mined-out areas and potential critical stratum fracture areas;

[0017] The third category is the stable coal pillar area.

[0018] According to one embodiment of the present invention, the surface subsidence classification is based on the gridding of the mining area surface and then determining the carbon-phosphorus ratio, carbon-nitrogen ratio or nitrogen-phosphorus ratio of the surface.

[0019] According to one embodiment of the present invention, when determining the first subsidence model set using a simulated annealing algorithm, the subsidence at the first time point is classified as a number of roadways closest to the subsidence disturbance zone as the subsidence source of the collapse, and the surface subsidence amount and subsidence type at the time of complete subsidence are determined using a probability integral method;

[0020] Then, by changing the subsidence source of the collapse, the corresponding surface subsidence amount is obtained;

[0021] The objective function used by the simulated annealing algorithm is a first approximation, wherein the first approximation is a difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type;

[0022] The subsidence type is obtained based on at least the coal seam thickness and the subsidence coefficient.

[0023] According to one embodiment of the present invention, the process of determining the second subsidence model set includes:

[0024] Select a model from the first subsidence model set, obtain the corresponding collapsed area, and mark the corresponding roadway as collapsed;

[0025] Then, by changing the state of the collapse source to an uncollapsed subsidence source, collapse it and obtain the corresponding surface subsidence;

[0026] The objective function used by the simulated annealing algorithm is a second approximation, where the second approximation is the difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type;

[0027] The subsidence type is obtained based on at least the coal seam thickness and the subsidence coefficient.

[0028] According to one embodiment of the present invention, the subsidence models of the first subsidence model set and the second subsidence model set further include a collapse ratio of a subsidence source.

[0029] According to one embodiment of the present invention, the first similarity or the second similarity is a difference value of the proportion of collapsed areas of the same type.

[0030] According to one embodiment of the present invention, the potential subsidence disturbance area includes an area that has not collapsed at the second time point and whose collapse ratio of an adjacent area is lower than a first threshold.

[0031] According to one embodiment of the present invention, the second model set is sorted from low to high based on the collapse ratio in the second subsidence model set, and the model with the lowest collapse ratio is obtained as a benchmark for prediction.

[0032] According to one embodiment of the present invention, the object to which the ecological restoration measures are applied is the area where the collapse type is changed to a subsidence disturbance zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flow chart of a method for ecological maintenance in mining areas based on simulated surface subsidence is shown. DETAILED DESCRIPTION

[0034] The present disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the present disclosure, rather than to imply any limitation on the scope of the present disclosure.

[0035] As used herein, the term "including" and its variations are to be interpreted as open-ended terms meaning "including, but not limited to." The term "based on" is to be interpreted as "based, at least in part, on." The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment." The term "another embodiment" is to be interpreted as "at least one other embodiment." Terms such as "upper," "lower," "left," "right," "front," "back," "top," "bottom," "inner," "outer," "vertical," "horizontal," "transverse," and "longitudinal" indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings. These terms are primarily intended to better describe the present application and its embodiments and are not intended to limit the devices, elements, or components indicated to having a specific orientation, or to being constructed and operated in a specific orientation. Furthermore, some of the above terms may be used to indicate other meanings besides orientation or positional relationships. For example, the term "on" may, in certain circumstances, be used to indicate a dependency or connection relationship. Those skilled in the art will understand the specific meanings of these terms in this application based on the specific circumstances. Furthermore, the terms "installed," "disposed," "provided with," "connected," and "connected" are to be interpreted broadly. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection, an indirect connection through an intermediate medium, or an internal connection between two devices, elements, or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements, or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance or quantity of the indicated devices, elements, or components. Unless otherwise specified, "plurality" means two or more.

[0036] According to one embodiment of the present invention, a method for ecological maintenance in a mining area based on simulated surface subsidence includes:

[0037] Determine potential subsidence sources based on the distribution information of tunnels in the mine map;

[0038] determining a subsidence classification of a ground surface at a first time point and a second time point, wherein the interval between the first time point and the second time point is greater than 6 months;

[0039] A first set of subsidence models is determined based on potential subsidence sources and matched with subsidence classification at a first time point using a simulated annealing algorithm;

[0040] determining a second subsidence model set based on the first subsidence model set, a simulated annealing algorithm, and the surface subsidence classification at the second time point;

[0041] identifying potential subsidence disturbance areas where the collapse type changed within the first time period based on the second set of subsidence models and applying ecological restoration measures;

[0042] The subsidence classification includes original surface, self-repairing area and subsidence disturbance area;

[0043] The first subsidence model set and the second subsidence model set include a collapse area of ​​a subsidence source.

[0044] In this embodiment, a method for ecological maintenance of mining areas based on simulated surface subsidence is proposed. First, potential subsidence sources are determined based on the distribution information of tunnels in the mine map, and the surface subsidence classification at the first time point and the second time point is determined. Secondly, a simulated annealing algorithm is used with the potential subsidence sources to determine a first subsidence model set that matches the subsidence classification at the first time point. Thirdly, based on the first subsidence model set and the surface subsidence classification at the second time point, a simulated annealing algorithm is used to determine a second subsidence model set. Finally, based on the second subsidence model set, potential subsidence disturbance areas where the collapse type changed within the first time period are determined, and ecological restoration measures are applied to the corresponding areas.

[0045] Specifically, mine maps are crucial tools for mining. They provide insights into the mining area's geography, engineering layout, ventilation system, power system, emergency escape system, and other information. In the present invention, mine maps are used to obtain information about the distribution of tunnels within the mining area, and potential subsidence sources are identified based on this tunnel information. More specifically, potential subsidence sources are areas where collapse may occur.

[0046] Specifically, simulated annealing is a probability-based random search optimization algorithm inspired by the solid annealing process. In physics, annealing involves heating a solid to a sufficiently high temperature and then slowly cooling it to regularize the arrangement of atoms within the solid, thereby reducing the system's energy state. Similarly, in optimization problems, simulated annealing avoids falling into local optima by occasionally accepting suboptimal solutions in the hope of finding the global optimal solution.

[0047] Specifically, a simulated annealing algorithm is used to determine a first set of subsidence models that match the subsidence classification at the first time point based on potential subsidence sources. That is, the simulated annealing algorithm is used to predict potential subsidence sources, find subsidence sources among the potential sources that match the subsidence classification that actually occurred at the first time point, and form the first set of subsidence models.

[0048] Specifically, according to the subsidence classification information in the first subsidence model set, the collapsed area is obtained, the corresponding lanes are marked, and the simulated annealing algorithm is used to predict the subsidence area and subsidence classification at the second time point for the non-collapsed area at the second time point, which is matched with the actual subsidence classification at the second time point to form a second subsidence model set.

[0049] Specifically, the interval between the first time point and the second time point is greater than 6 months. The reason is that the type of partial ground subsidence will change within a 6-month cycle. If it is too long, more changes will occur; if it is too short, the changes may be small. For example, if the first time point is January, then the second time point is July; if the first time point is February, then the second time point is August. More specifically, according to different geological conditions, the interval between the first time point and the second time point can be flexibly selected to be 6 - 12 months, preferably 6 months.

[0050] Specifically, based on the second subsidence model set, determine the subsidence disturbance area where the collapse type changes within the first time period. That is, through the prediction of the collapse area in the second subsidence model set, determine the area where the collapse type will change within the first time period, so as to determine the corresponding potential subsidence disturbance area that will change, and use corresponding ecological restoration measures according to the subsidence situation.

[0051] Specifically, the first subsidence model set and the second subsidence model set include the collapse areas of the subsidence sources. More specifically, since the first subsidence model set contains multiple subsidence types, that is, the parameters at initialization are inconsistent, multiple solutions may be generated during calculation, which in turn affects that there may also be multiple possibilities for the second subsidence model.

[0052] Specifically, in the simulated annealing algorithm, the initial state starts from an initial solution, which can be randomly generated. Then introduce the temperature parameter as a control parameter. At high temperatures, the algorithm has a higher probability of accepting a worse solution; as the temperature gradually decreases, this probability also decreases. Finally, gradually reduce the temperature until the stop condition is met. Among them, the acceptance criterion is used as the standard for whether to accept the newly generated candidate solution. If the new solution is better than the current solution, it is directly accepted; if the new solution is worse, it is accepted with a certain probability, and this probability is related to the difference between the two and the current temperature. For example, define the objective function as y = f(x), calculate y0 and y1 respectively, where y1 is the new solution. Through calculation, if y1 is better than y0 (y1 < y0) and the difference is less than 0, the probability P of accepting the new solution is 1, that is, accept the new solution; if y1 is worse, the probability of accepting the new solution is , where, represents the difference in the objective function between the new solution and the current solution, and T represents the current "temperature" parameter. More specifically, the simulated annealing algorithm is a relatively mature algorithm. In optimization problems, the simulated annealing algorithm avoids falling into local optima by allowing occasional acceptance of worse solutions in order to find the global optimum solution.

[0053] Specifically, subsidence is categorized into original surface, self-healing zone, and subsidence disturbance zone. The original surface refers to areas that have not been mined. The self-healing zone is the area above the mining face where there is no significant height difference between the two sides of the crack after mining subsidence has stabilized. This area exhibits the characteristic of rapid self-healing closure.

[0054] Specifically, the subsidence disturbance zone refers to areas such as surface collapse and permanent cracks caused by mineral mining. This area is strongly affected by the disturbance of mineral mining and is difficult to repair automatically. It will cause continuous damage to the surface environment, thereby leading to changes in soil factors, soil enzyme activity and ecological stoichiometric ratios.

[0055] The present invention uses a method for ecological maintenance of mining areas based on simulated surface subsidence to predict the subsidence disturbance area in the mineral mining area, and applies corresponding ecological restoration measures to intervene in the ecological environment, so as to achieve the purpose of reducing ecological restoration costs and improving ecological restoration quality.

[0056] According to one embodiment of the present invention, the subsidence sources are divided into first-class subsidence sources, second-class subsidence sources and third-class subsidence sources according to the probability of subsidence occurrence;

[0057] The first type of subsidence sources includes fault intersection areas and coal pillar failure areas;

[0058] The second type of subsidence sources include historical mined-out areas and potential critical stratum fracture areas;

[0059] The third category is the stable coal pillar area.

[0060] In this embodiment, three subsidence sources are introduced according to the probability of subsidence occurrence.

[0061] Specifically, the first type of subsidence sources include fault intersection areas and coal pillar failure areas. More specifically, fault intersection areas refer to complex geological structures formed by the intersection and cutting of two or more faults. Local stress fields are usually formed at the intersection points of the faults, which may lead to higher stress concentrations and increase the possibility of subsidence in the area. Coal pillar failure areas refer to areas where, during underground coal mining, the coal pillars (the coal body used to support the roof and side walls) lose their bearing capacity due to stress redistribution, and are subsequently damaged or deformed. When coal pillars fail, serious accidents such as roof collapse and tunnel deformation may occur. Therefore, the first type of subsidence sources are areas with a high probability of subsidence, and these areas are most likely to form subsidence disturbance zones.

[0062] Specifically, the second type of subsidence sources include historical mining areas and potential key layer fracture areas. More specifically, historical mining areas refer to underground spaces where mining activities have been carried out in the past but mining has stopped now. These areas have undergone significant changes in the stratum structure due to long-term mining activities, which may cause a series of geological disasters and engineering problems, such as ground subsidence, collapse, and changes in groundwater levels. Potential key layer fracture areas refer to specific areas where the key layer may rupture or become unstable due to stress redistribution during underground mining. Key layers generally refer to those rock layers with high strength, large thickness and that play a supporting role in the stratum. When these key layers are damaged, serious geological disasters such as roof collapse and ground subsidence may occur. Therefore, the second type of subsidence sources are areas with a higher probability of subsidence, which may form self-recovery zones or subsidence disturbance zones.

[0063] Specifically, the third type of subsidence source is a stable coal pillar area. A stable coal pillar area is one that maintains its structural integrity and bearing capacity through reasonable design and layout during underground coal mining. Therefore, the third type of subsidence source is an area with a low probability of subsidence.

[0064] According to one embodiment of the present invention, the surface subsidence classification is based on the gridding of the mining area surface and then determining the carbon-phosphorus ratio, carbon-nitrogen ratio or nitrogen-phosphorus ratio of the surface.

[0065] In this embodiment, the surface subsidence classification is based on the determination of the carbon-phosphorus ratio, carbon-nitrogen ratio, or nitrogen-phosphorus ratio of the surface after the mining area surface is gridded. Since the carbon-phosphorus ratio, carbon-nitrogen ratio, or nitrogen-phosphorus ratio of the surface will change with the change of mining years, and the change trends of self-repair areas and subsidence disturbance areas will have certain differences, after the surface is gridded, the subsidence classification is determined by the carbon-phosphorus ratio, carbon-nitrogen ratio, or nitrogen-phosphorus ratio to make the classification result more accurate.

[0066] Specifically, grid division and regional calculation is a common calculation method, and the simulated annealing algorithm used in the present invention also performs calculations on each grid.

[0067] Specifically, the nitrogen-phosphorus ratio is the ratio of total nitrogen to total phosphorus, while the carbon-nitrogen ratio and carbon-phosphorus ratio are the ratios of organic matter to total nitrogen and total phosphorus, respectively. Soil total phosphorus can be determined according to the "Determination of Total Phosphorus in Soil - Alkali Fusion-Molybdenum Antimony Counterspectrophotometric Method: HJ632-2011"; soil total nitrogen can be determined according to the "Soil Quality - Determination of Total Nitrogen - Kjeldahl Method: HJ717-2014"; and soil organic matter can be determined using the potassium dichromate oxidation method described in the "Determination of Soil Organic Matter: NY / T1121.6-2006" standard.

[0068] Specifically, the surface carbon-phosphorus ratio (CPR) changes differently with mining. In the self-repairing area, the CPR increases with mining age, while in the subsidence-disturbed area, the CPR first increases and then decreases with reclamation age.

[0069] Specifically, as the mining years increase, the carbon-nitrogen ratio of the surface in the self-healing area is significantly higher than that in the subsidence disturbance area.

[0070] Specifically, the nitrogen-phosphorus ratio of the surface shows a trend of first increasing and then decreasing with the increase of mining years, and the nitrogen-phosphorus ratio in the subsidence disturbance area is significantly higher than that in the self-repairing area.

[0071] According to one embodiment of the present invention, when determining the first subsidence model set using a simulated annealing algorithm, the subsidence at the first time point is classified as a number of roadways closest to the subsidence disturbance zone as the subsidence source of the collapse, and the surface subsidence amount and subsidence type at the time of complete subsidence are determined using a probability integral method;

[0072] Then, by changing the subsidence source of the collapse, the corresponding surface subsidence amount is obtained;

[0073] The objective function used by the simulated annealing algorithm is a first approximation, wherein the first approximation is a difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type;

[0074] The subsidence type is obtained based on at least the coal seam thickness and the subsidence coefficient.

[0075] In this embodiment, when determining the first subsidence model set, a simulated annealing algorithm is used to identify the nearest multiple roadways classified as subsidence disturbance zones at the first time point as the collapse subsidence sources. A probability integral method is then used to calculate the surface subsidence amount and subsidence type at the time of complete subsidence. Finally, the corresponding surface subsidence amount is obtained by changing the collapse subsidence source.

[0076] Specifically, the objective function of the simulated annealing algorithm used in this embodiment is the first approximation. The first approximation is the difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type. In other words, the objective function is a measure of the difference between the calculated surface subsidence type and the actual surface subsidence type, which can be achieved using methods such as the sum of absolute differences or the sum of squared differences.

[0077] Specifically, the Probability Integral Transform (PIT) is an important method in statistics, primarily used to transform random variables into uniform distributions. This method is based on the properties of the cumulative distribution function (CDF), which states that any continuous random variable, when transformed through its own CDF, will yield a random variable with a uniform distribution on the interval (0, 1). Based on statistical theory and extensive observational data, this method assumes that rock failure and surface subsidence follow a certain probability distribution pattern. It is widely used to calculate surface movement and deformation caused by mining.

[0078] Specifically, when calculating the surface subsidence amount when completely subsided, a variety of fast calculation methods can be used. For example, in one embodiment, based on the consideration of the coal seam mining thickness, coal seam inclination and subsidence coefficient, the formula Calculate, where It is the amount of surface subsidence when complete subsidence occurs, m is the mining thickness of the coal seam, q is the subsidence coefficient, and A is the inclination of the coal seam. The subsidence coefficient is an empirical coefficient that measures the amount of surface subsidence per unit mining thickness. It reflects the degree of impact of mining on the surface under specific geological conditions. It is usually obtained through field measurements or historical data statistics. Its range can range from 0.1 to 0.9, depending on geological conditions, lithology and other factors.

[0079] In another embodiment, taking into account the mining thickness and mining depth, the formula Calculation is performed, where W is the amount of subsidence, k is the empirical coefficient, m is the mining thickness, and H is the mining depth. The empirical coefficient varies according to different geological conditions and mining methods. In other embodiments, finite element calculation can also be used.

[0080] Specifically, subsidence type is determined based on at least coal seam thickness and subsidence coefficient. Coal seam thickness refers to the actual thickness of the mined coal seam, which directly affects the scale and severity of surface subsidence. Generally speaking, the thicker the coal seam, the greater the potential for surface subsidence after mining.

[0081] Specifically, the method in this embodiment can use existing data to quickly estimate the collapse and subsidence of subsidence disturbance zones in different mining areas, and compare it with the actual collapse situation to obtain a first subsidence model that matches the subsidence classification at the first time point.

[0082] According to one embodiment of the present invention, the process of determining the second subsidence model set includes:

[0083] Select a model from the first subsidence model set, obtain the corresponding collapsed area, and mark the corresponding roadway as collapsed;

[0084] Then, by changing the state of the collapse source to an uncollapsed subsidence source, collapse it and obtain the corresponding surface subsidence;

[0085] The objective function used by the simulated annealing algorithm is a second approximation, where the second approximation is the difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type;

[0086] The subsidence type is obtained based on at least the coal seam thickness and the subsidence coefficient.

[0087] This embodiment describes the process of determining the second subsidence model set. First, a model from the first subsidence model set is selected and the corresponding subsidence area is obtained. Next, the roadway corresponding to the subsidence area is marked as collapsed. Finally, by changing the state of the subsidence source to a non-collapsed subsidence source, a simulated annealing algorithm is used to perform a subsidence simulation and obtain the corresponding subsidence amount.

[0088] Specifically, the models in the first subsidence model set are subsidence classifications that match the actual subsidence conditions at the first time point. Therefore, using a model in the first subsidence model, it is possible to know the areas in the mining area that have collapsed and mark the corresponding areas as collapsed.

[0089] Specifically, the system uses a simulated annealing algorithm to simulate the collapse of the collapsed area and obtain the corresponding surface subsidence. This method then classifies the surface subsidence in the corresponding area at the second time point, forming a second set of subsidence models. More specifically, the distribution of underground subsidence types in the second set of subsidence models is further optimized based on the data within the first subsidence model. This model reflects the potential for underground subsidence at the second time point, and serves as a basis for predicting potential subsequent subsidence types.

[0090] Specifically, the objective function of the simulated annealing algorithm is the second approximation, which is the difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type. More specifically, there are many ways to calculate the difference value. For example, in some embodiments, the subsidence type of each grid at the second time point is calculated, and the calculated subsidence type is compared with the actual subsidence type. If they are consistent, it is recorded as 1, otherwise it is recorded as 0. The calculated numbers are compared, and the resulting number is m, then the difference value is 1-m. For example, in other embodiments, the subsidence height of each grid at the second time point is calculated, and it is compared with the actual subsidence height at the second time point to obtain the ratio of the corresponding calculated height value to the actual height value. If the ratio is greater than 1, it is recorded as 1, otherwise it is recorded as 0. The ratio is recorded as the value corresponding to the grid, and the calculated numbers are compared. The resulting value is m, then 1-m is its difference value.

[0091] Specifically, the subsidence type is determined based on at least the coal seam thickness and the subsidence coefficient.

[0092] According to one embodiment of the present invention, the subsidence models of the first subsidence model set and the second subsidence model set further include a collapse ratio of a subsidence source.

[0093] In this example, the subsidence models of the first and second subsidence model sets also include the collapse ratio of the subsidence source. Specifically, in real-world scenarios, not all roadways beneath a disturbed subsidence zone will completely collapse; some may collapse within a certain area or at a certain height. For example, if a roadway collapses uniformly, a collapse ratio can be added to the calculation to ensure that the calculated surface subsidence is lower than the subsidence that would occur if the roadway were completely subsided.

[0094] According to one embodiment of the present invention, the first similarity or the second similarity is a difference value of the proportion of collapsed areas of the same type.

[0095] In this embodiment, the first approximation or the second approximation may also be a difference in the proportion of the same type of subsidence areas, that is, the difference between the proportion of the subsidence area to the mining area calculated based on the selected subsidence source and the actual proportion of the same type of subsidence areas to the mining area.

[0096] According to one embodiment of the present invention, a potential subsidence disturbance area includes an area that has not collapsed at the second time point and whose adjacent area collapse ratio is lower than a first threshold. According to one embodiment of the present invention, the second model set is sorted from low to high based on the collapse ratio in the second subsidence model set, and the model with the lowest collapse ratio is obtained as the basis for prediction. In this embodiment, a potential subsidence disturbance area also includes an area that has not collapsed at the second time point and whose adjacent area collapse ratio is lower than the first threshold.

[0097] Specifically, the collapse ratio refers to the proportion of collapsed areas among all collapse sources.

[0098] Specifically, in real-world scenarios, when a certain area within a mining region collapses, the adjacent areas often form relatively stable structures. Therefore, if a region that has not experienced subsidence at the second point in time has a relatively low level of subsidence in its adjacent areas, this region can be considered a potential subsidence disturbance area, meaning it may be prone to collapse.

[0099] Specifically, all models in the second subsidence model set are sorted in ascending order by collapse ratio. Models with higher collapse ratios are actually more stable than models with lower collapse ratios. Therefore, the model with the lowest collapse ratio is selected as the prediction benchmark. This can make the prediction of potential subsidence disturbance areas more reasonable.

[0100] According to one embodiment of the present invention, the object to which the ecological restoration measures are applied is the area where the collapse type is changed to a subsidence disturbance zone.

[0101] In this embodiment, the objects for applying ecological restoration measures are introduced. Specifically, the areas where the collapse type is changed to subsidence disturbance areas. More specifically, in actual mining scenarios, if the collapsed area is below a certain threshold, the ecological environment of the subsidence area can be self-repaired. For example, a 10-meter tunnel collapsed, but the surface only sank 1 meter to form a stable structure. At this time, there is no need to implement ecological restoration measures. These areas correspond to self-repair areas. When the subsidence exceeds a certain height, the surface ecosystem is severely damaged, and ecological restoration measures are required. For example, when the surface sinks more than 3 meters, the vegetation will be displaced, the light will be affected, and then the microbial system will be affected. The various elements in the soil will also be affected. It is difficult for the ecology to repair itself, and artificial intervention is required to implement ecological restoration measures. These areas correspond to subsidence disturbance areas. Therefore, when the collapse type of a certain area is changed to a subsidence disturbance area, the area needs to take ecological restoration measures.

[0102] The beneficial effect of the present invention is that: through the method of the present invention for ecological maintenance of mining areas based on simulated surface subsidence, the generation of subsidence disturbance zones in mining areas can be effectively simulated, thereby quickly distinguishing self-repairing zones and subsidence disturbance zones in mining areas, so that targeted ecological restoration measures can be carried out for subsidence disturbance zones, which not only protects the ecological environment of the mining area, but also greatly reduces the cost of restoration.

[0103] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0104] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0105] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0106] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of these modules may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.

[0107] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0108] If the functions are implemented as software modules and sold or used as standalone products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution itself, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal transmission / reception method according to various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0109] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention herein is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features having similar functions disclosed in this application.

[0110] It should be understood that the size of the serial numbers of the steps in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. The foregoing description of the implementation of the present disclosure has been given for the purpose of example and description. The foregoing description is not exhaustive and is not intended to limit the present disclosure to the exact form disclosed. Various variations and modifications may exist based on the above teachings, or various variations and modifications may be obtained from the practice of the present disclosure. These embodiments are selected and described in order to illustrate the principles of the present disclosure and its practical application, so that those skilled in the art can utilize the present disclosure in various embodiments and various modifications suitable for the specific purpose conceived.

Claims

1. A method for ecological maintenance of mining areas based on simulated surface subsidence, characterized in that: include: Determine potential subsidence sources based on the distribution information of tunnels in the mine map; determining a subsidence classification of the ground surface at a first time point and a second time point; The interval between the first time point and the second time point is greater than 6 months; a first set of subsidence models based on potential subsidence source determination and subsidence classification matching at a first time point using a simulated annealing algorithm; determining a second subsidence model set based on the first subsidence model set, a simulated annealing algorithm, and the surface subsidence classification at the second time point; identifying potential subsidence disturbance areas where the collapse type changed within the first time period based on the second set of subsidence models and applying ecological restoration measures; The subsidence classification includes original surface, self-repairing area and subsidence disturbance area; The first subsidence model set and the second subsidence model set include a subsidence area of ​​a subsidence source; When using the simulated annealing algorithm to determine the first subsidence model set, the subsidence at the first time point is classified into several roadways closest to the subsidence disturbance area as the subsidence source, and the probability integral method is used to calculate the surface subsidence amount and subsidence type when the subsidence is complete; Then, by changing the subsidence source of the collapse, the corresponding surface subsidence amount is obtained; The objective function used by the simulated annealing algorithm is a first approximation, wherein the first approximation is a difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type; The subsidence type is obtained based on at least the coal seam thickness and the subsidence coefficient; The process of determining the second subsidence model set includes: Select a model from the first subsidence model set, obtain the corresponding collapsed area, and mark the corresponding roadway as collapsed; Then, by changing the state of the collapse source to an uncollapsed subsidence source, collapse it and obtain the corresponding surface subsidence; The objective function used by the simulated annealing algorithm is a second approximation, where the second approximation is the difference between the surface subsidence type calculated based on the selected collapse source and the actual surface subsidence type; The subsidence type is obtained based on at least the coal seam thickness and the subsidence coefficient.

2. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 1, characterized in that: The subsidence sources are divided into the first type of subsidence source, the second type of subsidence source and the third type of subsidence source according to the probability of subsidence; The first type of subsidence sources includes fault intersection areas and coal pillar failure areas; The second type of subsidence sources include historical mined-out areas and potential critical stratum fracture areas; The third type of subsidence source is the stable coal pillar area.

3. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 1, characterized in that: The surface subsidence classification is based on the gridding of the mining area surface and the determination of the carbon-phosphorus ratio, carbon-nitrogen ratio or nitrogen-phosphorus ratio of the surface.

4. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 1, characterized in that: The subsidence models of the first subsidence model set and the second subsidence model set further include a collapse ratio of a subsidence source.

5. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 1, characterized in that: The first approximation or the second approximation is the difference in proportion of the same type of collapsed areas.

6. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 1, characterized in that: The potential subsidence disturbance area includes an area that has not collapsed at the second time point and whose collapse ratio of an adjacent area is lower than a first threshold.

7. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 6, characterized in that: The second model set is sorted from low to high based on the collapse ratio in the second subsidence model set, and the model with the lowest collapse ratio is obtained as a benchmark for prediction.

8. The method for ecological maintenance of mining areas based on simulated surface subsidence according to claim 1, characterized in that: The targets for applying ecological restoration measures are areas where the collapse type has changed to subsidence disturbance areas.

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