Mine safety risk prevention and control method and system based on multi-source data fusion

Abstract

The invention discloses a mine safety risk prevention and control method and system based on multi-source data fusion, and particularly relates to the technical field of mine safety monitoring, and the method comprises the steps: obtaining surface topography, an underground geologic structure and real-time monitoring parameters through remote sensing images, drilling data and dynamic monitoring equipment, and constructing a mining area geologic database with consistent time and space; fusing geologic feature data, integrating earth surface and underground feature data by using a three-dimensional geologic modeling technology, and mapping dynamic monitoring parameters into a model to generate a dynamic geologic feature field; performing clustering analysis on the abnormal feature points based on a spatial clustering algorithm, and calibrating a potential safety hazard region; calculating a regional risk comprehensive index by combining the risk values of the dynamic features, the geological features and the spatial features; early warning is triggered in a graded mode according to the comprehensive index, prevention and control measures are put forward, and the evaluation model is dynamically updated; comprehensive support is provided for mine potential safety hazard area monitoring and safety management decision making, and the method is suitable for risk management scenes of complex mining areas.

Description

Technical Field

[0001] The present invention relates to the technical field of mine safety monitoring, and in particular to a mine safety risk prevention and control method and system based on multi-source data fusion. Background Art

[0002] With the continuous expansion of mining scale, the complexity of the geological environment in mining areas has increased significantly. Geological disasters such as landslides and subsidence have occurred frequently, seriously threatening the safety of mining workers and facilities. Therefore, how to efficiently identify potential safety hazard areas, assess geological risks, and take timely prevention and control measures has become a core issue in mine safety management. Traditional methods of geological risk prevention and control in mining areas mostly rely on a single data source, such as surface topography or dynamic monitoring data, which is difficult to fully reflect the geological environment and dynamic changes of mining areas. In addition, the calculation method of risk assessment is usually relatively simple, lacking the deep integration and precise modeling of multi-source data features, which limits the effectiveness of safety prevention and control.

[0003] Existing technologies have exposed several key problems in practical applications. First, due to the single data source, the identification of safety hazard areas is not comprehensive enough, and key geological features or dynamic monitoring parameters may be missed. Second, the risk assessment model lacks comprehensive consideration of geological, dynamic and spatial characteristics, resulting in insufficient accuracy of assessment results and failure to provide a reliable basis for decision-making. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a mine safety risk prevention and control method and system based on multi-source data fusion to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a mine safety risk prevention and control method based on multi-source data fusion, comprising the following steps:

[0006] Step 1: Multi-source geological data collection and preprocessing: Collect multi-source geological data in the mining area, including surface topographic data, underground geological structure data and dynamic monitoring data; perform format conversion and spatiotemporal alignment on the multi-source geological data, fill in missing values ​​through interpolation algorithms, and use adaptive denoising methods to filter out abnormal data, so as to generate a mining area geological database that is consistent in time and space;

[0007] Step 2: Fusion of geological feature data: Based on the preprocessed data, a multi-source geological feature model of the mining area is constructed, the surface topography and underground geological structure are integrated to generate a three-dimensional geological profile, and the dynamic monitoring data is mapped to the three-dimensional geological model to generate a dynamic geological feature field;

[0008] Step 3: Identification of potential safety hazards: Analyze the abnormal feature points in the model through spatial clustering algorithm to identify potential safety hazards caused by landslides, subsidence or mining in the mining area;

[0009] Step 4: Dynamic assessment of geological risks in mining areas: Combined with mining activities and geological conditions in the mining area, dynamic quantitative assessment of potential safety hazards is conducted to calculate the comprehensive risk index;

[0010] Step 5. Risk warning and prevention: Based on the classification of the comprehensive risk index, trigger warning signals of different levels.

[0011] Furthermore, the surface topographic data obtains a digital elevation model of the mining area through remote sensing images or drone aerial photography, and extracts slope, slope direction and surface deformation characteristics; the underground geological structure data describes the rock layer distribution, fracture development degree and rock strength through drilling data and geophysical surveys; the dynamic monitoring data obtains stress change and displacement velocity dynamic monitoring parameters through slope displacement sensors, stress sensors and pore water pressure gauges.

[0012] Furthermore, the potential safety hazard area identification includes the following steps:

[0013] Step 101: construct a geological data feature space and extract key geological features, such as slope, slope aspect, fracture distribution, rock strength and stress state;

[0014] Step 102: Use the local anomaly factor method to screen abnormal feature points in the multidimensional feature space;

[0015] Step 103: Analyze the spatial distribution of abnormal feature points through a density clustering algorithm, and mark the potential safety hazard areas based on density accessibility;

[0016] Step 104: Marking the geological characteristics of the potential safety hazard area, including the degree of rock strata fracture, stress concentration area and surface settlement rate;

[0017] Step 105: Output a distribution map of potential safety hazards, including the location, scope, and credibility of potential safety hazards, to provide input data for subsequent dynamic evaluation.

[0018] Furthermore, the credibility of the potential safety hazard area is obtained in the following manner:

[0019] Step 201: Obtain a spatial feature similarity score. The spatial feature similarity is used to quantify the matching degree between the spatial features of the potential safety hazard area and the historical disaster cases. The calculation formula is:

[0020]

[0021] Among them, S spa represents the spatial feature similarity score; F i represents the ith spatial feature of the potential safety hazard area; H irepresents the i-th spatial feature in the historical disaster case; w i represents the weight of the i-th spatial feature (determined according to its impact on the occurrence of disasters); ∈ is a small constant to prevent the denominator from being zero; N1 represents the number of spatial features;

[0022] Step 202: Obtain a geological feature similarity score. The geological feature similarity is used to measure the matching degree between the potential safety hazard area and the historical disaster case in geological conditions (such as the degree of fracture development and rock formation strength). The calculation formula is:

[0023]

[0024] Among them, S geo Indicates the geological feature similarity score; G s represents the sth geological feature of the potential safety hazard area; K s represents the ith geological feature of the historical disaster case; v s represents the weight of the sth geological feature; N2 represents the number of geological features;

[0025] Step 203: Obtain a dynamic feature similarity score. The dynamic feature similarity is used to quantify the matching degree between the dynamic monitoring data (such as displacement rate and stress distribution) of the potential safety hazard area and the disaster precursor features of the historical disaster cases. The calculation formula is:

[0026]

[0027] Among them, S dyn represents the dynamic feature similarity score; D j represents the jth dynamic feature of the potential safety hazard area; R j represents the jth dynamic feature in the historical case, u j represents the weight of the jth dynamic feature; N3 represents the number of dynamic features;

[0028] Step 204: Calculate the credibility of the potential safety hazard area using the following formula:

[0029]

[0030] Among them, C risk Indicates the credibility of the potential safety hazard area; w spa ,w geo ,w dyn They represent the weight of each feature score, which is adjusted according to the disaster sensitivity of the specific scenario.

[0031] Furthermore, the credibility C risk The range is [0, 1], where C risk→1 The characteristics of the potential safety hazard area are highly similar to historical cases and have high credibility; C risk →0 means that the characteristics of the safety hazard area are quite different from the historical cases and the credibility is low.

[0032] Furthermore, the calculation of the comprehensive risk index includes the following steps:

[0033] Calculate the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value of the potential safety hazard area respectively;

[0034] Calculate the weight coefficient based on the area ratio of potential safety hazards;

[0035] Combined with the credibility of the potential safety hazard area, the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value are integrated to calculate the comprehensive risk index using the weighted average formula.

[0036] Furthermore, the comprehensive risk index FR is obtained as follows:

[0037] Assume that there are several potential safety hazards areas, and use t to represent the sequence number of the potential safety hazards areas.

[0038] Get the average risk R of each potential safety hazard area avg,t , Credibility C risk,t and weight coefficient w t , the weight coefficient w is expressed by the area ratio of the potential safety hazard area t ;

[0039] The comprehensive risk index FR is calculated by the following formula:

[0040]

[0041]

[0042] Among them, R T represents the dynamic characteristic risk value, R D represents the geological characteristic risk value, R S Represents the spatial characteristic risk value.

[0043] The dynamic characteristic risk value is obtained in the following way:

[0044]

[0045] in, Refers to the dynamic characteristic difference between the potential safety hazard area and the historical case; T τ Refers to the risk threshold of dynamic features; α T is the nonlinear adjustment coefficient, which controls the sensitivity of the risk value to the characteristic difference;

[0046] The geological characteristic risk value is obtained in the following way:

[0047]

[0048] in, Indicates the difference in geological characteristics between the potential safety hazard area and historical cases; Indicates risk thresholds for geological features;

[0049] The spatial characteristic risk value The way to obtain is:

[0050]

[0051] in, Represents the difference in spatial characteristics between the safety hazard area and the historical case; represents the risk threshold of spatial characteristics; β S is the nonlinear adjustment coefficient, which controls the sensitivity of characteristic differences to risk values.

[0052] Furthermore, the risk warning and prevention steps also include pushing risk distribution maps and emergency recommendations through the mining area management platform, and proposing targeted risk prevention and control measures based on the assessment results. The risk prevention and control measures include slope reinforcement, drainage project optimization and dangerous area closure, continuous monitoring of dynamic geological data in the reinforced area, updating the risk assessment model, and forming a closed-loop feedback mechanism.

[0053] Furthermore, the calculation method of the comprehensive risk index includes:

[0054] According to the spatial distribution and characteristic similarity of the potential safety hazard areas, an inter-regional risk interaction matrix is ​​constructed; each element of the risk interaction matrix represents the risk coupling intensity between two potential safety hazard areas;

[0055] Coupling risk correction: Based on the initial risk value, the risk value of each potential safety hazard area is corrected through matrix calculation;

[0056] The risk coupling intensity has a weighted effect on the correction value. On the basis of risk correction, the comprehensive risk index of the safety hazard area is recalculated, and the evaluation results that fully reflect the risk interaction effects between regions are output.

[0057] To achieve the purpose of the present invention, a mine safety risk prevention and control system based on multi-source data fusion is provided, comprising:

[0058] The geological data acquisition module is used to collect multi-source geological data of the mining area, including surface topographic data (such as slope, aspect and surface deformation characteristics), underground geological structure data (such as fracture development and rock formation strength) and dynamic monitoring data (such as stress change and displacement velocity); the collected data is formatted and aligned in time and space, missing values ​​are filled by interpolation algorithms, and abnormal data are filtered out by adaptive denoising methods to generate a unified mining area geological database;

[0059] The geological feature fusion module builds a multi-source geological feature model based on the mining area geological database provided by the geological data acquisition module. Specifically, it uses surface topography data and underground geological structure data to build a three-dimensional geological model, generate a three-dimensional geological profile of the mining area, and map dynamic monitoring data (such as displacement and stress) into the three-dimensional geological model to generate a dynamic geological feature field.

[0060] The safety hazard area identification module uses the multi-source geological feature model generated by the geological feature fusion module to analyze the abnormal feature points in the model through a spatial clustering algorithm, identify the potential safety hazard areas caused by landslides, subsidence or mining in the mining area, and mark the geological characteristics (such as the degree of rock stratum fracture and stress concentration location); output the distribution map of the safety hazard area, including location, scope and credibility;

[0061] The geological risk assessment module performs dynamic quantitative assessment based on the distribution map of potential safety hazards provided by the potential safety hazard identification module, combined with mining activities and geological conditions in the mining area; it calculates the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value respectively, calculates the comprehensive risk index combined with the credibility of the potential safety hazard area, and quantifies the risk level of each potential safety hazard area;

[0062] The early warning and prevention and control module triggers multi-level early warning signals based on the comprehensive risk index and risk level classification provided by the geological risk assessment module; pushes risk distribution maps and emergency recommendations through the mining area management platform; formulates targeted prevention and control measures (such as slope reinforcement and drainage optimization) based on the risk level, and conducts continuous dynamic monitoring of the reinforced area to form a closed-loop feedback mechanism.

[0063] Technical effects and advantages of the present invention:

[0064] The present invention realizes the precise prevention and control of mine safety risks through multi-source data fusion technology, and solves the problem of incomplete risk identification and inaccurate assessment due to insufficient single data source in the prior art. The present invention adopts a combination of surface topographic data, underground geological structure data and dynamic monitoring data, and comprehensively presents the geological state and dynamic changes of the mining area through data preprocessing, three-dimensional geological model construction and dynamic feature field mapping, ensuring the comprehensiveness and scientificity of hidden danger identification. Through the optimized risk comprehensive index calculation method, combined with the difference analysis of dynamic, geological and spatial characteristics and credibility assessment, the accuracy and sensitivity of risk assessment are further improved. At the same time, the present invention continuously monitors and dynamically adjusts the risks of mine safety hazard areas through dynamic early warning and feedback mechanisms, forming a closed-loop prevention and control, and improving the pertinence and timeliness of prevention and control measures. Compared with traditional methods, the present invention can significantly reduce the risk of mine disasters, ensure the safety and sustainability of mining operations, and has strong technical innovation and practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 This is a flow chart of the mine safety risk prevention and control method of the present invention;

[0066] Figure 2 This is a flowchart of identifying potential safety hazards areas according to the present invention. DETAILED DESCRIPTION

[0067] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0068] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0069] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0070] Example 1

[0071] See also Figure 1 The present invention provides a flow chart of a mine safety risk prevention and control method. Figure 1 A mine safety risk prevention and control method based on multi-source data fusion is shown, comprising the following steps:

[0072] Step 1: Multi-source geological data collection and preprocessing:

[0073] Collect multi-source geological data within the mining area, including:

[0074] Surface topographic data: Obtain the digital elevation model (DEM) of the mining area surface through remote sensing images or drone aerial photography, and extract the slope, slope aspect and surface deformation characteristics;

[0075] Underground geological structure data: Combine drilling data with geophysical surveys (such as electrical prospecting or seismic wave inversion) to describe the distribution of rock formations in the mining area, the degree of fracture development, and rock strength;

[0076] Dynamic monitoring data of the mining area: dynamic monitoring parameters are obtained through slope displacement sensors, stress sensors and pore water pressure gauges; the dynamic monitoring parameters at least include: stress changes and displacement speed;

[0077] The collected data is converted into a format and aligned in time and space, missing values ​​are filled by interpolation algorithm, and abnormal data are filtered out by adaptive denoising method to generate a mining area geological database that is consistent in time and space (providing a high-quality data foundation for subsequent fusion analysis);

[0078] Step 2: Fusion of geological feature data:

[0079] Based on the data preprocessed in step 1, a multi-source geological characteristic model of the mining area is constructed, including:

[0080] Fusion of geological spatial features: Use multi-source data to build a three-dimensional geological model, integrate the surface topography and underground geological structure, and generate a three-dimensional geological profile of the mining area;

[0081] Dynamic parameter mapping: Mapping dynamic monitoring data with the three-dimensional geological model in time and space to generate a dynamic geological characteristic field;

[0082] Step 3: Identification of potential safety hazards: Analyze the abnormal feature points in the model through spatial clustering algorithm to identify potential safety hazards caused by landslides, subsidence or mining in the mining area;

[0083] Step 4: Dynamic assessment of geological risks in mining areas: Dynamically quantify the geological risks in potential safety hazards areas and output a comprehensive risk index;

[0084] Step 5: Risk warning and prevention:

[0085] Design and implement mine safety prevention and control measures based on the comprehensive risk index, including:

[0086] Multi-level early warning system: According to the classification of the comprehensive risk index (low, medium and high), different levels of early warning signals are triggered, and risk distribution maps and emergency suggestions are pushed through the mining area management platform;

[0087] Risk prevention and control measures: Based on the assessment results, targeted prevention and control measures are proposed, including slope reinforcement (such as anchor support), drainage project optimization, and closure of dangerous areas;

[0088] Dynamic monitoring and feedback mechanism: Continuously monitor the dynamic geological data of the reinforced area, update the risk assessment model, and form a closed-loop feedback mechanism to ensure the prevention and control effect;

[0089] Output: mining area early warning signals, emergency response plans and reinforcement measures implementation results.

[0090] What needs to be further explained in the embodiments of the present invention is that the surface topographic data obtains the digital elevation model of the mining area through remote sensing images or drone aerial photography, and extracts the slope, slope direction and surface deformation characteristics; the underground geological structure data describes the rock layer distribution, fracture development degree and rock strength through drilling data and geophysical surveys (such as electrical prospecting or seismic wave inversion); the dynamic monitoring data obtains stress change and displacement velocity dynamic monitoring parameters through slope displacement sensors, stress sensors and pore water pressure gauges.

[0091] Explanation: The dynamic geological characteristic field is a three-dimensional spatial model generated based on the fusion of multi-source geological data, which is used to describe the comprehensive characteristics of the geological structure and real-time dynamic changes in the mining area. Specifically, the surface topography data provides macro-geomorphological features such as slope and slope direction, and the underground geological structure data reflects stability factors such as rock layer distribution and fracture development, while the dynamic monitoring data records the changes in geological parameters in real time and reveals the activity trends of safety hazard areas. The dynamic geological characteristic field can intuitively display the spatial distribution and risk evolution process of safety hazard areas, and is an important basis for safety hazard area identification, risk assessment and early warning decision-making. Through the construction of this characteristic field, a refined description of the complex geological environment of the mining area can be achieved, providing core data support for the mine safety risk prevention and control method of multi-source data fusion.

[0092] In the embodiments of the present invention, it is necessary to further explain that Figure 2 A flowchart of identifying potential safety hazards areas is shown in FIG. 1 , wherein the method of identifying potential safety hazards areas is as follows:

[0093] Step 101: Construct geological data feature space

[0094] Based on the multi-source geological data collected in the mining area, key geological features such as slope, slope direction, crack distribution, rock strength and stress state are extracted and integrated into a unified multi-dimensional feature space; each dimension of the multi-dimensional feature space represents a geological attribute, providing a data basis for subsequent clustering algorithms;

[0095] Step 102: Screening of abnormal feature points

[0096] Standardize the data in the multidimensional feature space, calculate the distribution mean and variance of each dimensional feature, and mark the abnormal points in the feature space that deviate from the normal value range through a method based on local abnormal factors;

[0097] Explanation: The abnormal points may represent potential hazards of landslide, subsidence or other geological hazards;

[0098] Step 103: Using spatial clustering algorithm to identify potential safety hazard areas

[0099] Using density clustering algorithms (such as DBSCAN algorithm), cluster analysis of potential safety hazards is performed based on the spatial distribution of abnormal feature points. High-density areas in space are marked as clusters by defining core points and density accessibility, and isolated points are regarded as noise. High-density areas in the clustering results are potential safety hazard areas.

[0100] Step 104, marking geological characteristics of the potential safety hazard area: marking the clustering results with geological attributes, where the geological attribute information includes the degree of rock stratum fracture, stress concentration area, and surface settlement rate;

[0101] Step 105: Output the distribution map of potential safety hazards

[0102] A visual distribution map of potential safety hazards is generated based on the clustering results and transmitted to the mine management platform. The distribution map includes the location, scope, credibility and corresponding risk level of the potential safety hazards, providing input data for subsequent dynamic risk assessment and early warning.

[0103] It needs to be further explained in the embodiment of the present invention that the credibility of the potential safety hazard area is obtained in the following manner:

[0104] Step 201: Obtain a spatial feature similarity score. The spatial feature similarity is used to quantify the matching degree between the spatial features of the potential safety hazard area and the historical disaster cases. The calculation formula is:

[0105]

[0106] Among them, S spa represents the spatial feature similarity score; F i represents the ith spatial feature of the potential safety hazard area; H i represents the i-th spatial feature in the historical disaster case; w i represents the weight of the i-th spatial feature (determined according to its impact on the occurrence of disasters); ∈ is a small constant to prevent the denominator from being zero; N1 represents the number of spatial features;

[0107] The formula combines the similarity score with the weight through geometric product, nonlinearly amplifying the significant differences between features;

[0108] Step 202: Obtain a geological feature similarity score. The geological feature similarity is used to measure the matching degree between the potential safety hazard area and the historical disaster case in geological conditions (such as the degree of fracture development and rock formation strength). The calculation formula is:

[0109]

[0110] Among them, S geo Indicates the geological feature similarity score; G s represents the sth geological feature of the potential safety hazard area; K s represents the ith geological feature of the historical disaster case; v s represents the weight of the sth geological feature; N2 represents the number of geological features;

[0111] The exponential function is used to compress the accumulated differences of inconsistent features to avoid the extreme impact of a single feature on the overall score;

[0112] Step 203: Obtain a dynamic feature similarity score. The dynamic feature similarity is used to quantify the matching degree between the dynamic monitoring data (such as displacement rate and stress distribution) of the potential safety hazard area and the disaster precursor features of the historical disaster cases. The calculation formula is:

[0113]

[0114] Among them, S dyn represents the dynamic feature similarity score; D j represents the jth dynamic feature of the potential safety hazard area; R j represents the jth dynamic feature in the historical case; u j represents the weight of the jth dynamic feature; N3 represents the number of dynamic features;

[0115] Step 204: Calculate the credibility of the potential safety hazard area using the following formula:

[0116]

[0117] Among them, C risk Indicates the credibility of the potential safety hazard area; w spa ,w geo ,w dyn They represent the weight of each feature score, which is adjusted according to the disaster sensitivity of the specific scenario.

[0118] The formula adopts a weighted geometric mean approach, emphasizing the balance of feature scores while amplifying the contribution of high-risk features to the final credibility.

[0119] Explanation: The reliability C risk The range is [0, 1], where C risk →1 The characteristics of the potential safety hazard area are highly similar to historical cases and have high credibility; C risk →0 means that the characteristics of the safety hazard area are quite different from historical cases and the credibility is low; the similarity of the spatial, geological and dynamic characteristics of the safety hazard area is calculated by nonlinear geometric formula, and the credibility score is obtained by combining the weighted geometric average, which avoids the limitations of traditional mean calculation and fully considers the weight differences and dynamic influences between features, providing rigorous technical support for the scientific assessment of safety hazard areas in mining areas.

[0120] It needs to be further explained in the embodiment of the present invention that the comprehensive risk index FR is obtained in the following manner:

[0121] Assume that there are several potential safety hazards areas, and use t to represent the sequence number of the potential safety hazards areas.

[0122] Get the average risk R of each potential safety hazard area avg,t , Credibility Crisk,t and weight coefficient w t , the weight coefficient w is expressed by the area ratio of the potential safety hazard area t ;

[0123] The comprehensive risk index FR is calculated by the following formula:

[0124]

[0125] Among them, R T represents the dynamic characteristic risk value, R D represents the geological characteristic risk value, R S Represents the spatial characteristic risk value.

[0126] It needs to be further explained in the embodiment of the present invention that the dynamic characteristic risk value is obtained in the following manner:

[0127]

[0128] in, Refers to the dynamic characteristic difference between the potential safety hazard area and the historical case; T τ Refers to the risk threshold of dynamic features; α T is the nonlinear adjustment coefficient, which controls the sensitivity of the risk value to the characteristic difference;

[0129] The geological characteristic risk value is obtained in the following way:

[0130]

[0131] in, Indicates the difference in geological characteristics between the potential safety hazard area and historical cases; Indicates risk thresholds for geological features;

[0132] The spatial characteristic risk value The way to obtain is:

[0133]

[0134] in, Represents the difference in spatial characteristics between the safety hazard area and the historical case; represents the risk threshold of spatial characteristics; β S is the nonlinear adjustment coefficient, which controls the sensitivity of characteristic differences to risk values.

[0135] The risks in the potential safety areas of mining areas often present complex spatial distribution characteristics, and there may be significant linkage effects between the potential safety areas. For example, slope landslides may cause surface deformation in the surrounding areas, while the collapse of underground goafs may cause large-scale surface subsidence. This risk linkage characteristic is usually called the risk coupling effect between regions. Traditional risk assessment methods usually analyze each potential safety area independently, ignoring the mutual influence between regions, resulting in the assessment results may underestimate the overall risk and fail to accurately reflect the actual threat of regional linkage to mining safety. In order to improve the comprehensiveness and accuracy of risk assessment, a calculation method that can quantify the risk interaction effect between regions is designed, and the regional linkage effect is incorporated into the calculation framework of the comprehensive risk index. This method can dynamically adjust the risk value of each potential safety area, fully consider the linkage characteristics between regions, and comprehensively reflect the overall potential risks of the mining area.

[0136] In a possible embodiment, the method for calculating the comprehensive risk index includes:

[0137] Interaction analysis of potential safety hazards: Based on the spatial distribution and feature similarity of potential safety hazards, a risk interaction matrix between regions is constructed; each element of the risk interaction matrix represents the risk coupling intensity between two potential safety hazards regions;

[0138] Explanation: The risk coupling intensity is calculated by the following factors:

[0139] The physical distance between the two areas;

[0140] the degree of matching of features, such as similarity of crack distribution and stress variations;

[0141] Statistical weights of similar linkage situations in historical cases;

[0142] Coupling risk correction: Based on the initial risk value, the risk value of each potential safety hazard area is corrected through matrix calculation;

[0143] Explanation: The matrix operation corrects the risk value of each potential safety hazard area as follows:

[0144] The modified risk value of each potential safety hazard area is equal to its initial risk comprehensive index plus the risk value of other areas transmitted through risk coupling; the risk coupling intensity has a weighted effect on the modified value, and a higher coupling intensity will have a greater impact on the risk value of adjacent areas;

[0145] On the basis of risk correction, the comprehensive risk index of the safety hazard area is recalculated, and the assessment results that fully reflect the risk interaction effects between regions are output. The calculation results of the comprehensive risk index can be used for risk classification, early warning triggering and optimization of prevention and control measures.

[0146] Example 2

[0147] The embodiment of the present invention provides a mine safety risk prevention and control system based on multi-source data fusion, including:

[0148] The geological data acquisition module is used to collect multi-source geological data of the mining area, including surface topographic data (such as slope, aspect and surface deformation characteristics), underground geological structure data (such as fracture development and rock formation strength) and dynamic monitoring data (such as stress change and displacement velocity); the collected data is formatted and aligned in time and space, missing values ​​are filled by interpolation algorithms, and abnormal data are filtered out by adaptive denoising methods to generate a unified mining area geological database;

[0149] The geological feature fusion module constructs a multi-source geological feature model based on the mining area geological database provided by the geological data acquisition module. Specifically, it uses surface topography data and underground geological structure data to build a three-dimensional geological model, generate a three-dimensional geological profile of the mining area, and map dynamic monitoring data (such as displacement and stress) into the three-dimensional geological model to generate a dynamic geological feature field.

[0150] The safety hazard area identification module uses the multi-source geological feature model generated by the geological feature fusion module to analyze the abnormal feature points in the model through a spatial clustering algorithm, identify the potential safety hazard areas caused by landslides, subsidence or mining in the mining area, and mark the geological characteristics (such as the degree of rock stratum fracture and stress concentration location); output the distribution map of the safety hazard area, including location, scope and credibility;

[0151] The geological risk assessment module performs dynamic quantitative assessment based on the distribution map of potential safety hazards provided by the potential safety hazard identification module, combined with mining activities and geological conditions in the mining area; it calculates the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value respectively, calculates the comprehensive risk index combined with the credibility of the potential safety hazard area, and quantifies the risk level of each potential safety hazard area;

[0152] The early warning and prevention and control module triggers multi-level early warning signals based on the comprehensive risk index and risk level classification provided by the geological risk assessment module. The risk distribution map and emergency suggestions are pushed through the mining area management platform. According to the risk level, targeted prevention and control measures (such as slope reinforcement and drainage optimization) are formulated, and the reinforced area is continuously and dynamically monitored to form a closed-loop feedback mechanism.

[0153] Explanation: The geological data acquisition module provides a high-quality geological database, which provides a unified and accurate data basis for subsequent modules; the geological feature fusion module constructs a geological model based on the database, which provides spatial and dynamic characteristics for the safety hazard area identification module; the safety hazard area identification module outputs the distribution map and characteristic information of the safety hazard area, which provides input for the geological risk assessment module to quantify the risk level; the geological risk assessment module outputs the comprehensive risk index and risk level, which provides a decision-making basis for the early warning and prevention and control module; the early warning and prevention and control module transmits the prevention and control measures and feedback information to the management platform to complete closed-loop management.

[0154] It should be noted that in the present disclosure, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element limited by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0155] Although the embodiments disclosed in the present disclosure are as above, the above contents are only embodiments adopted for facilitating the understanding of the present disclosure and are not intended to limit the present disclosure. Any technician in the technical field to which the present disclosure belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present disclosure, but the scope of patent protection of the present disclosure shall still be subject to the scope defined in the attached claims.

Claims

1. A mine safety risk prevention and control method based on multi-source data fusion, characterized in that: The following steps are involved: Step 1: Multi-source geological data collection and preprocessing: Collect multi-source geological data in the mining area, including surface topographic data, underground geological structure data and dynamic monitoring data; perform format conversion and spatiotemporal alignment on the multi-source geological data, fill in missing values ​​through interpolation algorithms, and use adaptive denoising methods to filter out abnormal data, so as to generate a mining area geological database that is consistent in time and space; Step 2: Fusion of geological feature data: Based on the preprocessed data, a multi-source geological feature model of the mining area is constructed, the surface topography and underground geological structure are integrated to generate a three-dimensional geological profile, and the dynamic monitoring data is mapped to the three-dimensional geological model to generate a dynamic geological feature field; Step 3: Identification of potential safety hazards: Analyze the abnormal feature points in the model through spatial clustering algorithm to identify potential safety hazards caused by landslides, subsidence or mining in the mining area; Step 4: Dynamic assessment of geological risks in mining areas: Combined with mining activities and geological conditions in the mining area, dynamic quantitative assessment of potential safety hazards is conducted to calculate the comprehensive risk index; Step 5. Risk warning and prevention: Based on the classification of the comprehensive risk index, trigger warning signals of different levels.

2. The mine safety risk prevention and control method based on multi-source data fusion according to claim 1 is characterized in that: The potential safety hazard area identification comprises the following steps: Step 101, constructing a geological data feature space and extracting key geological features; Step 102: Use the local anomaly factor method to screen abnormal feature points in the multidimensional feature space; Step 103: Analyze the spatial distribution of abnormal feature points through a density clustering algorithm, and mark the potential safety hazard areas based on density accessibility; Step 104: Marking the geological characteristics of the potential safety hazard area, including the degree of rock strata fracture, stress concentration area and surface settlement rate; Step 105: Output a distribution map of potential safety hazards, including the location, scope, and credibility of the potential safety hazards.

3. The mine safety risk prevention and control method based on multi-source data fusion according to claim 2 is characterized in that: The credibility of the potential safety hazard area is obtained in the following manner: Step 201: Obtain a spatial feature similarity score. The spatial feature similarity is used to quantify the matching degree between the spatial features of the potential safety hazard area and the historical disaster cases. The calculation formula is: Among them, S spa represents the spatial feature similarity score; F i represents the ith spatial feature of the potential safety hazard area; H i represents the i-th spatial feature in the historical disaster case; w i represents the weight of the i-th spatial feature; ∈ is a small constant to prevent the denominator from being zero; N1 represents the number of spatial features; Step 202: Obtain a geological feature similarity score. The geological feature similarity is used to measure the matching degree between the potential safety hazard area and the historical disaster case in geological conditions. The calculation formula is: Among them, S geo Indicates the geological feature similarity score; G s represents the sth geological feature of the potential safety hazard area; K s represents the ith geological feature of the historical disaster case; v s represents the weight of the sth geological feature; N2 represents the number of geological features; Step 203: Obtain a dynamic feature similarity score. The dynamic feature similarity is used to quantify the matching degree between the dynamic monitoring data of the potential safety hazard area and the disaster precursor features of historical disaster cases. The calculation formula is: Among them, S dyn represents the dynamic feature similarity score; D j represents the jth dynamic feature of the potential safety hazard area; R j represents the jth dynamic feature in the historical case; u j represents the weight of the jth dynamic feature; N3 represents the number of dynamic features; Step 204: Calculate the credibility of the potential safety hazard area using the following formula: Among them, C risk Indicates the credibility of the potential safety hazard area; w spa ,w geo ,w dyn Represent the weight of each feature score.

4. The mine safety risk prevention and control method based on multi-source data fusion according to claim 3 is characterized in that: The credibility C risk The range is [0, 1], where C risk →1 The characteristics of the potential safety hazard area are highly similar to historical cases and have high credibility; C risk →0 means that the characteristics of the safety hazard area are quite different from the historical cases and the credibility is low.

5. The mine safety risk prevention and control method based on multi-source data fusion according to claim 1 is characterized in that: The calculation of the risk comprehensive index includes the following steps: Calculate the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value of the potential safety hazard area respectively; Calculate the weight coefficient based on the area ratio of potential safety hazards; Combined with the credibility of the potential safety hazard area, the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value are integrated to calculate the comprehensive risk index using the weighted average formula.

6. The mine safety risk prevention and control method based on multi-source data fusion according to claim 5 is characterized in that: The method for obtaining the comprehensive risk index FR is as follows: Assume that there are several potential safety hazards areas, and use t to represent the sequence number of the potential safety hazards areas. Get the average risk R of each potential safety hazard area avg,t , Credibility C risk,t and weight coefficient w t , the weight coefficient w is expressed by the area ratio of the potential safety hazard area t ; The comprehensive risk index FR is calculated by the following formula: Among them, R T represents the dynamic characteristic risk value, R D represents the geological characteristic risk value, R S Represents the spatial characteristic risk value.

7. The mine safety risk prevention and control method based on multi-source data fusion according to claim 6 is characterized in that: The dynamic characteristic risk value is obtained in the following way: in, Refers to the dynamic characteristic difference between the potential safety hazard area and the historical case; T τ Refers to the risk threshold of dynamic features; α T is the nonlinear adjustment coefficient, which controls the sensitivity of the risk value to the characteristic difference; The geological characteristic risk value is obtained in the following way: in, Indicates the difference in geological characteristics between the potential safety hazard area and the historical case; Indicates risk thresholds for geological features; The spatial characteristic risk value The way to obtain is: in, Represents the difference in spatial characteristics between the safety hazard area and the historical case; represents the risk threshold of spatial characteristics; β S is the nonlinear adjustment coefficient, which controls the sensitivity of characteristic differences to risk values.

8. The mine safety risk prevention and control method based on multi-source data fusion according to claim 1 is characterized in that: The risk warning and prevention steps also include pushing risk distribution maps and emergency recommendations through the mining area management platform, proposing targeted risk prevention and control measures based on the assessment results, continuously monitoring the dynamic geological data of the reinforced area, updating the risk assessment model, and forming a closed-loop feedback mechanism.

9. The mine safety risk prevention and control method based on multi-source data fusion according to claim 6 is characterized in that: The calculation method of the comprehensive risk index includes: According to the spatial distribution and characteristic similarity of the potential safety hazard areas, an inter-regional risk interaction matrix is ​​constructed; each element of the risk interaction matrix represents the risk coupling intensity between two potential safety hazard areas; Coupling risk correction: Based on the initial risk value, the risk value of each potential safety hazard area is corrected through matrix calculation; The risk coupling intensity has a weighted effect on the correction value. On the basis of risk correction, the comprehensive risk index of the safety hazard area is recalculated, and the evaluation results that fully reflect the risk interaction effects between regions are output.

10. The mine safety risk prevention and control system based on multi-source data fusion is characterized by: include: The geological data acquisition module is used to collect multi-source geological data of the mining area, including surface topographic data, underground geological structure data and dynamic monitoring data; The collected data is formatted and aligned in time and space, missing values ​​are filled by interpolation algorithm, and abnormal data are filtered out by adaptive denoising method to generate a unified mining area geological database; The geological feature fusion module builds a multi-source geological feature model based on the mining area geological database provided by the geological data acquisition module; The safety hazard area identification module uses the multi-source geological feature model generated by the geological feature fusion module to analyze the abnormal feature points in the model through a spatial clustering algorithm, identify the potential safety hazard areas caused by landslides, subsidence or mining in the mining area, and mark the geological characteristics; output the distribution map of the safety hazard area, including location, scope and credibility; The geological risk assessment module conducts dynamic quantitative assessment based on the distribution map of potential safety hazards provided by the potential safety hazard identification module, combined with mining activities and geological conditions in the mining area; Calculate the dynamic characteristic risk value, geological characteristic risk value and spatial characteristic risk value respectively, calculate the comprehensive risk index based on the credibility of the potential safety hazard area, and quantify the risk level of each potential safety hazard area; The early warning and prevention and control module triggers multi-level early warning signals based on the comprehensive risk index and risk level classification provided by the geological risk assessment module.

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