A method, system, device and medium for predicting the risk of mine geological disasters

Abstract

The present invention discloses a method, system, device and medium for predicting the risk of mine geological disasters, which relates to the technical field of data processing. The method includes obtaining a mine area, geological information and topographic information, dividing the area into multiple sub-areas, obtaining a preset risk threshold, obtaining a first time point and a second time point; obtaining first slip zone thickness data on the surface of the sub-area at the first time point, obtaining first rock layer height data inside the sub-area at the first time point, obtaining second slip zone thickness data on the surface of the sub-area at the 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, obtaining a real-time risk threshold according to the geological risk index and the preset risk threshold, and obtaining a topographic risk index of the sub-area; obtaining a prediction result according to the topographic risk index of the sub-area and the real-time risk threshold. The present invention has the advantages of considering the associated 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, device and medium for predicting the risk of mine geological disasters. Background Art

[0002] Mine geological disasters are safety hazards that cannot be ignored during the mining development process. Their occurrence is often related to various factors such as the geological structure, topographic features, and human activities in the mine area. These disasters not only threaten the lives of mine workers but also may cause serious damage to the surrounding environment, resulting in huge economic losses. Therefore, accurately predicting the risk of mine geological disasters is of great significance for ensuring mine safety production and protecting the surrounding environment.

[0003] With the progress of 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 mine geological disasters. However, most of these methods focus on single geological structures or topographic features and ignore the interaction and influence between the two. In fact, the risk of mine geological disasters is the result of the combined action of these two factors, and the analysis of a single factor is difficult to accurately reflect the overall picture of the risk. In addition, existing risk prediction methods often use fixed rules for judgment, ignoring the spatio-temporal variability of geological and topographic conditions. In practical applications, since the geological and topographic conditions in the mine area change over time, this method may lead to deviations or misjudgments in the prediction results. Summary of the Invention

[0004] Aiming at the defects in the prior art, the present invention provides a method, system, device and medium for predicting the risk of mine geological disasters.

[0005] A method for predicting the risk of mine geological disasters includes: obtaining a mine area, the geological information corresponding to the mine area, and the topographic information corresponding to the mine area, dividing the mine area into multiple sub-areas according to different topographic information, obtaining the preset risk threshold corresponding to the sub-area according to the topographic information corresponding to the sub-area, and obtaining a first time point and a second time point at preset time intervals according to the topographic information; obtaining the first slip zone thickness data on the surface of the sub-area at the first time point, obtaining the first rock layer height data inside the sub-area at the first time point, obtaining the second slip zone thickness data on the surface of the sub-area at the second time point, and obtaining the second rock layer height data inside the sub-area at the second time point; obtaining the 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 the real-time risk threshold according to the geological risk index and the preset risk threshold, and obtaining the topographic risk index of the sub-area based on the topographic calculation model, the first slip zone thickness data, and the second slip zone thickness data; obtaining the prediction result according to the topographic risk index and the real-time risk threshold of the sub-area.

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

[0007] Optionally, obtaining a correction parameter according to a geological risk index is expressed as: ; where is the correction parameter, is the initial preset parameter, is the geological risk index.

[0008] Optionally, obtaining a prediction result according to a terrain risk index and a real-time risk threshold of a sub-region includes: obtaining the number of sub-regions where the terrain risk index exceeds the real-time risk threshold and recording it as the target number; obtaining a risk proportion according to the target number and the total number of sub-regions; obtaining a prediction result according to the risk proportion.

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

[0010] Optionally, the terrain calculation model in obtaining the terrain risk index of a sub-region based on a terrain calculation model, first slip zone thickness data, and second slip zone thickness data is expressed as: ); where is the terrain risk index of the i-th sub-region, is the first slip zone thickness data, is the second slip zone thickness data, is the first time point, is the second time point.

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

[0012] Optionally, the data processing module is further configured to: obtain a correction parameter according to the geological risk index; obtain the real-time risk threshold according to the correction parameter and the preset risk threshold.

[0013] An electronic device is also provided, including: a memory, on which a computer program is stored; a processor, configured to execute the computer program in the memory to implement the above-mentioned mine geological disaster risk prediction method.

[0014] A non-transitory 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 mine geological disaster risk prediction method is implemented.

[0015] The beneficial effects of the present invention are embodied in:

[0016] In the entire mine geological disaster risk prediction method, by comprehensively obtaining the geological information and topographic information of the mine area and dividing the mine area into multiple sub-areas with relatively uniform topographic features, the risk prediction can be carried out more precisely for each sub-area, improving the accuracy and pertinence of the prediction; further, the slip 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 spatio-temporal variability of geological and topographic conditions can be dynamically reflected, avoiding the prediction deviation or misjudgment caused by the traditional method's neglect of this variability; further, the geological calculation model and the topographic calculation model are used to process the rock layer height data and the slip zone thickness data respectively, and the geological risk index and the topographic risk index of the sub-area are calculated. These two indexes comprehensively consider the influence of geological and topographic factors on the disaster risk, making the prediction result 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, making the risk judgment standard more in line with the current geological risk situation, improving the timeliness and accuracy of the prediction; finally, by comparing the topographic risk index and the real-time risk threshold, it can be intuitively judged whether the sub-area is in a high-risk state, providing a scientific basis for subsequent risk management and prevention and control measures, and helping to take targeted measures in a timely manner to reduce the geological disaster risk and ensure the safety of the mine area. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally denoted by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0018] Figure 1 It is a schematic diagram of the steps of the mine geological disaster risk prediction method of the present invention;

[0019] Figure 2 It is a partial schematic diagram of the steps of S3 in the mine geological disaster risk prediction method of the present invention;

[0020] Figure 3 It is a schematic diagram of the steps of S4 in the mine geological disaster risk prediction method of the present invention;

[0021] Figure 4 It is a block diagram of an electronic device shown in an embodiment of the present invention.

[0022] Reference Numerals:

[0023] 700 - Electronic device, 701 - Processor, 702 - Memory, 703 - Multimedia component, 704 - I / O interface, 705 - Communication component. Detailed implementation manners

[0024] To make the objectives, 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 with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. The components of the embodiments of the present invention described and illustrated herein usually can be arranged and designed in various different configurations.

[0025] 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 claimed present invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0026] It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", etc. are only used for descriptive distinction and cannot be understood as indicating or implying relative importance.

[0027] As Figure 1 shown, a method for predicting the risk of mine geological disasters is provided, including:

[0028] S1. Obtain the mine area, the geological information corresponding to the mine area, and the terrain information corresponding to the mine area, divide the mine area into multiple sub-areas according to different terrain information, obtain the preset risk thresholds corresponding to the sub-areas according to the terrain information corresponding to the sub-areas, and obtain the first time point and the second time point at preset time intervals according to the terrain information;

[0029] S2. Obtain the first slip zone thickness data on the surface of the sub-area at the first time point, obtain the first rock layer height data inside the sub-area at the first time point, obtain the second slip zone thickness data on the surface of the sub-area at the second time point, and obtain the second rock layer height data inside the sub-area at the second time point;

[0030] S3. Obtain the geological risk indicators of the sub-area based on the geological calculation model, the first rock layer height data, and the second rock layer height data, obtain the real-time risk threshold according to the geological risk indicators and the preset risk threshold, and obtain the terrain risk indicators of the sub-area based on the terrain calculation model, the first slip zone thickness data, and the second slip zone thickness data;

[0031] S4. Obtain the prediction result according to the terrain risk indicators and the real-time risk threshold of the sub-area.

[0032] In this embodiment, it should be noted that in S1, first, it is necessary to comprehensively obtain relevant information of the mine area, including the geographical location, scope, and specific geological and topographical information of the mine area. Geological information may cover the type, structure, thickness of rock strata, and historical geological activity records, etc.; topographical information includes the slope, height, and geomorphic features of the mine, which helps to understand the external form of the mine area. In this way, according to the differences in topographical information, the mine area is divided into multiple sub-areas. Each sub-area has relatively uniform topographical features, so that risk prediction can be carried out more accurately for each sub-area. At the same time, according to the topographical information of each sub-area, a preset risk threshold is set for it; this preset risk threshold is determined based on topographical features and historical disaster data and is used for subsequent risk assessment. In addition, two time points, namely the first time point and the second time point, are also determined according to the topographical information, and these two time points are separated by a preset time period. The selection of these two time points is determined based on topographical features and historical disaster data. Generally, for topographical features where historical disasters are likely to occur, only a shorter preset time period is required to ensure that sufficient change information is captured while saving resources, so as to conduct accurate risk prediction.

[0033] For example, suppose there is a mine area with complex terrain, including steep slopes, flat valleys, and rugged ridges. After obtaining the geological and topographical information of this mine 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, since geological disasters are likely to occur, a relatively low preset risk threshold will be set. 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 likely to occur, so a relatively high preset risk threshold will be set. At the same time, the beginning and end of one 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. At the same time, the beginning and end of three weeks may be selected as the first time point and the second time point.

[0034] In S2, it is necessary to obtain the data of the thickness of the slip zone of each sub-surface in the mining area and the data of the rock layer height inside the sub-region at two specific time points, namely the first time point and the second time point. The data of the thickness of the slip zone refers to the thickness of the surface slip zone (i.e., the surface of the potential slip plane), which is an important indicator for evaluating the terrain stability. By measuring the first slip zone thickness data and the second slip zone thickness data at the first time point and the second time point, the change in the thickness of the slip zone can be observed, and then it can be judged whether the terrain tends to be unstable. The data of the rock layer height reflects the change in the position of the rock layer in the vertical direction and is a direct manifestation of 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. When operating specifically, professional measurement equipment and technologies, such as radar detection, laser scanning or GPS monitoring, etc., will be used to ensure the accuracy and reliability of the data, and these data will provide a basis for the subsequent calculation of geological risk indicators and terrain risk indicators.

[0035] For example, assume that the data of the thickness of the slip zone and the data of the rock layer height are obtained in a certain sub-region. At the first time point, the thickness of the slip zone at a certain place in this sub-region is measured to be 20 cm, and the height of a certain rock layer is 100 m. After a preset period of time (such as two weeks), at the second time point, the thickness of the slip zone and the rock layer height at this place are measured again, and it is found that the thickness of the slip zone has increased to 25 cm, and the rock layer height has decreased to 99.5 m. This means that during this period, the slip zone has thickened significantly, and the rock layer has settled. These data changes will be used as an important basis for the subsequent calculation of geological risk indicators and terrain risk indicators to help more accurately evaluate the geological disaster risks in the hillside area.

[0036] In S3, first, it is necessary to use a geological calculation model to process the rock layer height data within the sub-region obtained at the first time point and the second time point. Specifically, by comparing the rock layer height data at the 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, based on these rock layer height data and combined with the geological calculation model, the geological risk index of the sub-region is calculated. This index is used to quantify the geological disaster risk of the sub-region. Next, according to the calculated geological risk index and the preset risk threshold, a real-time risk threshold is obtained. 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-region. In addition, it is also necessary to use a terrain calculation model to process the slip zone thickness data on the surface of the sub-region obtained at the first time point and the second time point. By comparing the slip zone thickness data at the two time points, such as the first slip zone thickness data at the first time point and the second slip zone thickness data at the second time point, the change in the slip zone thickness can be observed, and then it can be judged whether the terrain tends to be unstable. Combining with the terrain calculation model, the terrain risk index of the sub-region can be calculated, and this index is used to quantify the disaster risk caused by terrain factors in the sub-region.

[0037] For example, assume that geological disaster risk prediction is carried out in a sub-region of a hillside area. At the first time point, the rock layer height at a certain location in this sub-region is measured to be 120 meters, and the slip zone thickness is 30 centimeters. After a preset time period of two weeks, at the second time point, the rock layer height and the slip zone thickness at this location are measured again, and it is found that the rock layer height has decreased to 119.6 meters, and the slip zone thickness has increased to 35 centimeters. This means that during this time period, the rock layer has settled and the slip zone has thickened. Next, using the geological calculation model and combining the change data of the rock layer height, the geological risk index of this sub-region is calculated. At the same time, according to the geological risk index and the preset risk threshold, a real-time risk threshold is dynamically adjusted. In addition, the terrain calculation model is also used to combine the change data of the slip zone thickness to calculate the terrain risk index of this sub-region. Finally, the terrain risk index is compared with the real-time risk threshold to evaluate the geological disaster risk of this sub-region.

[0038] In S4, first, it is necessary to analyze one by one the terrain risk indicators calculated for each sub-region; the terrain risk indicator is obtained based on a terrain calculation model, combined with the change in the thickness data of the sliding zone at two time points (the first time point and the second time point), and it reflects the disaster risk that the sub-region may face due to terrain factors (such as the thickening of the sliding zone, slope changes, etc.). Next, the terrain risk indicator 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 indicator, which takes into account the changes in geological activity, and thus can more accurately reflect the actual risk level of the sub-region at the current time point. By comparing the terrain risk indicator and the real-time risk threshold, it can be determined whether the sub-region is in a high-risk state.

[0039] For example, assume that geological disaster risk predictions are made for three sub-regions (hillslope area, valley area, and ridge area) in a mining area. In step S3, the terrain risk indicators and real-time risk thresholds of each sub-region have been calculated. Now, in step S4, these data are compared. Taking the hillslope area as an example, if its terrain risk indicator exceeds the real-time risk threshold, then it can be considered that the sub-region is in a high-risk state at the current time point and may be prone to geological disasters such as landslides. On the contrary, if the terrain risk indicator of the valley area is lower than its real-time risk threshold, then it can be considered that the risk of this sub-region is relatively low and the possibility of geological disasters is small. Through such comparisons and analyses, a comprehensive understanding of the overall geological disaster risk in the mining area can be obtained, providing a scientific basis for subsequent risk management and prevention measures.

[0040] In summary, in the entire mine geological disaster risk prediction method, by comprehensively obtaining the geological information and topographic information of the mine area and dividing the mine area into multiple sub-areas with relatively uniform topographic features, the risk prediction can be more precisely carried out for each sub-area, improving the accuracy and pertinence of the prediction; further, the data of the slip zone thickness on the surface of the sub-area and the data of the rock layer height inside the sub-area are obtained at two specific time points. By comparing the changes in these data, the spatio-temporal variability of the geological and topographic conditions can be dynamically reflected, avoiding the prediction deviation or misjudgment caused by the traditional method's neglect of this variability; further, the geological calculation model and the topographic calculation model are used to process the rock layer height data and the slip zone thickness data respectively, and the geological risk index and the topographic risk index of the sub-area are calculated. These two indexes comprehensively consider the influence of geological and topographic factors on the disaster risk, making the prediction result 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, making the risk judgment standard more in line with the current geological risk situation, improving the timeliness and accuracy of the prediction; finally, by comparing the topographic risk index and the real-time risk threshold, it can be intuitively judged whether the sub-area is in a high-risk state, providing a scientific basis for subsequent risk management and prevention and control measures, and helping to take targeted measures in a timely manner to reduce the geological disaster risk and ensure the safety of the mine area.

[0041] As Figure 2 shown, in one embodiment, obtaining the real-time risk threshold according to the geological risk index and the preset risk threshold in S3 includes:

[0042] S31. Obtain a correction parameter according to the geological risk index;

[0043] S32. Obtain the real-time risk threshold according to the correction parameter and the preset risk threshold.

[0044] In this embodiment, it should be noted that in S31, the geological risk index is calculated through a geological calculation model by combining the changes in the rock layer height data at two time points (the first time point and the second time point). It quantifies the activity level of 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. Through a certain algorithm or mapping relationship, the geological risk index is converted into a value that can adjust the preset risk threshold. This correction parameter reflects the degree of deviation of the sub-region risk level from the preset conditions under the current geological conditions. For example, if the geological risk index indicates that the rock layer settlement rate in the sub-region is relatively fast, it means that the geological activities in this region are relatively active, and then the correction parameter may increase 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 will determine the relationship between the correction parameter and the geological risk index based on historical data and geological characteristics.

[0045] In S32, the process of obtaining the real-time risk threshold based on the correction parameter and the preset risk threshold is the key to dynamically adjusting the risk judgment standard. The preset risk threshold is comprehensively determined based on the topographic characteristics and historical disaster data of the sub-region and is used to preliminarily evaluate the geological disaster risks. However, due to the spatio-temporal 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 an additive, thereby increasing or decreasing the threshold of risk judgment. For example, if the correction parameter is less than 1, the real-time risk threshold will decrease, 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, assume that the preset risk threshold of a certain 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 topographic risk index of this sub-region exceeds 8, it will be considered in a high-risk state, thus triggering corresponding risk management and prevention measures.

[0046] In one embodiment, the obtaining of the correction parameter according to the geological risk index in S31 is expressed as:

[0047] ; where

[0048] is the correction parameter, is the initial preset parameter, is the geological risk index.

[0049] In this embodiment, it should be noted that is a parameter for adjusting the preset risk threshold, which determines the degree of reduction of the real-time risk threshold relative to the preset risk threshold. is the initial preset parameter, which is a constant set based on historical data and experience and is used to control the reference value of the correction parameter of.

[0050] The selection of should take into account the general characteristics of the geological conditions and the distribution of historical disaster data. The value of is usually greater than or equal to 1, and its magnitude affects the overall range of the correction parameter . A larger value means that under the same geological risk index, the correction parameter will be relatively large, which may lead to a relatively high real-time risk threshold and make the system less sensitive to risk changes.

[0051] is the exponential decay term, is the geological risk index. The use of is due to the fact that the geological risk index has a non-linear and decreasing effect on the risk level. That is, as increases, geological activities become more active, but the rate of risk increase gradually slows down, which is consistent with the impact result of actual geological activities on risk. When is small, is close to 1, meaning that the geological risk is low, and the correction parameter is mainly determined by . When increases, gradually decreases, resulting in a decrease in the correction parameter as well, which reflects that as the geological risk increases, the system should become more sensitive, that is, the real-time risk threshold should be correspondingly reduced.

[0052] 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.

[0053] As Figure 3 shown, in one embodiment, obtaining the prediction result according to the terrain risk index and the real-time risk threshold of the sub-region in S4 includes:

[0054] S41. Obtain the number of sub-regions where the terrain risk index exceeds the real-time risk threshold and record it as the target number;

[0055] S42. Obtain the risk proportion according to the target number and the total number of sub-regions;

[0056] S43. Obtain the prediction result according to the risk proportion.

[0057] In this embodiment, it should be noted that in S41, it is necessary to compare the terrain risk index of each sub-region with its real-time risk threshold one by one to identify those sub-regions whose terrain risk index exceeds the real-time risk threshold. Due to changes in terrain factors (such as significant thickening of the slip zone, increased slope change, etc.), the disaster risk of these sub-regions has risen to a level that requires attention. By comparison, the number of sub-regions 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-regions in the mine area are in a high geological disaster risk state at the current time point. For example, assume that the mine area is divided into 10 sub-regions. After comparison, it is found that the terrain risk indices of 3 of them exceed their respective real-time risk thresholds. Then these 3 sub-regions are counted into the target number, that is, the target number is 3.

[0058] In S42, after obtaining the target number, it is necessary to further calculate the risk proportion to quantify the geological disaster risk level of the entire mine area. The risk proportion is obtained by dividing the target number by the total number of sub-regions. This proportional index can intuitively reflect how many sub-regions are in a high-risk state at the current time point. The higher the risk proportion, the greater the overall geological disaster risk of the mine area. Continuing with the above example, the total number of sub-regions is 10 and the target number is 3, then the risk proportion is 30%. This means that at the current time point, 30% of the sub-regions in the mine area are in a high geological disaster risk state.

[0059] In S43, finally, obtain the prediction result according to the risk proportion. The prediction result is an overall assessment of the geological disaster risk situation in the mine area, which may include risk levels, risk trends, and recommended risk management measures, etc. The risk proportion is one of the important bases for determining the prediction result. Generally speaking, the higher the risk proportion, 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 proportion is 30%, then the prediction result may indicate that there is a moderately high geological disaster risk in the mine area, and it is recommended to strengthen monitoring and early warning, and take necessary prevention and control measures for high-risk sub-regions to reduce the possibility and impact of geological disasters.

[0060] In one embodiment, the geological calculation model in S3 for 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:

[0061] ; where

[0062] is the geological risk index for the i-th sub-region, is the first rock layer height data for the i-th sub-region, is the second rock layer height data for the i-th sub-region, is the historical subsidence rate of the rock layer in the i-th sub-region, is the first time point, is the second time point.

[0063] In this embodiment, it should be noted that the absolute value operation calculates the change in the height of the rock layer between two time points, where the absolute value ensures that the change is positive whether the rock layer is subsiding or uplifting; in this way, by capturing the actual change in the height of the rock layer, regardless of the direction, it can accurately reflect the activity level of geological activities.

[0064] As a standardization factor, standardize the change in the height of the rock layer by the product of the historical subsidence rate and the time period; The value represents the height change of the rock layer within the preset time period at the historical subsidence rate; among them, different sub-regions may have different historical subsidence rates. Standardization makes the geological risk indicators comparable between different sub-regions. At the same time, considering the time period ensures that the historical total change is reflected.

[0065] It is ensured that the indicator reflects the change rate per unit time, that is, the rate of change with respect to time is obtained, so that the geological risk indicator eliminates the influence of time and can accurately reflect the change amount.

[0066] is to take the logarithm of the standardized change rate to compress the data range in a non-linear manner, and at the same time make the geological risk indicator less sensitive to extreme values, while maintaining sensitivity to small changes, which conforms to the actual characteristics of geological activities, that is, small changes may indicate potential risks, while extreme changes may indicate that the critical point of disaster occurrence is approaching.

[0067] Suppose there is a sub-region with the following data: = 120 meters (the height of the rock layer at the first time point), = 119.5 meters (the height of the rock layer at the second time point), = 0.05 meters / month (historical subsidence rate), = 0 (assumed to be the starting time point), = 0.5 months (the time point two weeks later).

[0068] After substituting, the calculated result is That is to say, through the geological calculation model, this change is converted into a geological risk index (about 3.7136), which reflects the geological activity level and potential risks of the sub-region at the current time point. This index can be used for subsequent risk assessment and decision-making to help identify high-risk areas and take corresponding prevention and control measures.

[0069] In one embodiment, the terrain calculation model in obtaining the terrain risk index of the sub-region based on the terrain calculation model, the first slip zone thickness data, and the second slip zone thickness data in S3 is expressed as:

[0070] ); where

[0071] is the terrain risk index of the i-th sub-region, is the first slip zone thickness data, is the second slip zone thickness data, is the first time point, is the second time point.

[0072] In this embodiment, it should be noted that the absolute value operation is to calculate the change amount of the slip zone thickness between two time points; the absolute value ensures that the change amount is positive whether the slip zone thickens or thins; therefore, this helps to accurately reflect the amplitude of the terrain change regardless of the change direction. Normalize the change amount of the slip zone thickness to the change rate per unit time (such as per day, per week, or per month); this helps to compare the change rates in different time periods and makes the risk index comparable in terms of time; through normalization, the influence of different time intervals on the risk index can be eliminated. compresses the data range in a non-linear manner, is not sensitive to small changes, and is relatively sensitive to extreme changes; this conforms to the actual characteristics of terrain activities, that is, small changes may indicate no risk, while extreme changes are likely to cause a significant increase in risk.

[0073] Suppose there is a sub-region with the following slip zone thickness data: = 20 cm (the slip zone thickness at the first time point). = 25 cm (the slip zone thickness at the second time point). = 0 weeks (assumed to be the starting time point). = 2 weeks (the time point two weeks later). Substitute these data into the terrain calculation model: Calculate the change amount of the slip zone thickness to get exp(2.5) ≈ 12.1825. This index reflects the terrain change rate and potential risks of the sub-region at the current time point and can be used for subsequent risk assessment and decision-making.

[0074] A mine geological disaster risk prediction system is also provided, which includes:

[0075] A first acquisition module, configured to acquire the mine area, the geological information corresponding to the mine area, and the terrain information corresponding to the mine area, divide the mine area into multiple sub-areas according to different terrain information, obtain the preset risk thresholds corresponding to the sub-areas according to the terrain information corresponding to the sub-areas, and obtain a first time point and a second time point at preset time intervals according to the terrain information;

[0076] A second acquisition module, configured to acquire the first sliding zone thickness data on the surface of the sub-area at the first time point, acquire the first rock layer height data inside the sub-area at the first time point, acquire the second sliding zone thickness data on the surface of the sub-area at the second time point, and acquire the second rock layer height data inside the sub-area at the second time point;

[0077] A data processing module, configured to obtain the 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, obtain the real-time risk threshold according to the geological risk index and the preset risk threshold, and obtain the terrain risk index of the sub-area based on the terrain calculation model, the first sliding zone thickness data, and the second sliding zone thickness data;

[0078] A prediction and analysis module, configured to obtain a prediction result according to the terrain risk index and the real-time risk threshold of the sub-area.

[0079] In one embodiment, the data processing module is further configured to: obtain a correction parameter according to the geological risk index; obtain the real-time risk threshold according to the correction parameter and the preset risk threshold.

[0080] In one embodiment, the prediction and analysis module is further configured to: obtain the number of sub-areas whose terrain risk index exceeds the real-time risk threshold and record it as the target number; obtain the risk proportion according to the target number and the total number of sub-areas; obtain the prediction result according to the risk proportion.

[0081] In this embodiment, it should be noted that regarding the above mine geological disaster risk prediction system, the specific manner of performing operations has been described in detail in the embodiment of the mine geological disaster risk prediction method, and will not be elaborated here.

[0082] Figure 4 It is a block diagram of an electronic device for a mine geological disaster risk prediction method shown according to an exemplary embodiment. As Figure 4 shown, the electronic device 700 may include: a processor 701, a memory 702. The electronic device 700 may further include one or more of a multimedia component 703, an I / O interface 704, and a communication component 705.

[0083] Among them, 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 mine geological disaster risk prediction method. The memory 702 is used to store various types of data to support the operation of the electronic device 700. These data may include, for example, instructions for any application or method operating on the electronic device 700, as well as application-related data, such as contact data, sent and received messages, pictures, audio, video, and so on. 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 (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc. The multimedia component 703 may include a screen and an audio component. The screen may be a touch screen, for example, 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 a keyboard, a mouse, 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: a Wi-Fi module, a Bluetooth module, an NFC module, and so on.

[0084] In an exemplary embodiment, the electronic device 700 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, and is used to execute the above-mentioned mine geological disaster risk prediction method.

[0085] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When the program instructions are executed by a processor, the steps of the above-mentioned mine geological disaster risk prediction method 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 mine geological disaster risk prediction method.

[0086] In another exemplary embodiment, a computer program product is also provided. The computer program product 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.

[0087] The preferred embodiments of the present disclosure have been 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, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0088] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combination methods.

[0089] In addition, any combination can be made between various different embodiments of the present disclosure as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

[0090] 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 foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and 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 covered within the scope of the claims and the description 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; Among them, the geological calculation model 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, is the second time point; Wherein, obtaining the real-time risk threshold includes: obtaining the correction parameter according to the geological risk index; obtaining the real-time risk threshold according to the correction parameter and the preset risk threshold; obtaining the correction parameter is expressed as: ;in, To correct the parameters, is the initial preset parameter, It is an indicator of geological risk; Among them, the terrain calculation model 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; 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 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.

3. 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; Among them, the geological calculation model 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, is the second time point; The data processing module is also used to: obtain correction parameters according to geological risk indicators; obtain real-time risk thresholds according to the correction parameters and preset risk thresholds; obtain correction parameters expressed as: ;in, To correct the parameters, is the initial preset parameter, It is an indicator of geological risk; Among them, the terrain calculation model 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; 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.

4. 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 mine geological disaster risk prediction method described in claim 1 or 2.

5. 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 as described in claim 1 or 2 is implemented.

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