A method for monitoring mine geological environment in the process of green mine management

Abstract

The present invention discloses a method for monitoring the geological environment of a mine in a green mine governance process, and relates to the field of geological environment resource management of a mine. The method comprises: receiving M green governance schemes in a pre-planned green governance scheme, analyzing the impact of environmental geological changes on geological stability, and establishing M environmental geological safety intervals; extracting a first governance node, collecting geological environment data before execution, and generating first initial geological environment data; judging whether the first initial geological environment data is in a first environmental geological safety interval; if so, collecting first dynamic meteorological forecast data in the planned execution time zone, analyzing the changes in geological environment parameters, and generating first dynamic geological environment forecast data; judging whether it exceeds the first environmental geological safety interval, and performing geological environment monitoring reminders. The method solves the technical problem of insufficient early warning accuracy and timeliness in existing geological environment monitoring, and achieves the technical effect of improving early warning accuracy and timeliness.

Description

Technical Field

[0001] The present application relates to the field related to mine geological environment resource management, and in particular to a mine geological environment monitoring method in the process of green mine management. Background Art

[0002] In the process of green mine governance, mine geological environment monitoring is a key link to ensure the safety of governance projects and the effectiveness of ecological restoration. At present, mine geological environment monitoring mainly adopts the static threshold method, which monitors parameters such as displacement and groundwater level in the entire region by presetting fixed safety standards. However, this method is not associated with the dynamic needs of different governance stages (such as slope cutting and shaping, vegetation reclamation), resulting in rigid monitoring standards and inability to accurately identify stage-specific risks; at the same time, there is a lack of fusion analysis of real-time meteorological data (such as short-term rainfall and sudden temperature changes), making it difficult to timely warn of derivative disasters such as landslides and leakage caused by meteorological disturbances, resulting in a high false alarm rate and delayed response.

[0003] Among the current related technologies, mining geological environment monitoring has technical problems such as insufficient accuracy and timeliness of early warning. Summary of the invention

[0004] This application provides a mine geological environment monitoring method in the process of green mine governance. It divides M governance nodes according to the mine governance plan, matches each node with a dynamic geological safety interval, and collects real-time geological data when starting the node to verify whether the node safety interval is met and intercept substandard working conditions. After the verification is passed, meteorological forecast data is accessed during the node construction period to simulate the trend of geological parameter changes. If the predicted data exceeds the current node safety interval, technical means such as graded warnings are immediately triggered, thereby achieving the technical effect of improving the accuracy and timeliness of warnings.

[0005] The present application provides a method for monitoring the geological environment of a mine in a green mine governance process, including: receiving M green governance plans corresponding to M governance nodes in a pre-planned green governance plan for a preset mine area, analyzing the impact of environmental geological changes on the geological stability of the preset mine area, and establishing M environmental geological safety intervals; extracting the first governance node in the green governance plan, collecting geological environment data before the node is executed, and generating first initial geological environment data; extracting the first environmental geological safety interval from the M environmental geological safety intervals, and determining whether the first initial geological environment data is within the first environmental geological safety interval; if so, collecting first dynamic meteorological forecast data in the planned execution time zone of the first governance node, analyzing the changes in geological environment parameters, and generating first dynamic geological environment forecast data; Determine whether the first dynamic geological environment prediction data exceeds the first environmental geological safety interval, and conduct geological environment monitoring reminders during the mine governance process; wherein, analyze the impact of environmental geological changes on the geological stability of the preset mining area, establish M environmental geological safety intervals, and perform the following processing: collect global geological data before mining for the preset mining area under the first preset stable environmental conditions to generate a global geological environment data set; model the mining characteristics of the M governance nodes based on the M green governance schemes, and establish M mining structure models; based on the M mining structure models, with the global geological environment data set as the center, adjust the global geological environment data set according to the preset adjustment step size, analyze the mine geological stability, and generate the M environmental geological safety intervals.

[0006] In a possible implementation, based on the M mining structure models, with the global geological environment dataset as the center, the global geological environment dataset is adjusted according to a preset adjustment step size to analyze the mine geological stability, generate the M environmental geological safety intervals, and perform the following processing: extract mine structure features based on the M mining structure models to generate M mine structure parameter sets; perform multiple iterative adjustments on the global geological environment dataset according to the preset adjustment step size, combine the geological environment dataset after each adjustment with the M mine structure parameter sets to perform mine geological stability analysis, and generate M critical geological environment data with mine stability indicators less than a preset stability threshold; generate the M environmental geological safety intervals using the M critical geological environment data.

[0007] In a possible implementation, the geological environment data set after each adjustment is combined with M mine structure parameter sets to perform mine geological stability analysis, and the following processing is performed: a mine geological stability event library is constructed, wherein the mine geological stability event library contains mine structure parameter samples and geological environment samples corresponding to multiple geological instability events; a similarity analysis network is constructed and connected to the mine geological stability event library, and the geological environment data set after each adjustment is combined with M mine structure parameter sets through the similarity analysis network, and then the mine structure parameter samples and geological environment samples corresponding to multiple geological instability events are subjected to similarity analysis, and a mine stability index is generated with maximum comparison similarity.

[0008] In a possible implementation, the following processing is performed: if the first initial geological environment data is not within the first environmental geological safety interval, a geological environment monitoring abnormality reminder signal is generated.

[0009] In a possible implementation, the first dynamic meteorological forecast data is collected in the planning execution time zone of the first governance node, the change analysis of the geological environment parameters is performed, and the first dynamic geological environment prediction data is generated, and the following processing is performed: the mining structure corresponding to the first governance node is determined as a retrieval element, and a first mapping sample data set about meteorological data and geological environment parameters is collected; the correlation influence relationship between meteorological data and geological environment parameters is analyzed with the first mapping sample data set; the influence of the first dynamic meteorological forecast data on the first initial geological environment data is analyzed with the said correlation influence relationship, and the first dynamic geological environment prediction data is generated.

[0010] In a possible implementation, the following processing is also performed: a mining pollution leakage monitoring point set is set in the preset mining area based on the M green governance plans; the mining pollution leakage monitoring point set is connected in the planning execution time zone of the first governance node to monitor the pollutant distribution characteristics of pollutants generated by mining, and generate first pollutant distribution monitoring data; the first pollutant distribution monitoring data is combined with the first dynamic geological environment prediction data to perform a geological environment pollution proximity trend analysis to generate a first pollution proximity trend; and a geological environment pollution warning is issued based on the first pollution proximity trend.

[0011] In a possible implementation, the first pollutant distribution monitoring data and the first dynamic geological environment prediction data are combined to perform a geological environment pollution proximity trend analysis to generate a first pollution proximity trend, and the following processing is performed: mine environmental pollutants are determined based on the first pollutant distribution monitoring data; the mine environmental pollutants are used as retrieval elements, historical pollution diffusion data sets are collected, and a correlation network between pollutant diffusion characteristics and geological environment is trained; the first pollutant distribution monitoring data and the first dynamic geological environment prediction data are analyzed by the correlation network, and the diffusion characteristics of mine environmental pollutants are output; the first pollution proximity trend is generated based on the diffusion characteristics of the mine environmental pollutants.

[0012] The method for monitoring the geological environment of a mine in the process of green mine governance proposed in this application first receives M green governance schemes corresponding to M governance nodes in the pre-planned green governance scheme for a preset mine area, analyzes the impact of environmental geological changes on the geological stability of the preset mine area, establishes M environmental geological safety intervals, then extracts the first governance node in the green governance scheme, collects geological environmental data before node execution, generates the first initial geological environmental data, and then extracts the first environmental geological safety interval from the M environmental geological safety intervals, determines whether the first initial geological environmental data is in the first environmental geological safety interval, and if so, collects the first dynamic meteorological forecast data in the planned execution time zone of the first governance node, analyzes the changes in geological environmental parameters, generates the first dynamic geological environmental forecast data, and finally determines whether the first dynamic geological environmental forecast data exceeds the first environmental geological safety interval, and performs geological environmental monitoring reminders during the mine governance process. The technical effect of improving the accuracy and timeliness of early warning is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0014] Figure 1 A schematic flow chart of a method for monitoring the geological environment of a mine during green mine management provided in an embodiment of the present application.

[0015] Figure 2 A schematic diagram of a process for providing geological environment pollution warning in a mine geological environment monitoring method during a green mine management process provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0017] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0018] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0019] The present application embodiment provides a method for monitoring the geological environment of a mine in a green mine management process, such as Figure 1 As shown, the method includes: Step S100, receiving M green governance plans corresponding to M governance nodes in a pre-planned green governance plan for a preset mining area, analyzing the impact of environmental geological changes on the geological stability of the preset mining area, and establishing M environmental geological safety intervals.

[0020] Specifically, pre-planned green governance plans for preset mining areas are received through user-side interfaces (such as APIs). These plans include detailed mining plans, ecological restoration measures, etc. to minimize the impact on the environment and ensure the sustainable use of resources. Using geological modeling software and geographic information systems (GIS), combined with historical geological data (including geological structure maps, stratigraphic lithology distribution, historical collapse records, etc.), remote sensing images (providing information such as surface morphology and vegetation coverage in the mining area), geological exploration reports (detailed records of groundwater levels, rock and soil properties, fault distribution, etc.), etc., analyze the geological environmental changes that may be caused by mining, such as stratum displacement, groundwater level changes, etc. Based on the above analysis, one or more environmental geological safety intervals are set for each governance node. These intervals reflect the allowable range of changes in geological environmental parameters to ensure the geological stability of the mine.

[0021] Among them, the influence of environmental geological changes on the geological stability of the preset mining area is analyzed, and M environmental geological safety intervals are established. Step S100 further includes step S110, in which global geological data collection is performed for the preset mining area before mining under the first preset stable environmental conditions to generate a global geological environment data set. Specifically, the basic geological data of the preset mining area without external interference (such as rainfall, strong wind, etc.) is obtained, including using geological exploration equipment (such as geological radar, seismograph, gravimeter, etc.) to conduct a comprehensive exploration of the mining area, collect information such as the distribution, thickness, and physical properties of underground rock formations; use satellite remote sensing or drone aerial photography technology to obtain remote sensing data such as surface morphology, vegetation coverage, and soil moisture in the mining area; set up monitoring stations at key locations of the mine, and use professional instruments (such as inclinometers, water level gauges, stress gauges, etc.) to measure geological environmental parameters in real time or regularly. The above exploration, remote sensing and field measurement data are integrated into a comprehensive global geological environment data set, which reflects the basic geological characteristics of the mining area.

[0022] Step S120, based on the M green governance schemes, the mining characteristics of the M governance nodes are modeled, and M mining structure models are established. Specifically, each green governance scheme (including detailed mining plans, ecological restoration measures and other documents) is analyzed in detail to understand the mining scope, depth, method and other information of each governance node. Use 3D modeling software (such as AutoCAD, 3DMax, SketchUp, etc.) to perform 3D modeling on the mining area of ​​each governance node according to the results of the scheme analysis, and simulate the changes in the mine structure after mining. Extract key mining features such as mining boundaries, mining depths, mining volumes, etc. from the 3D model.

[0023] Step S130, based on the M mining structure models, with the global geological environment data set as the center, the global geological environment data set is adjusted according to the preset adjustment step length, and then the geological stability of the mine is analyzed to generate the M environmental geological safety intervals. Specifically, the global geological environment data set is integrated with each mining structure model to simulate the changes in the geological environment after mining. Use geological stability analysis software (such as FLAC3D, UDEC, etc.) to simulate and analyze the fused data to evaluate the impact of mining activities on geological stability. According to the stability analysis results, one or more environmental geological safety intervals are set for each governance node. These intervals reflect the allowable range of variation of geological environment parameters to ensure the geological stability of the mine. This implementation method comprehensively considers the basic geological characteristics of the mining area and the impact of mining activities on the geological environment through global geological data collection and three-dimensional modeling, and uses geological stability analysis software and expert experience to accurately evaluate the impact of mining activities on geological stability, thereby improving the accuracy of generating environmental geological safety intervals.

[0024] In a possible implementation, based on the M mining structure models, with the global geological environment data set as the center, the global geological environment data set is adjusted according to a preset adjustment step size to analyze the geological stability of the mine, and the M environmental geological safety intervals are generated. Step S130 further includes step S131, extracting the structural features of the mine based on the M mining structure models to generate M mining structure parameter sets. Specifically, the M mining structure models are opened using three-dimensional modeling software, and the key structural parameters of the mine, such as mining depth, mining boundary, pillar size, mining volume, etc., are extracted through the built-in analysis tools or plug-ins of the software. The extracted structural parameters are integrated into M mining structure parameter sets, and each set corresponds to the mining characteristics of a governance node.

[0025] Step S132, the global geological environment data set is adjusted multiple times according to the preset adjustment step length, and the geological environment data set after each adjustment is combined with M mine structure parameter sets to perform mine geological stability analysis, and M critical geological environment data with mine stability index less than the preset stability threshold are generated. Specifically, taking the global geological environment data set as the starting point, multiple iterative adjustments are performed according to the preset adjustment step length (such as the small change amount of the geological parameter) to generate a series of different geological environment data sets. For each adjusted geological environment data set, a geological stability analysis software (such as FLAC3D, UDEC, MIDAS GTS, etc.) is used to perform simulation analysis in combination with the corresponding mine structure parameter set. During the analysis process, the impact of mining on the geological environment, such as stress redistribution, rock formation displacement, etc., is considered, and the mine stability index (such as safety factor, displacement, stress concentration, etc.) is calculated. Find the geological environment data set that makes the mine stability index less than the preset stability threshold (the critical value of the stability index set according to the mine geological conditions and mining requirements), and the geological environment parameters corresponding to these data sets are the critical geological environment data.

[0026] Step S133, generate the M environmental geological safety intervals with the M critical geological environment data. Specifically, the M critical geological environment data identified in step S132 are integrated to form M data sets, each of which corresponds to the safety boundary conditions of a governance node. According to the critical geological environment parameters in each data set, the corresponding environmental geological safety intervals are set. These intervals reflect the allowable range of variation of geological environment parameters while maintaining the geological stability of the mine. This implementation method can accurately identify the key geological environment parameters that affect the geological stability of the mine through multiple iterative adjustments and stability analysis, thereby setting a reasonable safety interval and ensuring the comprehensiveness and accuracy of the safety interval setting.

[0027] In a possible implementation, the geological environment data set after each adjustment is combined with M mine structure parameter sets to perform mine geological stability analysis. Step S132 further includes step S1321, constructing a mine geological stability event library, wherein the mine geological stability event library contains mine structure parameter samples and geological environment samples corresponding to multiple geological instability events. Specifically, relevant data (at least hundreds) of multiple geological instability events that occurred in history are collected from multiple sources such as professional geological databases, mine mining records, and historical meteorological records. Geological instability events refer to mine structural instability events caused by changes in the geological environment during or after mining. These data include but are not limited to mine structural parameters (a series of parameters describing the characteristics of mine mining, such as mining depth, mining area, mining method, etc.) and geological environment parameters (a series of parameters describing the geological environment characteristics of the area where the mine is located, such as soil type, groundwater distribution, rainfall, seismic activity, etc.). The collected data is cleaned and sorted to ensure the accuracy and consistency of the data. According to factors such as the severity and impact range of the geological instability event, each event is labeled to form a structured event sample. Integrate the annotated event samples into the mine geological stability event database.

[0028] Step S1322, construct a similarity analysis network and connect it with the mine geological stability event library. Through the similarity analysis network, each adjusted geological environment data set is combined with M mine structure parameter sets, and then the mine structure parameter samples and geological environment samples corresponding to multiple geological instability events are analyzed for similarity, and the mine stability index is generated with the maximum comparison similarity. Specifically, the similarity analysis network can use a neural network model in deep learning, such as a convolutional neural network (CNN) or a recurrent neural network (RNN), to extract features from the geological environment data set and the mine structure parameter set, and calculate their similarity with the samples in the mine geological stability event library. The similarity analysis network is used to extract features from the geological environment data set and the M mine structure parameter sets after each adjustment. The extracted features are calculated for similarity with the samples in the mine geological stability event library, and a measurement method such as cosine similarity and Euclidean distance can be used. According to the similarity calculation result, the geological instability event corresponding to the maximum comparison similarity is selected as a reference, and the current mine geological stability is comprehensively evaluated according to factors such as the severity and impact range of the event, and the mine stability index is generated. This implementation method fully utilizes the information in historical data and improves the accuracy of geological stability analysis by constructing a mine geological stability event database and a similarity analysis network.

[0029] Step S200, extracting the first governance node in the green governance scheme, collecting geological environment data before the node is executed, and generating first initial geological environment data.

[0030] Specifically, geological environment monitoring sensors are deployed at key locations in the mining area, such as seismometers, groundwater level meters, inclinometers, etc. The sensor network collects geological environment data in real time or regularly, such as seismic waves, groundwater levels, surface displacements, etc. The collected data is cleaned and calibrated to generate the first initial geological environment data.

[0031] Step S300: extracting a first environmental geological safety interval from the M environmental geological safety intervals, and determining whether the first initial geological environment data is within the first environmental geological safety interval.

[0032] Specifically, from the M environmental geological safety intervals, according to the specific content and location of the first governance node, the corresponding first environmental geological safety interval is selected. Each indicator in the first initial geological environment data is compared with the corresponding indicator range in the first environmental geological safety interval, and each indicator is checked to see whether it falls within the upper and lower limits of the safety interval through numerical comparison. If all indicators in the first initial geological environment data are within the first environmental geological safety interval, it is considered that the geological environmental conditions in the current mining area are safe, and the next step of operation (ie, step S400) can be continued. If any indicator exceeds the safety interval, a risk assessment is required immediately, and the mining plan needs to be adjusted or additional geological reinforcement measures need to be taken.

[0033] In a possible implementation, step S300 further includes step S310, generating a geological environment monitoring abnormality reminder signal if the first initial geological environment data is not within the first environmental geological safety zone.

[0034] Specifically, when the first initial geological environment data does not meet the requirements of the first environmental geological safety interval, it indicates that there is an abnormality in the current geological environment. The system automatically identifies which geological environment parameters exceed the safety range through built-in algorithms or rules, and determines the type and degree of the abnormality. According to the results of abnormal identification, a corresponding geological environment monitoring abnormality reminder signal is generated, which includes information such as abnormality type, abnormality degree, location of occurrence, and recommended measures. The system sends the abnormal reminder signal to relevant managers or technicians through preset communication channels (such as SMS, email, App push, etc.). At the same time, the abnormal information is also displayed on the monitoring interface of the system so that relevant personnel can view and process it in real time. This implementation method can timely discover potential geological disaster risks by real-time monitoring and comparing geological environment data with safety intervals, provide timely and accurate early warning information for mine management, avoid or reduce the occurrence of geological disasters, and ensure the safety of the mine management process.

[0035] Step S400: If yes, collect the first dynamic meteorological forecast data in the planning execution time zone of the first governance node, perform change analysis on the geological environment parameters, and generate the first dynamic geological environment prediction data.

[0036] Specifically, the dynamic meteorological forecast data in the planned execution time zone of the first governance node is obtained through the meteorological department or third-party meteorological forecast service, such as rainfall, wind speed, wind direction, etc. The geological environment prediction model (such as hydrogeological model, slope stability analysis model, etc.) is used to combine meteorological data and initial geological environment data to predict the changes in geological environment parameters during the execution of the governance node, and output the first dynamic geological environment prediction data, including predicted stratum displacement, groundwater level changes, etc.

[0037] In a possible implementation, the first dynamic meteorological forecast data is collected in the planning execution time zone of the first governance node, and the change analysis of the geological environment parameters is performed to generate the first dynamic geological environment forecast data. Step S400 further includes step S410, determining the mining structure corresponding to the first governance node as a search element, and collecting the first mapping sample data set about meteorological data and geological environment parameters. Specifically, according to the specific information of the first governance node, the corresponding mining structure is determined, and the mining structure is used as a search element. Different mining structures (such as open-pit mining, underground mining, etc.) have different effects on the geological environment. Using data mining algorithms or tools, the mapping samples of meteorological data and geological environment parameters related to the mining structure are retrieved from the historical database. These samples include meteorological data (such as rainfall, temperature, humidity, etc.) at different time points and corresponding geological environment parameters (such as soil moisture, groundwater level, rock formation stability, etc.). The retrieved samples are screened to ensure the accuracy and representativeness of the samples, remove outliers, duplicate values ​​or samples that do not meet the requirements, and integrate the screened samples into the first mapping sample data set.

[0038] Step S420, using the first mapping sample data set to analyze the correlation between meteorological data and geological environment parameters. Specifically, a statistical analysis method (such as Pearson correlation coefficient, Spearman rank correlation coefficient, etc.) or a machine learning algorithm (such as linear regression, decision tree, neural network, etc.) is used to analyze the correlation between meteorological data and geological environment parameters. According to the results of the correlation analysis, a prediction model is constructed to describe the relationship between meteorological data and geological environment parameters. The model is verified by methods such as cross-validation or holdout method to ensure the accuracy and reliability of the model.

[0039] Step S430, analyze the influence of the first dynamic meteorological forecast data on the first initial geological environment data with the related influence relationship, and generate the first dynamic geological environment forecast data. Specifically, the first dynamic meteorological forecast data is input into the constructed prediction model, and the input meteorological data is processed by the prediction model to predict the corresponding geological environment parameter value. The prediction result is superimposed on the first initial geological environment data to obtain the first dynamic geological environment forecast data, which contains the change information of the geological environment parameters in the future. This implementation method can more accurately predict the change trend of the future geological environment by constructing a prediction model and analyzing the correlation between meteorological data and geological environment parameters, thereby improving the accuracy of the analysis of changes in geological environment parameters.

[0040] Step S500, determining whether the first dynamic geological environment prediction data exceeds the first environmental geological safety range, and performing geological environment monitoring reminders during the mine management process.

[0041] Specifically, the first dynamic geological environment prediction data is compared with the first environmental geological safety interval. If the predicted data exceeds the safety interval, a geological environment monitoring reminder is triggered, including sending an early warning message to relevant personnel or systems, suggesting adjustment of the governance plan or taking emergency measures. The embodiment of the present application divides M governance nodes according to the mine governance plan, matches a dynamic geological safety interval for each node, collects real-time geological data when starting the node, verifies whether the node safety interval is met, intercepts substandard working conditions, and after verification, accesses meteorological forecast data during the node construction period to simulate the trend of geological parameter changes. If the predicted data exceeds the current node safety interval, technical means such as graded early warning are immediately triggered, achieving the technical effect of improving the accuracy and timeliness of early warnings.

[0042] like Figure 2 As shown, in a possible implementation, the method further includes step S600, setting a mining pollution leakage monitoring point set in the preset mining area based on the M green governance schemes. Specifically, using GIS technology, according to the mining planning and ecological restoration requirements in the green governance plan, the geological structure, water flow direction, wind direction and other environmental factors of the mining area are analyzed to determine the potential pollution leakage risk points. Professional personnel are organized to conduct on-site surveys to verify the accuracy of GIS analysis, and adjust the location of monitoring points according to the actual situation on site. The survey content includes but is not limited to topography, soil type, vegetation coverage, water source distribution, etc. Pollutant monitoring equipment is installed at the determined monitoring point locations to form a mining pollution leakage monitoring point set. These devices have real-time monitoring, data transmission and alarm functions to ensure timely detection and handling of pollution leakage incidents.

[0043] Step S700, in the planned execution time zone of the first governance node, connect the mining pollution leakage monitoring point set to monitor the pollutant distribution characteristics of pollutants generated by mining, and generate the first pollutant distribution monitoring data. Specifically, connect the equipment of all mining pollution leakage monitoring points to the central monitoring platform to ensure real-time transmission and aggregation of data. Start the monitoring equipment to monitor the pollutants generated during the mining process in real time. The monitoring indicators include but are not limited to heavy metal concentration, organic matter content, suspended matter concentration, etc. Use data analysis technology to process and analyze the real-time monitoring data to extract pollutant distribution characteristic information, including the spatial distribution of pollutants, time change trends, etc.

[0044] Step S800, combining the first pollutant distribution monitoring data with the first dynamic geological environment prediction data to perform a geological environment pollution approaching trend analysis and generate a first pollution approaching trend. Specifically, the first pollutant distribution monitoring data and the first dynamic geological environment prediction data are integrated to form a comprehensive analysis data set. Using spatial analysis technology, the relationship between pollutant distribution and geological environment is analyzed to identify potential pollution diffusion paths and affected areas. Based on historical monitoring data and geological environment parameters, a pollutant diffusion prediction model is constructed, which can simulate the diffusion process of pollutants and predict the concentration distribution of pollutants in the future. Using the prediction model, the integrated data is processed and analyzed to generate the results of the geological environment pollution approaching trend analysis, including information such as the diffusion speed, diffusion range, and degree of impact of pollutants.

[0045] Step S900, based on the first pollution approaching trend, a pollution warning of the geological environment is performed. Specifically, according to the severity and urgency of the geological environment pollution, a warning rule is set, including the triggering conditions, warning levels, and warning measures of the warning signal. The analysis result of the first pollution approaching trend is compared with the warning rule. When the triggering conditions are met, the warning signal is automatically triggered. The warning signal can be prompted in various forms such as sound, light, text message, and email. By using information release technology, the warning information is promptly conveyed to relevant personnel and departments such as mine managers, environmental protection departments, and local residents. The information release channels can include official websites, social media, and text message platforms. According to the warning information, the corresponding emergency plan is activated, and necessary pollution control and governance measures are taken to prevent the spread of pollution and reduce environmental impact. This implementation method can monitor the concentration and distribution characteristics of pollutants generated in the mining process in real time by setting a mining pollution leakage monitoring point set, and analyze the pollution approaching trend in combination with geological environment prediction data and pollutant distribution monitoring data, so as to timely discover potential pollution risks, and timely prompt mine managers and relevant departments to take necessary pollution control and governance measures through the pollution warning system, thereby ensuring the safe production of mines and the sustainable development of the ecological environment.

[0046] In a possible implementation, the first pollutant distribution monitoring data and the first dynamic geological environment prediction data are combined to perform a geological environment pollution approaching trend analysis to generate a first pollution approaching trend, and step S800 further includes step S810, determining the mine environmental pollutants based on the first pollutant distribution monitoring data. Specifically, a preliminary analysis is performed on the first pollutant distribution monitoring data collected from the mining pollution leakage monitoring point set, including cleaning (removing outliers, filling missing values, etc.) and preprocessing (such as data standardization, normalization, etc.) of the monitoring data to ensure data quality. Use technical means such as chemical analysis or spectral analysis to identify specific types of pollutants in the monitoring data, such as heavy metals, harmful chemicals, etc.

[0047] Step S820, using the mine environmental pollutants as search elements, collect historical pollution diffusion data sets, and train the correlation network between pollutant diffusion characteristics and geological environment. Specifically, based on the determined pollutant types, a large amount of historical data on the corresponding pollutant diffusion under different geological environments is extracted from the historical database, including pollutant types, diffusion ranges, durations, and corresponding geological environment parameters. Using these data as training sets, a neural network model is constructed and trained, which can learn the relationship between pollutant diffusion characteristics and geological environment parameters (such as soil type, groundwater flow direction, wind speed, etc.).

[0048] Step S830: Analyze the first pollutant distribution monitoring data and the first dynamic geological environment prediction data with the correlation network to output the diffusion characteristics of the mine environmental pollutants. Specifically, the first pollutant distribution monitoring data and the first dynamic geological environment prediction data are provided as input to the trained neural network model. The model calculates the diffusion characteristics of the pollutants based on the input data, including diffusion speed, direction, range, etc.

[0049] Step S840, generating the first pollution proximity trend based on the diffusion characteristics of the pollutants in the mining environment. Specifically, based on the pollutant diffusion characteristics output in step S830, combined with the spatial distribution information of the geological environment, a map or model representing the pollutant diffusion trend is generated using a geographic information system (GIS) or similar spatial analysis tool. This model can be used to intuitively display the areas to which pollutants may spread in the future, as well as the relative distance and time relationship between these areas and the current location. The generated pollution proximity trend is presented to decision makers in the form of a map, animation or report. This implementation method improves the accuracy of predicting future pollutant diffusion trends by training a neural network model to learn the complex relationship between pollutant diffusion characteristics and the geological environment.

[0050] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for monitoring the geological environment of a mine in a green mine management process, characterized in that: include: Receive M green governance plans corresponding to M governance nodes in a pre-planned green governance plan for a preset mining area, analyze the impact of environmental geological changes on the geological stability of the preset mining area, and establish M environmental geological safety intervals; Extracting the first governance node in the green governance scheme, collecting geological environment data before the node is executed, and generating first initial geological environment data; Extracting a first environmental geological safety interval from the M environmental geological safety intervals, and determining whether the first initial geological environment data is within the first environmental geological safety interval; If yes, first dynamic meteorological forecast data is collected in the planning execution time zone of the first governance node, and the change analysis of geological environment parameters is performed to generate first dynamic geological environment forecast data; Determine whether the first dynamic geological environment prediction data exceeds the first environmental geological safety range, and provide geological environment monitoring reminders during the mine management process; Among them, the impact of environmental geological changes on the geological stability of the preset mining area is analyzed, and M environmental geological safety zones are established, including: Under the first preset stable environmental condition, global geological data collection is performed for the preset mining area before mining to generate a global geological environment data set; Based on the M green governance schemes, mining characteristics of the M governance nodes are modeled to establish M mining structure models; Based on the M mining structure models, with the global geological environment dataset as the center, the global geological environment dataset is adjusted according to a preset adjustment step length, and then the mine geological stability is analyzed to generate the M environmental geological safety intervals.

2. The method for monitoring the geological environment of a mine in a green mine management process according to claim 1, characterized in that: Based on the M mining structure models, with the global geological environment dataset as the center, the global geological environment dataset is adjusted according to a preset adjustment step length, and then the geological stability of the mine is analyzed to generate the M environmental geological safety intervals, including: Extracting mine structure features based on the M mine mining structure models to generate M mine structure parameter sets; Iteratively adjusting the global geological environment dataset for multiple times according to the preset adjustment step length, combining the geological environment dataset after each adjustment with the M mine structure parameter sets to perform mine geological stability analysis, and generating M critical geological environment data with mine stability indicators less than a preset stability threshold; The M environmental geological safety intervals are generated using the M critical geological environment data.

3. The method for monitoring the geological environment of a mine in a green mine management process as claimed in claim 2, characterized in that: Combine each adjusted geological environment data set with M mine structure parameter sets to perform mine geological stability analysis, including: Constructing a mine geological stability event library, wherein the mine geological stability event library contains mine structural parameter samples and geological environment samples corresponding to a plurality of geological instability events; A similarity analysis network is constructed and connected to the mine geological stability event library. Through the similarity analysis network, each adjusted geological environment data set is combined with M mine structure parameter sets respectively, and then similarity analysis is performed on the mine structure parameter samples and geological environment samples corresponding to multiple geological instability events, so as to generate a mine stability index with the maximum comparison similarity.

4. The method for monitoring the geological environment of a mine in a green mine management process according to claim 1, characterized in that: If the first initial geological environment data is not within the first environmental geological safety zone, a geological environment monitoring abnormality reminder signal is generated.

5. The method for monitoring the mine geological environment in the process of green mine management according to claim 1, characterized in that: Collecting first dynamic meteorological forecast data in the planning execution time zone of the first governance node, analyzing the changes of geological environment parameters, and generating first dynamic geological environment forecast data, including: Determine the mining structure corresponding to the first governance node as a search element, and collect a first mapping sample data set about meteorological data and geological environment parameters; Analyzing the relevant influence relationship between meteorological data and geological environment parameters using the first mapping sample data set; The influence of the first dynamic meteorological prediction data on the first initial geological environment data is analyzed based on the relevant influence relationship to generate the first dynamic geological environment prediction data.

6. The method for monitoring the geological environment of a mine in a green mine management process according to claim 1, characterized in that: Also includes: Based on the M green governance schemes, a mining pollution leakage monitoring point set is set in the preset mining area; Connecting the mining pollution leakage monitoring point set in the planning execution time zone of the first governance node to monitor the pollutant distribution characteristics of pollutants generated by mining, and generating first pollutant distribution monitoring data; Combining the first pollutant distribution monitoring data with the first dynamic geological environment prediction data, performing a geological environment pollution approaching trend analysis to generate a first pollution approaching trend; Based on the first pollution approaching trend, a pollution warning of the geological environment is carried out.

7. A method for monitoring the geological environment of a mine in a green mine management process as claimed in claim 6, characterized in that: Combining the first pollutant distribution monitoring data with the first dynamic geological environment prediction data to perform geological environment pollution imminent trend analysis to generate a first pollution imminent trend, including: Determining mine environmental pollutants based on the first pollutant distribution monitoring data; Using the mine environmental pollutants as search elements, collecting historical pollution diffusion data sets, and training a correlation network between pollutant diffusion characteristics and geological environment; Analyzing the first pollutant distribution monitoring data and the first dynamic geological environment prediction data using the correlation network to output diffusion characteristics of mine environmental pollutants; The first pollution proximity trend is generated based on the diffusion characteristics of the mine environmental pollutants.

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