A method and system for tracing the source of heavy metal pollutants in mining areas

Abstract

This invention discloses a method and system for tracing the source of heavy metal pollutants in mining areas, relating to the field of pollutant tracing technology. It solves the technical problem that existing methods for tracing the source of heavy metals can lead to discrepancies between the propagation and diffusion rates of heavy metals in different media and the propagation media of historical pollution events, resulting in inaccurate predictions of the pollution source location. This invention acquires pollution data of the contaminated area in the mining area; determines the type of pollution source based on the pollution data; analyzes the diffusion rate of the pollution source based on the type of pollution source and the pollution data; determines the pollution source area based on the diffusion rate; and predicts the pollution diffusion range based on the pollution source area to obtain the predicted pollution area. This method enables the determination of the pollution source area based on the diffusion rate of the pollution source, avoiding the problem of different diffusion rates in different media and improving the accuracy of the pollution source area analysis results.

Description

Technical Field

[0001] This invention belongs to the field of pollutant traceability and relates to the technology for tracing the source of heavy metal pollutants in mining areas, specifically a method and system for tracing the source of heavy metal pollutants in mining areas. Background Technology

[0002] Heavy metal pollutants are released from ores containing heavy metals during mining, crushing, and beneficiation processes through dust, wastewater, and waste residue. Tracing the sources, migration pathways, and release processes of heavy metal pollutants in mining areas is crucial. Source tracing analysis can identify recyclable heavy metals in tailings or wastewater, promoting resource reuse and reducing the total amount of heavy metals entering the environment, thus decreasing emissions. Therefore, tracing the sources of heavy metal pollutants in mining areas is of great significance for environmental protection, pollution control, and sustainable development.

[0003] Current methods for tracing the source of heavy metal pollutants involve multi-level, in-depth sampling in different regions and testing the heavy metal concentrations in the collected samples. Based on the test data, combined with climate data and historical pollution events, models are used to infer the location of the pollution source. However, heavy metals spread and diffuse at different rates in different media. Analyzing based on historical pollution events may result in the propagation media of historical pollution events differing from the propagation media of the current pollution source, leading to deviations in the inferred location of the pollution source.

[0004] This invention provides a method and system for tracing the source of heavy metal pollutants in mining areas to solve the above-mentioned technical problems. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a method and system for tracing the source of heavy metal pollutants in mining areas, which is used to solve the technical problem that the propagation and diffusion speed of heavy metals in different media is different. Based on the analysis of historical pollution events, the propagation medium of historical pollution events may be different from the propagation medium of the pollution source at present, resulting in the deviation of the prediction results of the pollution source location.

[0006] To achieve the above objectives, a first aspect of the present invention provides a method for tracing the source of heavy metal pollutants in mining areas, comprising:

[0007] Obtain pollution data for contaminated areas within the mining zone;

[0008] Determine the type of pollution source based on pollution data from the polluted area;

[0009] The diffusion rate of pollution sources is analyzed based on their type and pollution data.

[0010] Determine the pollution source area based on the diffusion rate;

[0011] Predict the extent of pollution spread based on the pollution source area.

[0012] Preferably, determining the type of pollution source based on pollution data of the polluted area includes:

[0013] Retrieve pollution data from the contaminated area; the pollution data includes: types of heavy metals, heavy metal content, and detection time.

[0014] Obtain a heavy metal pollution database; match the heavy metal types in the pollution data with the heavy metal pollution database to obtain several corresponding candidate types; determine the scope of heavy metal pollution sources and the mining area types within the scope, and select the corresponding pollution source type from several candidate types based on the mining area type.

[0015] This invention determines the type of heavy metal contamination in a contaminated area based on pollution data, and matches the corresponding heavy metal type with the type of ore to obtain several candidate types. Based on the type of mining area within the defined range, the candidate types are screened to obtain the corresponding pollution source type. This enables the analysis of pollution sources in the contaminated area and lays the foundation for subsequent determination of pollution source areas.

[0016] Preferably, the analysis of the diffusion rate of the pollution source based on the type of pollution source and pollution data includes:

[0017] Retrieve the corresponding pollution source type to obtain the pollution transmission database; match the pollution source type with the pollution transmission database to obtain the corresponding transmission speed;

[0018] The process involves retrieving heavy metal content and detection time from pollution data; integrating heavy metal content, detection time, and propagation speed into a boundary analysis sequence; calling the boundary analysis model and inputting the boundary analysis sequence into the model to obtain the boundary distance after a set time period; the boundary analysis model is constructed based on an artificial intelligence model.

[0019] The detection area is defined based on the boundary distance, and the heavy metal content in the detection area is monitored in real time. The propagation distance of the pollution source is corrected based on the detection results to obtain the corresponding diffusion rate.

[0020] This invention determines the propagation speed of a pollution source based on its type, analyzes the boundary distance after a set time period based on the propagation speed, delineates the detection area based on the boundary distance, and performs real-time detection of the heavy metal content in the detection area. It can correct the propagation speed of the pollution source based on the actual detection time to obtain the diffusion speed. Since the propagation of pollutants is affected by the medium, correcting the propagation speed of the pollution source based on the actual detection results helps to make the detection results more accurate.

[0021] Preferably, the boundary analysis model is constructed based on an artificial intelligence model, including:

[0022] Select a suitable model and deep learning framework from the artificial intelligence model; build the model based on the selected model and deep learning framework to obtain the trained model;

[0023] Obtain the standard dataset; the standard dataset includes: standard input data consistent with the content attributes of the boundary analysis sequence; and standard output data consistent with the content attributes of the boundary distance.

[0024] The standard dataset is divided into a training set, a validation set, and a test set according to a set ratio. The training set is used to train the training model. The validation set is used to adjust the internal parameters of the training model. The test set is used to test the trained model and obtain the test index. When the test index is greater than the index threshold, the training model is marked as a boundary analysis model. Otherwise, the boundary model is rebuilt and trained.

[0025] It should be noted that the division ratio and metric thresholds of the standard dataset are set by experts. The test metrics include: accuracy, F1 score, recall, and stability. When retraining the boundary model, you can either reselect the model and deep learning framework to build and train the training model, or redefine the proportion of the standard dataset and retrain the training model.

[0026] Preferably, the step of correcting the propagation distance of the pollution source based on the detection results includes:

[0027] Retrieve test results from several testing areas; the test results include: testing time and heavy metal content;

[0028] The difference between the detection time in the detection results and the detection time in the pollution data is calculated to obtain the propagation time of the pollution source; the propagation speed of the corresponding pollution source is calculated through the boundary distance and the logical relationship between propagation time and diffusion speed.

[0029] Preferably, determining the pollution source area based on the diffusion rate includes:

[0030] Retrieve boundary distances and heavy metal contents; construct a heavy metal content attenuation model; obtain the diffusion distances and initial heavy metal contents of several corresponding mining area types from the polluted area;

[0031] The theoretical heavy metal content within the polluted area is calculated based on the initial heavy metal content and diffusion distance; the difference between the theoretical heavy metal content and the heavy metal content in the pollution data is calculated; and the mining area type corresponding to the theoretical heavy metal content with the smallest difference is taken as the pollution source area.

[0032] This invention analyzes data from several mining areas, constructs a decay model for heavy metal content, and analyzes the theoretical heavy metal content in polluted areas based on the decay model. It then selects the area with the smallest difference between the actual and theoretical heavy metal content as the pollution source area. This allows for the determination of pollution source areas based on actual conditions, which helps improve the accuracy of pollution source tracing.

[0033] Preferably, the method for constructing the attenuation model of heavy metal content includes:

[0034] The decay model for heavy metal content is constructed as follows: C2 = C1e -kr Where C2 represents the heavy metal content in the test results; C1 represents the heavy metal content in the pollution data; k represents the attenuation coefficient; and r represents the boundary distance.

[0035] Retrieve the boundary distance, pollution data, and heavy metal content from the test results; substitute the boundary distance, pollution data, and heavy metal content from the test results into the attenuation model to obtain the corresponding attenuation coefficient.

[0036] Preferably, the prediction of the pollution diffusion range based on the pollution source area includes:

[0037] Obtain the initial heavy metal content of the pollution source area; obtain the heavy metal content standard; and use formula C. B =C0e -kL The pollution distance from the pollution source is calculated; the predicted pollution area of ​​the pollution source is divided with the pollution source area as the center and the pollution distance as the radius.

[0038] Among them, C B The standard for representing heavy metal content is as follows: C0 represents the initial heavy metal content, L represents the diffusion distance, and k represents the attenuation coefficient.

[0039] The diffusion rate of the pollution source is retrieved; a diffusion convection model is constructed based on the diffusion rate; the diffusion time is predicted based on the diffusion convection model; and a dynamic flow map of pollution is generated using drawing software based on the predicted time and the predicted pollution area.

[0040] This invention calculates the pollution distance of a pollution source based on the initial heavy metal content of the pollution source area; divides the pollution area of ​​the pollution source according to the pollution distance to obtain the predicted pollution area; constructs a diffusion convection model and calculates the predicted time of the pollution source based on the diffusion convection model; and generates a dynamic pollution flow map using drawing software, which can predict the propagation path of the pollution source. Technicians can use the predicted data to intervene in the propagation and diffusion of the pollution source, which is beneficial to avoid serious pollution and damage to the ecological environment and harm to human health.

[0041] Preferably, the method of constructing the diffusion convection model includes:

[0042] The expression for constructing the diffusion convection model is: Where D represents the diffusion coefficient, v represents the diffusion velocity, and k represents the attenuation coefficient; obtain the release time of the pollution source area; calculate the difference between the detection time and the release time of the pollution area to obtain the diffusion time;

[0043] The diffusion distance between the pollution source area and the pollution area is retrieved, and the diffusion distance is used as x in the diffusion convection model, and the diffusion time is used as t in the diffusion convection model; the diffusion coefficient D in the diffusion convection model is calculated.

[0044] A second aspect of the present invention provides a source tracing system for heavy metal pollutants in mining areas, comprising: a source tracing analysis module, and a data acquisition module and a pollution prediction module connected thereto;

[0045] The data acquisition module is used to acquire pollution data from polluted areas in the mining area;

[0046] The source tracing analysis module is used to determine the type of pollution source based on pollution data of the polluted area; analyze the diffusion rate of the pollution source based on the type of pollution source and pollution data; and determine the pollution source area based on the diffusion rate.

[0047] The pollution prediction module is used to predict the extent of pollution spread based on the pollution source area, and to obtain the predicted pollution area.

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] 1. This invention determines the type of heavy metal contamination in a polluted area based on pollution data, and matches the corresponding heavy metal type with the type of ore to obtain several candidate types. It then filters these candidate types based on the mining area type within a defined range to obtain the corresponding pollution source type. This allows for analysis of the pollution sources in the polluted area, laying a foundation for subsequent determination of the pollution source region. Furthermore, it determines the propagation speed of the pollution source based on its type, analyzes the boundary distance after a set time period based on the propagation speed, delineates the detection area based on the boundary distance, and performs real-time detection of the heavy metal content within the detection area. The invention also allows for correction of the pollution source propagation speed based on the actual detection time to obtain the diffusion speed. Since the propagation of pollutants is affected by the medium, correcting the pollution source propagation speed based on the actual detection results lays the foundation for subsequent determination of the pollution source region and helps to make the detection results more accurate.

[0050] 2. This invention analyzes data from several mining areas, constructs a heavy metal content attenuation model, and analyzes the theoretical heavy metal content in polluted areas based on the attenuation model. The area with the smallest difference between the actual and theoretical heavy metal content is selected as the pollution source area. This allows for the determination of pollution source areas based on actual conditions, improving the accuracy of pollution source tracing. The pollution distance is calculated based on the initial heavy metal content of the pollution source area. The pollution area is divided according to the pollution distance to obtain the predicted pollution area. A diffusion convection model is constructed, and the predicted time of the pollution source is calculated based on this model. A dynamic pollution flow map is generated using drawing software, enabling the prediction of the pollution source's propagation path. Technicians can use the predicted data to intervene in the spread and diffusion of pollution sources, helping to prevent severe pollution and damage to the ecological environment and harm to human health. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a schematic diagram of the overall steps of the method of the present invention;

[0053] Figure 2 This is a schematic diagram illustrating the steps for calculating the diffusion rate in this invention;

[0054] Figure 3 This is a schematic diagram illustrating the steps for determining the pollution source area and predicting pollution in this invention.

[0055] Figure 4 This is a schematic diagram of the system model steps of the present invention. Detailed Implementation

[0056] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Please see Figure 1 The first aspect of this invention provides a method for tracing the source of heavy metal pollutants in a mining area, comprising:

[0058] Obtain pollution data for contaminated areas within the mining zone;

[0059] Determine the type of pollution source based on pollution data from the polluted area;

[0060] The diffusion rate of pollution sources is analyzed based on their type and pollution data.

[0061] Determine the pollution source area based on the diffusion rate;

[0062] Predict the extent of pollution spread based on the pollution source area.

[0063] Please see Figure 2 The process involves: acquiring pollution data of contaminated mining areas; retrieving pollution data from contaminated areas, including heavy metal types, heavy metal content, and detection time; obtaining a heavy metal pollution database; matching the heavy metal types in the pollution data with the heavy metal pollution database to obtain several candidate types; determining the scope of heavy metal pollution sources and the mining area types within the determined scope; and selecting the corresponding pollution source type from several candidate types based on the mining area type.

[0064] It should be noted that the scope of heavy metal pollution sources is determined manually based on historical experience; the heavy metal pollution database is constructed based on historical data and is updated when new matching types appear.

[0065] For example: Suppose pollution data for a polluted area is obtained, containing two heavy metals, heavy metal 1 and heavy metal 2. Heavy metal 1 and heavy metal 2 are matched with a heavy metal pollution database, and the ore types corresponding to heavy metal 1 are found to be ore A and C, and the ore types corresponding to heavy metal 2 are found to be ore D and J. The ore types within the range are determined to be A, C and J. Then the pollution source types are A, C and J.

[0066] The process involves retrieving the corresponding pollution source type and obtaining a pollution propagation database; matching the pollution source type with the pollution propagation database to obtain the corresponding propagation speed; retrieving the heavy metal content and detection time from the pollution data; integrating the heavy metal content, detection time, and propagation speed into a boundary analysis sequence; calling the boundary analysis model and inputting the boundary analysis sequence into the boundary analysis model to obtain the boundary distance after a set time period; wherein, the boundary analysis model is constructed based on an artificial intelligence model; delineating the detection area based on the boundary distance, and performing real-time detection of the heavy metal content in the detection area.

[0067] Retrieve detection results from several detection areas; the detection results include: detection time and heavy metal content; calculate the difference between the detection time in the detection results and the detection time in the pollution data to obtain the propagation time of the pollution source; calculate the diffusion rate of the corresponding pollution source through the boundary distance and the logical relationship between propagation time and diffusion rate, and obtain the corresponding diffusion rate.

[0068] 1 100 200 0.5 2 80 100 0.8 …… …… …… ……

[0069] Table 1: Schematic diagram of heavy metal diffusion rate

[0070] For example: The diffusion rate of the corresponding heavy metal can be calculated based on the boundary distance and the propagation time. The calculation formula is: diffusion rate = boundary distance / propagation time. According to Table 1, the diffusion rate of heavy metal 1 in the polluted area is 0.5, and the diffusion rate of heavy metal 2 is 0.8.

[0071] It is worth noting that the boundary analysis model is built upon an artificial intelligence model, including:

[0072] Select a suitable model and deep learning framework from the artificial intelligence model; build the model based on the selected model and deep learning framework to obtain the trained model;

[0073] Obtain the standard dataset; the standard dataset includes: standard input data consistent with the content attributes of the boundary analysis sequence; and standard output data consistent with the content attributes of the boundary distance.

[0074] The standard dataset is divided into a training set, a validation set, and a test set according to a set ratio. The training set is used to train the training model. The validation set is used to adjust the internal parameters of the training model. The test set is used to test the trained model and obtain the test index. When the test index is greater than the index threshold, the training model is marked as a boundary analysis model. Otherwise, the boundary model is rebuilt and trained.

[0075] It should be noted that the division ratio and metric thresholds of the standard dataset are set by experts. The test metrics include: accuracy, F1 score, recall, and stability. When retraining the boundary model, you can either reselect the model and deep learning framework to build and train the training model, or redefine the proportion of the standard dataset and retrain the training model.

[0076] Please see Figure 3 We retrieve the boundary distance and heavy metal content; the attenuation model of heavy metal content is constructed as: C2 = C1e -kr Where C2 represents the heavy metal content in the test results; C1 represents the heavy metal content in the pollution data; k represents the attenuation coefficient; and r represents the boundary distance. The boundary distance, pollution data, and heavy metal content in the test results are retrieved. The boundary distance, pollution data, and heavy metal content in the test results are substituted into the attenuation model to obtain the corresponding attenuation coefficient.

[0077] Obtain the diffusion distance and initial heavy metal content of several corresponding mining area types from the polluted area; calculate the theoretical heavy metal content within the polluted area based on the initial heavy metal content and diffusion distance; calculate the difference between the theoretical heavy metal content and the heavy metal content in the pollution data; and take the mining area type corresponding to the theoretical heavy metal content with the smallest difference as the pollution source area.

[0078] For example: Suppose we analyze the pollution source area of ​​heavy metal 1 in the polluted area, and the distances between mine type A and mine type C and the polluted area are R1 and R2, respectively; obtain the initial heavy metal content of mine type A and mine type C, and calculate the theoretical heavy metal 1 content of the polluted area based on the initial heavy metal content, which are 120 and 80, respectively; the actual detected heavy metal 1 content in the polluted area is 117; then mine type A is taken as the pollution source area.

[0079] Obtain the initial heavy metal content of the pollution source area; obtain the heavy metal content standard; and use formula C. B =C0e -kL The pollution distance from the pollution source is calculated; the predicted pollution area is divided with the pollution source area as the center and the pollution distance as the radius; where C B The standard for representing heavy metal content is as follows: C0 represents the initial heavy metal content, L represents the diffusion distance, and k represents the attenuation coefficient. The diffusion velocity of the pollution source is retrieved. A diffusion convection model is constructed based on the diffusion velocity. The diffusion time is predicted based on the diffusion convection model. A dynamic flow map of pollution is generated using drawing software based on the predicted time and the predicted pollution area.

[0080] It should be noted that using drawing software to create a dynamic flow map of pollution in a contaminated area can visually represent the direction of pollutant flow, which is beneficial for relevant personnel to understand the flow direction of pollution sources in a timely manner when carrying out pollution control. Drawing software includes ParaView, Python Ecosystem Tools, or VisIt, etc. When selecting drawing software, the appropriate drawing software should be selected according to the transmission medium of the pollution source. When there are multiple transmission media, one can choose the corresponding drawing software to draw the dynamic flow map of pollution for the corresponding medium, or a drawing software that is compatible with both can be selected to draw the dynamic flow map of pollution.

[0081] It is worth noting that the methods for constructing diffusion convection models include:

[0082] The expression for constructing the diffusion convection model is: Where D represents the diffusion coefficient, v represents the diffusion velocity, and k represents the attenuation coefficient; obtain the release time of the pollution source area; calculate the difference between the detection time and the release time of the pollution area to obtain the diffusion time;

[0083] The diffusion distance between the pollution source area and the pollution area is retrieved, and the diffusion distance is used as x in the diffusion convection model, and the diffusion time is used as t in the diffusion convection model; the diffusion coefficient D in the diffusion convection model is calculated.

[0084] Please see Figure 4 A second aspect of the present invention provides a source tracing system for heavy metal pollutants in mining areas, comprising: a source tracing analysis module, and a data acquisition module and a pollution prediction module connected thereto;

[0085] The data acquisition module is used to acquire pollution data from polluted areas in the mining area;

[0086] The source tracing analysis module is used to determine the type of pollution source based on pollution data of the polluted area; analyze the diffusion rate of the pollution source based on the type of pollution source and pollution data; and determine the pollution source area based on the diffusion rate.

[0087] The pollution prediction module is used to predict the extent of pollution spread based on the pollution source area, and to obtain the predicted pollution area.

[0088] Some of the data in the above formula are calculated by removing dimensions and taking their numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0089] The working principle of this invention is as follows: This invention acquires pollution data of the contaminated area in the mining area; determines the type of pollution source based on the pollution data of the contaminated area; analyzes the diffusion rate of the pollution source based on the type of pollution source and the pollution data; determines the pollution source area based on the diffusion rate; and predicts the pollution diffusion range based on the pollution source area to obtain the predicted pollution area.

[0090] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for tracing the source of heavy metal pollutants in mining areas, characterized in that, include: Obtain pollution data for contaminated areas within the mining zone; Determine the type of pollution source based on pollution data from the polluted area; The diffusion rate of pollution sources is analyzed based on their type and pollution data. Determine the pollution source area based on the diffusion rate; Predict the extent of pollution spread based on the pollution source area; The analysis of the diffusion rate of pollution sources based on the type of pollution source and pollution data includes: Retrieve the corresponding pollution source type to obtain the pollution transmission database; match the pollution source type with the pollution transmission database to obtain the corresponding transmission speed; The process involves retrieving heavy metal content and detection time from pollution data; integrating heavy metal content, detection time, and propagation speed into a boundary analysis sequence; calling the boundary analysis model and inputting the boundary analysis sequence into the model to obtain the boundary distance after a set time period; the boundary analysis model is constructed based on an artificial intelligence model. The detection area is defined based on the boundary distance, and the heavy metal content in the detection area is detected in real time. The propagation distance of the pollution source is corrected based on the detection results to obtain the corresponding diffusion rate. The determination of the pollution source area based on the diffusion rate includes: Retrieve boundary distances and heavy metal contents; construct a heavy metal content attenuation model; obtain the diffusion distances and initial heavy metal contents of several corresponding mining area types from the polluted area; Based on the attenuation model, the theoretical heavy metal content in the polluted area is calculated based on the initial heavy metal content and the diffusion distance; the difference between the theoretical heavy metal content and the heavy metal content in the pollution data is calculated; and the mining area type corresponding to the theoretical heavy metal content with the smallest difference is taken as the pollution source area. The method for constructing the attenuation model of heavy metal content includes: The decay model for heavy metal content is constructed as follows: Where C2 represents the heavy metal content in the real-time detection results; C1 represents the heavy metal content in the pollution data; k represents the attenuation coefficient; and r represents the boundary distance. Retrieve the boundary distance, pollution data, and heavy metal content from real-time detection results; substitute the boundary distance, pollution data, and heavy metal content from real-time detection results into the attenuation model to obtain the corresponding attenuation coefficient.

2. The method for tracing the source of heavy metal pollutants in a mining area according to claim 1, characterized in that, The process of determining the type of pollution source based on pollution data from the polluted area includes: Retrieve pollution data from the contaminated area; the pollution data includes: types of heavy metals, heavy metal content, and detection time. Obtain a heavy metal pollution database; match the heavy metal types in the pollution data with the heavy metal pollution database to obtain several corresponding candidate types; determine the scope of heavy metal pollution sources and the mining area types within the scope, and select the corresponding pollution source type from several candidate types based on the mining area type.

3. The method for tracing the source of heavy metal pollutants in a mining area according to claim 1, characterized in that, The boundary analysis model is constructed based on an artificial intelligence model and includes: Select a suitable model and deep learning framework from the artificial intelligence model; build the model based on the selected model and deep learning framework to obtain the trained model; Obtain the standard dataset; the standard dataset includes: standard input data consistent with the content attributes of the boundary analysis sequence; and standard output data consistent with the content attributes of the boundary distance. The standard dataset is divided into a training set, a validation set, and a test set according to a set ratio. The training set is used to train the training model. The validation set is used to adjust the internal parameters of the training model. The test set is used to test the trained model and obtain the test index. When the test index is greater than the index threshold, the training model is marked as a boundary analysis model. Otherwise, the boundary model is rebuilt and trained.

4. The method for tracing the source of heavy metal pollutants in a mining area according to claim 1, characterized in that, The correction of the pollution source's propagation distance based on the detection results includes: Retrieve test results from several testing areas; the test results include: testing time and heavy metal content; The difference between the detection time in the detection results and the detection time in the pollution data is calculated to obtain the propagation time of the pollution source; the propagation speed of the corresponding pollution source is calculated through the boundary distance and the logical relationship between propagation time and diffusion speed.

5. The method for tracing the source of heavy metal pollutants in a mining area according to claim 1, characterized in that, The prediction of pollution diffusion range based on pollution source area includes: Obtain the initial heavy metal content of the pollution source area; obtain the heavy metal content standard; and use the formula... The pollution distance from the pollution source is calculated; the predicted pollution area of ​​the pollution source is divided with the pollution source area as the center and the pollution distance as the radius. Among them, C B The standard for representing heavy metal content is as follows: C0 represents the initial heavy metal content, L represents the diffusion distance, and k represents the attenuation coefficient. The diffusion rate of the pollution source is retrieved; a diffusion convection model is constructed based on the diffusion rate; the diffusion time is predicted based on the diffusion convection model; and a dynamic flow map of pollution is generated using drawing software based on the predicted time and the predicted pollution area.

6. The method for tracing the source of heavy metal pollutants in a mining area according to claim 5, characterized in that, The methods for constructing the diffusion convection model include: The expression for constructing the diffusion convection model is: ;in, Let v represent the diffusion coefficient, v represent the diffusion velocity, and k represent the attenuation coefficient; obtain the release time of the pollution source area; calculate the difference between the detection time and the release time of the pollution area to obtain the diffusion time; The diffusion distance between the pollution source area and the pollution area is retrieved, and the diffusion distance is used as x in the diffusion convection model, and the diffusion time is used as t in the diffusion convection model; the diffusion coefficient D in the diffusion convection model is calculated.

7. A source tracing system for heavy metal pollutants in mining areas, applied to the source tracing method for heavy metal pollutants in mining areas as described in any one of claims 1-6, characterized in that, include: The source tracing analysis module, and the connected data acquisition module and pollution prediction module; The data acquisition module is used to acquire pollution data from polluted areas in the mining area; The source tracing analysis module is used to determine the type of pollution source based on pollution data of the polluted area. Based on the type of pollution source and the analysis of pollution data, the diffusion rate of the pollution source is determined; the pollution source area is determined based on the diffusion rate. The pollution prediction module is used to predict the pollution diffusion range based on the pollution source area, and obtain the predicted pollution area; The analysis of the diffusion rate of pollution sources based on the type of pollution source and pollution data includes: Retrieve the corresponding pollution source type to obtain the pollution transmission database; match the pollution source type with the pollution transmission database to obtain the corresponding transmission speed; The process involves retrieving heavy metal content and detection time from pollution data; integrating heavy metal content, detection time, and propagation speed into a boundary analysis sequence; calling the boundary analysis model and inputting the boundary analysis sequence into the model to obtain the boundary distance after a set time period; the boundary analysis model is constructed based on an artificial intelligence model. The detection area is defined based on the boundary distance, and the heavy metal content in the detection area is detected in real time. The propagation distance of the pollution source is corrected based on the detection results to obtain the corresponding diffusion rate. The determination of the pollution source area based on the diffusion rate includes: Retrieve boundary distances and heavy metal contents; construct a heavy metal content attenuation model; obtain the diffusion distances and initial heavy metal contents of several corresponding mining area types from the polluted area; Based on the attenuation model, the theoretical heavy metal content in the polluted area is calculated based on the initial heavy metal content and the diffusion distance; the difference between the theoretical heavy metal content and the heavy metal content in the pollution data is calculated; and the mining area type corresponding to the theoretical heavy metal content with the smallest difference is taken as the pollution source area. The method for constructing the attenuation model of heavy metal content includes: The decay model for heavy metal content is constructed as follows: Where C2 represents the heavy metal content in the real-time detection results; C1 represents the heavy metal content in the pollution data; k represents the attenuation coefficient; and r represents the boundary distance. Retrieve the boundary distance, pollution data, and heavy metal content from real-time detection results; substitute the boundary distance, pollution data, and heavy metal content from real-time detection results into the attenuation model to obtain the corresponding attenuation coefficient.

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