Mine geological disaster risk prediction method, system, equipment and medium

Abstract

The invention discloses a mine geological disaster risk prediction method, system and device and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a mine region, geological information and topographic information, dividing the mine region, geological information and topographic information into a plurality of sub-regions, obtaining a preset risk threshold, and obtaining a first time point and a second time point; acquiring first slip zone thickness data of the surface of the sub-region at a first time point, acquiring first rock stratum height data in the sub-region at the first time point, acquiring second slip zone thickness data of the surface of the sub-region at a second time point, and acquiring second rock stratum height data in the sub-region at the second time point; obtaining a geological risk index of the sub-region, obtaining a real-time risk threshold according to the geological risk index and a preset risk threshold, and obtaining a terrain risk index of the sub-region; and obtaining a prediction result according to the terrain risk index and the real-time risk threshold value of the sub-region. The method has the advantages of considering the correlation influence, improving the prediction accuracy, and being stable and reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method, system, equipment and medium for predicting the risk of geological disasters in mines. Background Art

[0002] Mine geological disasters are a potential safety hazard that cannot be ignored in the process of mining development. Their occurrence is often related to multiple factors such as the geological structure, terrain characteristics and human activities in the mining area. These disasters not only threaten the lives of mine workers, but may also cause serious damage to the surrounding environment and lead to huge economic losses. Therefore, accurately predicting the risk of mine geological disasters is of great significance to ensuring mine safety and surrounding environmental protection.

[0003] With the advancement of science and technology and the development of information technology, some risk prediction methods based on mathematical models and computer technology have gradually been applied to the field of mining geological hazards. However, most of these methods focus on a single geological structure or terrain feature, while ignoring the interaction and influence between the two. In fact, the risk of mining geological hazards is the result of the combined effect of two factors, and the analysis of a single factor is difficult to accurately reflect the full picture of the risk; in addition, the existing risk prediction methods often use fixed rules for judgment, ignoring the temporal and spatial variability of geological and terrain conditions. In actual applications, since the geological and terrain conditions in the mining area will change over time, this method will lead to deviations or misjudgments in the prediction results. Summary of the invention

[0004] In view of the defects in the prior art, the present invention provides a method, system, equipment and medium for predicting the risk of mining geological disasters.

[0005] A method for predicting the risk of geological disasters in a mine, comprising: obtaining a mine area, geological information corresponding to the mine area and terrain information corresponding to the mine area, dividing the mine area into a plurality of sub-areas according to different terrain information, obtaining a preset risk threshold corresponding to the sub-area according to the terrain information corresponding to the sub-area, and obtaining a first time point and a second time point at an interval of a preset time period according to the terrain information; obtaining first sliding belt thickness data on the surface of the sub-area at a first time point, obtaining first rock layer height data inside the sub-area at the first time point, obtaining second sliding belt thickness data on the surface of the sub-area at a second time point, and obtaining second rock layer height data inside the sub-area at the second time point; obtaining a geological risk index of the sub-area based on a geological calculation model, the first rock layer height data and the second rock layer height data, obtaining a real-time risk threshold based on the geological risk index and the preset risk threshold, and obtaining a terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data and the second sliding belt thickness data; obtaining a prediction result based on the terrain risk index of the sub-area and the real-time risk threshold.

[0006] Optionally, obtaining a real-time risk threshold according to the geological risk indicator and the preset risk threshold includes: obtaining a correction parameter according to the geological risk indicator; and obtaining a real-time risk threshold according to the correction parameter and the preset risk threshold.

[0007] Optionally, the correction parameter is obtained according to the geological risk index and expressed as: ;in, To correct the parameters, is the initial preset parameter, It is an indicator of geological risk.

[0008] Optionally, obtaining prediction results based on the terrain risk index of the sub-area and the real-time risk threshold includes: obtaining the number of sub-areas whose terrain risk index exceeds the real-time risk threshold and recording it as the target number; obtaining the risk ratio based on the target number and the total number of sub-areas; and obtaining the prediction results based on the risk ratio.

[0009] Optionally, the geological calculation model in obtaining the geological risk index of the sub-region based on the geological calculation model, the first rock formation height data and the second rock formation height data is expressed as: ;in, is the geological risk index of the ith sub-region, is the height data of the first rock layer in the ith sub-area, is the height data of the second rock layer in the ith sub-area, is the historical subsidence rate of the rock formation in the ith sub-region, For the first time point, The second time point.

[0010] Optionally, the terrain calculation model in obtaining the terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data and the second sliding belt thickness data is expressed as: );in, is the terrain risk index of the ith sub-region, is the thickness data of the first sliding belt, is the thickness data of the second sliding belt, For the first time point, The second time point.

[0011] A mine geological disaster risk prediction system is also provided, the system comprising: a first acquisition module, used to acquire a mine area, geological information corresponding to the mine area and terrain information corresponding to the mine area, and divide the mine area into multiple sub-areas according to different terrain information, and acquire a preset risk threshold corresponding to the sub-area according to the terrain information corresponding to the sub-area, and acquire a first time point and a second time point at an interval of a preset time period according to the terrain information; a second acquisition module, used to acquire first sliding belt thickness data on the surface of the sub-area at a first time point, and acquire first rock layer height data inside the sub-area at the first time point, and acquire second sliding belt thickness data on the surface of the sub-area at a second time point, and acquire second rock layer height data inside the sub-area at the second time point; a data processing module, used to acquire a geological risk index of the sub-area based on a geological calculation model, the first rock layer height data and the second rock layer height data, and acquire a real-time risk threshold based on the geological risk index and the preset risk threshold, and acquire a terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data and the second sliding belt thickness data; a prediction analysis module, used to acquire a prediction result based on the terrain risk index of the sub-area and the real-time risk threshold.

[0012] Optionally, the data processing module is also used to: obtain correction parameters according to geological risk indicators; and obtain real-time risk thresholds according to the correction parameters and preset risk thresholds.

[0013] An electronic device is also provided, comprising: a memory on which a computer program is stored; and a processor for executing the computer program in the memory to implement the above-mentioned method for predicting the risk of geological disasters in mines.

[0014] A non-temporary computer-readable storage medium is also provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned mining geological disaster risk prediction method is implemented.

[0015] The beneficial effects of the present invention are embodied in: In the entire mine geological disaster risk prediction method, by comprehensively acquiring the geological information and topographic information of the mining area and dividing the mining area into multiple sub-areas with relatively uniform terrain characteristics, risk prediction can be carried out more accurately for each sub-area, thereby improving the accuracy and pertinence of the prediction; further, the sliding zone thickness data on the surface of the sub-area and the rock layer height data inside the sub-area are obtained at two specific time points. By comparing the changes in these data, the temporal and spatial variability of geological and topographic conditions can be dynamically reflected, thus avoiding the prediction bias or misjudgment caused by traditional methods that ignore such variability; further, the geological calculation model and the terrain calculation model are used to process the rock layer height data and the terrain height data, respectively. The geological risk index and terrain risk index of the sub-area are calculated based on the sliding zone thickness data. These two indicators comprehensively consider the impact of geological and terrain factors on disaster risks, making the prediction results more comprehensive and reliable; further, the preset risk threshold is dynamically adjusted according to the geological risk index to obtain the real-time risk threshold, so that the risk judgment standard is more in line with the current geological risk situation, improving the timeliness and accuracy of the prediction; finally, by comparing the terrain risk index and the real-time risk threshold, it is possible to intuitively judge whether the sub-area is in a high-risk state, which provides a scientific basis for subsequent risk management and prevention measures, and helps to take targeted measures in a timely manner to reduce the risk of geological disasters and ensure the safety of the mining area. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0017] Figure 1 It is a schematic diagram of the steps of the method for predicting the risk of geological disasters in mines of the present invention; Figure 2 It is a schematic diagram of some steps of S3 in the method for predicting the risk of geological disasters in mines of the present invention; Figure 3 Schematic diagram of step S4 in the method for predicting the risk of geological disasters in mines of the present invention; Figure 4 The present invention is a block diagram of an electronic device according to an embodiment of the present invention.

[0018] Reference numerals: 700 - electronic device, 701 - processor, 702 - memory, 703 - multimedia component, 704 - I / O interface, 705 - communication component. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. In addition, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0022] like Figure 1 As shown, a method for predicting the risk of geological disasters in mines is provided, including: S1. Obtain a mining area, geological information corresponding to the mining area, and terrain information corresponding to the mining area, and divide the mining area into multiple sub-areas according to different terrain information, and obtain a preset risk threshold corresponding to the sub-area according to the terrain information corresponding to the sub-area, and obtain a first time point and a second time point separated by a preset time period according to the terrain information; S2, obtaining first sliding zone thickness data on the surface of the sub-region at a first time point, obtaining first rock formation height data inside the sub-region at the first time point, obtaining second sliding zone thickness data on the surface of the sub-region at a second time point, and obtaining second rock formation height data inside the sub-region at a second time point; S3, obtaining a geological risk index of the sub-area based on the geological calculation model, the first rock layer height data and the second rock layer height data, obtaining a real-time risk threshold value based on the geological risk index and the preset risk threshold value, and obtaining a terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data and the second sliding belt thickness data; S4. Obtain prediction results based on the terrain risk index and real-time risk threshold of the sub-area.

[0023] In this embodiment, it should be noted that, in S1, first of all, it is necessary to fully obtain relevant information of the mining area, including the geographical location, scope, and specific geological information and topographic information of the mining area. Geological information may cover the type, structure, thickness, and historical geological activity records of the rock layer; topographic information includes the slope, height, and geomorphic features of the mine, which helps to understand the external form of the mining area. In this way, the mining area is divided into multiple sub-areas according to the differences in topographic information. Each sub-area has relatively uniform topographic features, so that risk prediction can be performed more accurately for each sub-area. At the same time, according to the topographic information of each sub-area, a preset risk threshold is set for it; this preset risk threshold is determined based on the terrain characteristics and historical disaster data, and is used for subsequent risk assessment. In addition, two time points are determined based on the terrain information, namely the first time point and the second time point, and the two time points are separated by a preset time period. The selection of these two time points is determined based on the terrain characteristics and historical disaster data. Generally, for terrain features where historical disasters are prone to occur, only a shorter preset time period is required, and sufficient change information is captured on the premise of saving resources, so as to make accurate risk predictions.

[0024] For example, suppose there is a mining area with complex terrain, including steep slopes, flat valleys, and rugged ridges. After obtaining the geological and topographic information of this mining area, it may be divided into three sub-areas: the slope area, the valley area, and the ridge area. For the slope area, according to historical data, due to the proneness of geological disasters, a relatively low preset risk threshold will be set, and at the same time, the beginning and end of two weeks may be selected as the first time point and the second time point. For the valley area, according to historical data, geological disasters are not prone to occur, so a relatively high preset risk threshold will be set, and at the same time, the beginning and end of a month may be selected as the first time point and the second time point. For the ridge area, according to historical data, the probability of geological disasters is medium, so a medium preset risk threshold will be set, and at the same time, the beginning and end of three weeks may be selected as the first time point and the second time point.

[0025] In S2, it is necessary to obtain the sliding belt thickness data of each sub-surface of the mining area and the rock layer height data inside the sub-area at two specific time points, namely the first time point and the second time point. The sliding belt thickness data refers to the thickness of the surface sliding belt (i.e. the surface of the potential sliding surface), which is an important indicator for evaluating the stability of the terrain. By measuring the first sliding belt thickness data and the second sliding belt thickness data at the first time point and the second time point, the change in the sliding belt thickness can be observed, and then it can be judged whether the terrain tends to be unstable. The rock layer height data reflects the change in the vertical position of the rock layer, which is a direct reflection of the geological activity. By comparing the first rock layer height data and the second rock layer height data at two time points, the settlement or uplift rate of the rock layer can be calculated, which is an important basis for evaluating geological risks. In specific operations, professional measurement equipment and technologies, such as radar detection, laser scanning or GPS monitoring, will be used to ensure the accuracy and reliability of the data. These data will provide a basis for the calculation of subsequent geological risk indicators and terrain risk indicators.

[0026] For example, suppose that the data of sliding belt thickness and rock layer height are obtained in a certain sub-area. At the first time point, the sliding belt thickness at a certain place in the sub-area is measured to be 20cm, and the height of a certain rock layer is 100m. After a preset period of time (such as two weeks), at the second time point, the sliding belt thickness and rock layer height are measured again, and it is found that the sliding belt thickness has increased to 25cm and the rock layer height has decreased to 99.5 meters. This means that during this period of time, the sliding belt has significantly thickened and the rock layer has subsided. These data changes will serve as an important basis for the subsequent calculation of geological risk indicators and terrain risk indicators, helping to more accurately assess the geological disaster risks in hillside areas.

[0027] In S3, first, the geological calculation model needs to be used to process the rock layer height data inside the sub-area obtained at the first time point and the second time point. Specifically, by comparing the rock layer height data at two time points, such as the first rock layer height data at the first time point and the second rock layer height data at the second time point, the settlement or uplift rate of the rock layer can be calculated. This rate is an important indicator for evaluating geological activity and can reflect the stability of the rock layer in the vertical direction. At the same time, the geological risk index of the sub-area is calculated based on these rock layer height data and combined with the geological calculation model. This indicator is used to quantify the geological disaster risk of the sub-area. Next, a real-time risk threshold is obtained based on the calculated geological risk index and the preset risk threshold. This real-time risk threshold is dynamically adjusted according to the current geological risk situation and can more accurately reflect the actual risk level of the sub-area. In addition, the terrain calculation model needs to be used to process the sliding belt thickness data on the surface of the sub-area obtained at the first time point and the second time point. By comparing the sliding belt thickness data at two time points, such as the first sliding belt thickness data at the first time point and the second sliding belt thickness data at the second time point, the change in the sliding belt thickness can be observed, and then it can be judged whether the terrain tends to be unstable. Combined with the terrain calculation model, the terrain risk index of the sub-region can be calculated. This index is used to quantify the disaster risk caused by terrain factors in the sub-region.

[0028] For example, suppose that a geological disaster risk prediction is conducted in a hillside sub-region. At the first time point, the rock layer height at a certain location in the sub-region was measured to be 120 meters, and the sliding zone thickness was 30 centimeters. After a preset time period of two weeks, at the second time point, the rock layer height and sliding zone thickness were measured again, and it was found that the rock layer height dropped to 119.6 meters, and the sliding zone thickness increased to 35 centimeters. This means that during this period of time, the rock layer subsided and the sliding zone thickened. Next, the geological calculation model is used to calculate the geological risk index of the sub-region in combination with the change data of the rock layer height. At the same time, a real-time risk threshold is dynamically adjusted based on the geological risk index and the preset risk threshold. In addition, the terrain calculation model is used to calculate the terrain risk index of the sub-region in combination with the change data of the sliding zone thickness. Finally, the terrain risk index is compared with the real-time risk threshold to assess the geological disaster risk of the sub-region.

[0029] In S4, first, the terrain risk index calculated for each sub-region needs to be analyzed one by one; the terrain risk index is based on the terrain calculation model, combined with the change in the thickness of the sliding belt at two time points (the first time point and the second time point), and it reflects the disaster risk that may be caused by terrain factors (such as thickening of the sliding belt, slope changes, etc.) in the sub-region. Next, the terrain risk index of each sub-region is compared with its corresponding real-time risk threshold. The real-time risk threshold is dynamically adjusted according to the geological risk index. It takes into account the changes in geological activity and can more accurately reflect the actual risk level of the sub-region at the current time point. By comparing the terrain risk index and the real-time risk threshold, it can be determined whether the sub-region is in a high-risk state.

[0030] For example, suppose that geological hazard risk prediction is carried out in three sub-areas (hillside area, valley area and ridge area) of a mining area. In step S3, the terrain risk index and real-time risk threshold of each sub-area have been calculated. Now, in step S4, these data are compared. Taking the hillside area as an example, if its terrain risk index exceeds the real-time risk threshold, then it can be considered that the sub-area is in a high-risk state at the current time point, and geological disasters such as landslides may occur. On the contrary, if the terrain risk index of the valley area is lower than its real-time risk threshold, then it can be considered that the risk of the sub-area is relatively low, and the possibility of geological disasters is small. Through such comparison and analysis, we can have a comprehensive understanding of the overall geological hazard risk of the mining area, and provide a scientific basis for subsequent risk management and prevention and control measures.

[0031] In summary, in the entire mine geological disaster risk prediction method, by comprehensively acquiring the geological information and topographic information of the mining area and dividing the mining area into multiple sub-areas with relatively uniform terrain characteristics, risk prediction can be carried out more accurately for each sub-area, thereby improving the accuracy and pertinence of the prediction; further, the sliding zone thickness data on the surface of the sub-area and the rock layer height data inside the sub-area are obtained at two specific time points. By comparing the changes in these data, the temporal and spatial variability of geological and topographic conditions can be dynamically reflected, thus avoiding the prediction bias or misjudgment caused by traditional methods due to ignoring such variability; further, the geological calculation model and the terrain calculation model are used to process the rock layer height respectively. The geological risk index and terrain risk index of the sub-area are calculated based on the data and the sliding zone thickness data. These two indicators comprehensively consider the impact of geological and topographic factors on disaster risks, making the prediction results more comprehensive and reliable; further, the preset risk threshold is dynamically adjusted according to the geological risk index to obtain the real-time risk threshold, so that the risk judgment standard is more in line with the current geological risk situation, improving the timeliness and accuracy of the prediction; finally, by comparing the terrain risk index and the real-time risk threshold, it is possible to intuitively judge whether the sub-area is in a high-risk state, which provides a scientific basis for subsequent risk management and prevention measures, and helps to take targeted measures in a timely manner to reduce the risk of geological disasters and ensure the safety of the mining area.

[0032] like Figure 2 As shown, in one embodiment, obtaining the real-time risk threshold according to the geological risk index and the preset risk threshold in S3 includes: S31. Obtaining correction parameters according to geological risk indicators; S32. Obtain a real-time risk threshold according to the correction parameter and the preset risk threshold.

[0033] In this embodiment, it should be noted that in S31, the geological risk index is calculated by combining the rock layer height data changes at two time points (the first time point and the second time point) through a geological calculation model, which quantifies the activity of the geological activities in the sub-region and the potential geological disaster risks. The acquisition of the correction parameter is based on this geological risk index, and the geological risk index is converted into a value that can adjust the preset risk threshold through a certain algorithm or mapping relationship. This correction parameter reflects the degree of deviation of the risk level of the sub-region relative to the preset conditions under the current geological conditions. For example, if the geological risk indicator indicates that the rock layer settlement rate in the sub-region is faster, indicating that the geological activities in the region are more active, then the correction parameter may be increased accordingly to reflect this increased risk level. The specific calculation method of the correction parameter may rely on empirical formulas, statistical analysis or machine learning models, which determine the relationship between the correction parameter and the geological risk index based on historical data and geological characteristics.

[0034] In S32, the process of obtaining the real-time risk threshold according to the correction parameter and the preset risk threshold is the key to dynamically adjusting the risk judgment standard. The preset risk threshold is determined based on the terrain characteristics and historical disaster data of the sub-region, and is used to preliminarily assess the risk of geological disasters. However, due to the spatiotemporal variability of geological conditions, this preset value may not accurately reflect the current risk level. Therefore, it is necessary to adjust the preset risk threshold through the correction parameter to obtain the real-time risk threshold. Specifically, the correction parameter may act on the preset risk threshold in the form of a multiplier or addend, thereby raising or lowering the threshold for risk judgment. For example, if the correction parameter is less than 1, the real-time risk threshold will be reduced, and the lower the correction parameter, the more sensitive the system is to geological disaster risks. Through such dynamic adjustment, the real-time risk threshold can more accurately reflect the actual risk level of the sub-region at the current time point, providing a scientific basis for subsequent risk prediction and decision-making. For example, assuming that the preset risk threshold of a sub-region is 10, and the correction parameter calculated based on the geological risk index is 0.8, then the real-time risk threshold will be 8 (i.e., 10 multiplied by 0.8). This means that when the terrain risk index of the sub-area exceeds 8, it will be considered to be in a high-risk state, thereby triggering corresponding risk management and prevention measures.

[0035] In one embodiment, the correction parameter obtained according to the geological risk index in S31 is expressed as: ;in, To correct the parameters, is the initial preset parameter, It is an indicator of geological risk.

[0036] In this embodiment, it should be noted that: It is a parameter used to adjust the preset risk threshold, which determines the degree to which the real-time risk threshold is reduced relative to the preset risk threshold. It is the initial preset parameter, which is a constant set based on historical data and experience and is used to control the correction parameter The baseline value.

[0037] The selection of the method should take into account the general characteristics of geological conditions and the distribution of historical disaster data. The value of is usually greater than or equal to 1, and its size affects the correction parameter The overall range of The value means that under the same geological risk index, the correction parameter will be relatively large, which may result in a higher real-time risk threshold and make the system less sensitive to risk changes.

[0038] is an exponential decay term, It is an indicator of geological risk. The use of geological risk indicators is due to The impact on risk level is nonlinear and diminishing. As the risk increases, geological activities become more active, but the rate of risk increase gradually slows down, which is consistent with the impact of actual geological activities on risks. When smaller, Close to 1, which means the geological risk is low, and the parameters are corrected Mainly by Decision. When increasing, gradually decreases, resulting in the correction parameter This reflects that as the geological risk increases, the system should become more sensitive, that is, the real-time risk threshold should be reduced accordingly.

[0039] It should also be noted that, further, the correction parameter is multiplied by the preset risk threshold and the real-time risk threshold is calculated.

[0040] like Figure 3 As shown, in one embodiment, obtaining the prediction result according to the terrain risk index and the real-time risk threshold of the sub-area in S4 includes: S41, obtaining the number of sub-areas whose terrain risk index exceeds the real-time risk threshold and recording it as the target number; S42. Obtain the risk ratio based on the number of targets and the total number of sub-areas; S43. Obtain prediction results based on risk ratio.

[0041] In this embodiment, it should be noted that in S41, the terrain risk index of each sub-area needs to be compared with its real-time risk threshold one by one to identify those sub-areas whose terrain risk index exceeds the real-time risk threshold. Due to changes in terrain factors (such as significant thickening of the sliding belt, intensified slope changes, etc.), the disaster risks of these sub-areas have increased to a level that requires attention. By comparison, the number of sub-areas whose terrain risk index exceeds the real-time risk threshold is counted, and this number is defined as the "target number". This target number directly reflects how many sub-areas in the mining area are in a high geological disaster risk state at the current time point. For example, assuming that the mining area is divided into 10 sub-areas, after comparison, it is found that the terrain risk indicators of 3 of the sub-areas exceed their respective real-time risk thresholds, then these 3 sub-areas are counted into the target number, that is, the target number is 3.

[0042] In S42, after obtaining the target number, the risk ratio needs to be further calculated to quantify the geological hazard risk level of the entire mining area. The risk ratio is obtained by dividing the target number by the total number of sub-areas. This ratio indicator can intuitively reflect how many proportions of sub-areas are in a high-risk state at the current point in time. The higher the risk ratio, the greater the overall geological hazard risk in the mining area. Continuing with the above example, the total number of sub-areas is 10 and the target number is 3, then the risk ratio is 30%. This means that at the current point in time, 30% of the sub-areas in the mining area are in a high geological hazard risk state.

[0043] In S43, finally, the prediction result is obtained according to the risk ratio. The prediction result is an overall assessment of the geological disaster risk status in the mining area, which may include risk level, risk trend, and recommended risk management measures. The risk ratio is one of the important bases for determining the prediction result. Generally speaking, the higher the risk ratio, the higher the risk level given in the prediction result, and the stricter the recommended risk management measures. Taking the previous example, if the risk ratio is 30%, the prediction result may indicate that there is a medium to high risk of geological disasters in the mining area, and it is recommended to strengthen monitoring and early warning, and take necessary prevention and control measures for high-risk sub-areas to reduce the possibility and impact of geological disasters.

[0044] In one embodiment, the geological calculation model in obtaining the geological risk index of the sub-region based on the geological calculation model, the first rock formation height data and the second rock formation height data in S3 is expressed as: ;in, is the geological risk index of the ith sub-region, is the height data of the first rock layer in the ith sub-area, is the height data of the second rock layer in the ith sub-area, is the historical subsidence rate of the rock formation in the ith sub-region, For the first time point, The second time point.

[0045] In this embodiment, it should be noted that the absolute value operation The change in rock layer height between two points in time is calculated, where the absolute value ensures that the change is positive regardless of whether the rock layer is sinking or rising; this accurately reflects the level of geological activity by capturing the actual change in rock layer height, regardless of direction.

[0046] As a normalization factor, the change in rock layer height is normalized by the product of the historical subsidence rate and the time period; The value represents the height change of the rock layer within a preset time period under the historical settlement rate; different sub-areas may have different historical settlement rates. Standardization makes the geological risk indicators between different sub-areas comparable. At the same time, considering the time period ensures that the total historical change is reflected.

[0047] The goal is to ensure that the indicator reflects the rate of change per unit time, that is, to obtain the rate of change over time, so that the geological risk indicator can eliminate the influence of time and accurately reflect the amount of change.

[0048] It takes the logarithm of the standardized rate of change and compresses the data range in a nonlinear way, making the geological risk indicators less sensitive to extreme values ​​while maintaining sensitivity to small changes, which is consistent with the actual characteristics of geological activities, that is, small changes may indicate potential risks, while extreme changes may indicate that the critical point for disaster occurrence is approaching.

[0049] Suppose there is a sub-area with the following data: =120 meters (the height of the rock layer at the first time point), =119.5 meters (height of the rock layer at the second time point), = 0.05 m / month (historical sedimentation rate), =0 (assumed to be the starting time point), =0.5 months (two weeks later).

[0050] After inputting, we get That is to say, through the geological calculation model, this change is converted into a geological risk index (about 3.7136), which reflects the degree of geological activity and potential risks in the sub-region at the current time point. This index can be used for subsequent risk assessment and decision-making, helping to identify high-risk areas and take corresponding prevention and control measures.

[0051] In one embodiment, the terrain calculation model in obtaining the terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data and the second sliding belt thickness data in S3 is expressed as: );in, is the terrain risk index of the ith sub-region, is the thickness data of the first sliding belt, is the thickness data of the second sliding belt, For the first time point, The second time point.

[0052] In this embodiment, it should be noted that the absolute value operation It calculates the change in thickness of the sliding zone between two points in time; the absolute value ensures that the change is positive regardless of whether the sliding zone is thickening or thinning; therefore, this helps to accurately reflect the magnitude of topographic change, regardless of the direction of change. The change in the thickness of the sliding belt is standardized to the rate of change per unit time (such as daily, weekly or monthly); this helps to compare the rate of change in different time periods, making the risk indicators comparable in time; through standardization, the impact of different time intervals on the risk indicators can be eliminated. It compresses the data range in a nonlinear way and is not sensitive to small changes but relatively sensitive to extreme changes. This is consistent with the actual characteristics of terrain activities, that is, small changes may indicate no risk, while extreme changes can easily cause a significant increase in risk.

[0053] Assume there is a sub-area whose sliding belt thickness data is as follows: = 20 cm (thickness of the sliding zone at the first time point). = 25 cm (thickness of the sliding zone at the second time point). =0 week (assumed to be the starting time point). = 2 weeks (two weeks later). Substituting these data into the terrain calculation model: Calculate the change in the thickness of the sliding zone and get exp(2.5)≈12.1825. This indicator reflects the terrain change rate and potential risk of the sub-region at the current time point, and can be used for subsequent risk assessment and decision-making.

[0054] A mine geological disaster risk prediction system is also provided, the system comprising: A first acquisition module is used to acquire a mining area, geological information corresponding to the mining area, and terrain information corresponding to the mining area, and divide the mining area into multiple sub-areas according to different terrain information, and acquire a preset risk threshold corresponding to the sub-area according to the terrain information corresponding to the sub-area, and acquire a first time point and a second time point separated by a preset time period according to the terrain information; A second acquisition module is used to acquire first sliding zone thickness data on the surface of the sub-region at a first time point, acquire first rock layer height data inside the sub-region at the first time point, acquire second sliding zone thickness data on the surface of the sub-region at a second time point, and acquire second rock layer height data inside the sub-region at the second time point; A data processing module, for obtaining a geological risk index of a sub-area based on a geological calculation model, the first rock layer height data, and the second rock layer height data, and obtaining a real-time risk threshold value based on the geological risk index and a preset risk threshold value, and obtaining a terrain risk index of the sub-area based on a terrain calculation model, the first sliding belt thickness data, and the second sliding belt thickness data; The prediction analysis module is used to obtain prediction results based on the terrain risk indicators and real-time risk thresholds of the sub-areas.

[0055] In one embodiment, the data processing module is further used to: obtain correction parameters according to geological risk indicators; and obtain real-time risk thresholds according to the correction parameters and preset risk thresholds.

[0056] In one embodiment, the prediction and analysis module is also used to: obtain the number of sub-areas whose terrain risk indicators exceed the real-time risk threshold and record it as the target number; obtain the risk ratio based on the target number and the total number of sub-areas; and obtain the prediction result based on the risk ratio.

[0057] In this embodiment, it should be noted that regarding the above-mentioned mining geological disaster risk prediction system, the specific method of performing operations therein has been described in detail in the implementation of the mining geological disaster risk prediction method, and will not be elaborated here.

[0058] Figure 4 is a block diagram of an electronic device for a method for predicting the risk of geological disasters in a mine according to an exemplary embodiment. Figure 4 As shown, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an I / O interface 704, and a communication component 705.

[0059] The processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned method for predicting the risk of mining geological disasters. The memory 702 is used to store various types of data to support the operation of the electronic device 700, which may include instructions for any application or method used to operate on the electronic device 700, and application-related data, such as contact data, messages sent and received, pictures, audio, video, etc. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 703 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 702 or sent through the communication component 705. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules, and the above-mentioned other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 705 may include: Wi-Fi module, Bluetooth module, NFC module, etc.

[0060] In an exemplary embodiment, the electronic device 700 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned mine geological disaster risk prediction method.

[0061] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned method for predicting the risk of mining geological hazards are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 702 including program instructions, and the above-mentioned program instructions can be executed by the processor 701 of the electronic device 700 to complete the above-mentioned method for predicting the risk of mining geological hazards.

[0062] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the above-mentioned mine geological disaster risk prediction method when executed by the programmable device.

[0063] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0064] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0065] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for predicting the risk of geological disasters in mines, characterized in that: include: Obtaining a mining area, geological information corresponding to the mining area, and terrain information corresponding to the mining area, dividing the mining area into a plurality of sub-areas according to different terrain information, obtaining a preset risk threshold corresponding to the sub-area according to the terrain information corresponding to the sub-area, and obtaining a first time point and a second time point separated by a preset time period according to the terrain information; Acquire first sliding zone thickness data on the surface of the sub-region at a first time point, acquire first rock formation height data inside the sub-region at the first time point, acquire second sliding zone thickness data on the surface of the sub-region at a second time point, and acquire second rock formation height data inside the sub-region at a second time point; Obtaining a geological risk index of the sub-area based on the geological calculation model, the first rock layer height data, and the second rock layer height data, and obtaining a real-time risk threshold value based on the geological risk index and the preset risk threshold value, and obtaining a terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data, and the second sliding belt thickness data; Obtain prediction results based on the terrain risk index and real-time risk threshold of the sub-area.

2. The method for predicting the risk of geological disasters in mines according to claim 1, characterized in that: The obtaining of the real-time risk threshold according to the geological risk index and the preset risk threshold comprises: Obtain correction parameters based on geological risk indicators; Get the real-time risk threshold based on the modified parameters and the preset risk threshold.

3. The method for predicting the risk of mining geological disasters according to claim 2, characterized in that: The correction parameters obtained according to the geological risk index are expressed as: ;in, To correct the parameters, is the initial preset parameter, It is an indicator of geological risk.

4. The method for predicting the risk of mining geological disasters according to claim 1, characterized in that: The obtaining of prediction results according to the terrain risk index and the real-time risk threshold of the sub-region includes: The number of sub-areas whose terrain risk index exceeds the real-time risk threshold is obtained and recorded as the target number; Get the risk percentage based on the number of targets and the total number of sub-areas; Get prediction results based on risk ratio.

5. The method for predicting the risk of mining geological disasters according to claim 1, characterized in that: The geological calculation model in obtaining the geological risk index of the sub-region based on the geological calculation model, the first rock layer height data and the second rock layer height data is expressed as: ;in, is the geological risk index of the ith sub-region, is the height data of the first rock layer in the ith sub-area, is the height data of the second rock layer in the ith sub-area, is the historical subsidence rate of the rock formation in the ith sub-region, For the first time point, The second time point.

6. The method for predicting the risk of geological disasters in mines according to claim 1, characterized in that: The terrain calculation model in obtaining the terrain risk index of the sub-area based on the terrain calculation model, the first sliding belt thickness data and the second sliding belt thickness data is expressed as: );in, is the terrain risk index of the ith sub-region, is the first sliding belt thickness data, is the thickness data of the second sliding belt, For the first time point, The second time point.

7. A mine geological disaster risk prediction system, characterized in that: The system comprises: A first acquisition module is used to acquire a mining area, geological information corresponding to the mining area, and terrain information corresponding to the mining area, and divide the mining area into multiple sub-areas according to different terrain information, and acquire a preset risk threshold corresponding to the sub-area according to the terrain information corresponding to the sub-area, and acquire a first time point and a second time point separated by a preset time period according to the terrain information; A second acquisition module is used to acquire first sliding zone thickness data on the surface of the sub-region at a first time point, acquire first rock layer height data inside the sub-region at the first time point, acquire second sliding zone thickness data on the surface of the sub-region at a second time point, and acquire second rock layer height data inside the sub-region at the second time point; A data processing module, for obtaining a geological risk index of a sub-area based on a geological calculation model, the first rock layer height data, and the second rock layer height data, and obtaining a real-time risk threshold value based on the geological risk index and a preset risk threshold value, and obtaining a terrain risk index of the sub-area based on a terrain calculation model, the first sliding belt thickness data, and the second sliding belt thickness data; The prediction analysis module is used to obtain prediction results based on the terrain risk indicators and real-time risk thresholds of the sub-areas.

8. The mine geological disaster risk prediction system according to claim 7, characterized in that: The data processing module is also used for: Obtain correction parameters based on geological risk indicators; Get the real-time risk threshold based on the modified parameters and the preset risk threshold.

9. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor is used to execute the computer program in the memory to implement the method for predicting the risk of mining geological disasters as described in any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for predicting the risk of mining geological disasters described in any one of claims 1 to 6 is implemented.

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