Mining area heavy metal pollutant risk early warning system and method

Abstract

The invention discloses a risk early warning system and method for heavy metal pollutants in a mining area, relates to the technical field of mine pollution early warning, and solves the technical problem that an existing heavy metal pollutant early warning system is low in efficiency when analyzing mineral heavy metal pollutants. Acquiring pollution data corresponding to each heavy metal pollutant in the mining area and a plurality of geological feature data on each set diffusion path; based on the pollution data and the geological characteristic data of the heavy metal pollutants, generating an initial diffusion rate of the corresponding heavy metal; acquiring a plurality of historical environment data of the mining area within a set time, and generating the heavy metal remaining amount of each area based on the historical environment data and the initial diffusion rate; generating an early warning report based on the heavy metal remaining amount; and the mining area heavy metal early warning efficiency is improved.

Description

Technical Field

[0001] The present application belongs to the field of mine pollution early warning technology, and specifically relates to a mining area heavy metal pollutant risk early warning system and method. Background Art

[0002] Mine environmental issues refer to the study of the pollution and damage to the environment caused by mining activities, such as the destruction of existing topography, landforms, and geological structures. Mine pollution not only damages the ecological environment but also seriously threatens human health and the sustainable development of the socio-economic system.

[0003] Existing mining area heavy metal analysis and early warning systems often set up several sampling points, analyze the soil at the sampling points, determine whether there are heavy metal pollutants, and issue early warnings. This method requires a lot of manpower and material resources, and the final effect is difficult to fully reflect the distribution of heavy metal pollutants in the area around the mining area; making the early warning of heavy metal pollutants in the mining area based on this method inefficient; therefore, a mining area heavy metal pollutant risk early warning system and method are needed. Summary of the Invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes a mining area heavy metal pollutant risk warning system and method, which is used to solve the technical problem that the existing heavy metal pollutant warning system has low efficiency when analyzing mineral heavy metal pollutants.

[0005] To achieve the above objectives, the first aspect of the present application provides a method for early warning of heavy metal pollutant risks in mining areas, comprising:

[0006] Obtain pollution data corresponding to each heavy metal pollutant in the mining area; as well as several geological characteristic data on each set diffusion path;

[0007] Generate preliminary diffusion rates of corresponding heavy metals based on pollution data of heavy metal pollutants and geological characteristics data;

[0008] Obtain some historical environmental data of the mining area within the set time, generate the heavy metal retention in each area based on the historical environmental data and the preliminary diffusion rate; and generate an early warning report based on the heavy metal retention.

[0009] The present application obtains pollution data corresponding to each heavy metal pollutant in the mining area; and a number of geological characteristic data on each set diffusion path; generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristic data of the heavy metal pollutants; obtains a number of historical environmental data of the mining area within a set time, and generates the heavy metal retention in each area based on the historical environmental data and the preliminary diffusion rate; generates an early warning report based on the heavy metal retention; analyzes the characteristics of each heavy metal pollutant, and at the same time analyzes the impact of the soil in each area on the diffusion of heavy metals, and then estimates the heavy metals in each area based on the diffusion environment and time, and generates corresponding alarm signals according to the estimation results; achieves a comprehensive analysis of the area around the mining area, and improves the efficiency of heavy metal early warning in the mining area.

[0010] Preferably, generating a preliminary diffusion rate of a corresponding heavy metal based on pollution data of heavy metal pollutants and geological characteristic data includes:

[0011] Extracting pollution source concentrations and pollutant characteristic data corresponding to each pollutant type in the pollution data; inputting the pollutant characteristic data into the stability evaluation model to obtain a stability score for the heavy metal pollutant; and generating a diffusion capacity coefficient for evaluating the diffusion capacity of the corresponding heavy metal based on the pollution source concentrations and stability scores corresponding to each pollutant type;

[0012] Extract the distribution area, content of soil adhesives and porosity from the geological characteristic data of each region, and generate the diffusion resistance coefficient based on the distribution area, content of soil adhesives and porosity of each region;

[0013] The difference between the diffusion capacity coefficient and the diffusion resistance coefficient is recorded as the diffusion rate coefficient of the corresponding area, and the product of the diffusion rate coefficient and the set unit diffusion rate is recorded as the initial diffusion rate of the heavy metal in the corresponding area.

[0014] Preferably, the stability evaluation model is obtained through artificial intelligence model training, including:

[0015] Obtain a number of pollutant characteristic data and their corresponding stability scores through a database. The pollutant characteristic data are the forms of the corresponding heavy metal pollutants, such as ionic state, molecular state, complex and precipitate, and related parameters affecting their stability, such as boiling point and ionic strength; the stability score is an expert's score of the ability of the heavy metal pollutants to exist in nature based on the relevant parameters of the heavy metal pollutants in the pollutant characteristics. For example, the higher the boiling point, the higher the stability of the corresponding heavy metal pollutant, the higher the stability score is set, and the weaker the diffusion ability under the same environmental conditions; for example, if the compound form is ionic and easily soluble in water, the lower the corresponding stability is, the lower the stability score is set, and the stronger the diffusion ability under the same environmental conditions; integrate the several pollutant characteristic data and stability scores into a number of training data and test data;

[0016] The artificial intelligence model is trained using training data, and the trained artificial intelligence model is tested using test data; ultimately, a stability evaluation model is obtained whose input is pollutant characteristic data and whose output is a stability score; wherein, the artificial intelligence model includes a BP neural network model and an RBF neural network model.

[0017] Preferably, the generating of the corresponding heavy metal diffusion capacity coefficient based on the pollution source concentration and stability score corresponding to each pollutant type includes:

[0018] Obtain the stability score and pollution source concentration of each heavy metal pollutant; substitute the stability score and pollution source concentration into the set diffusion capacity quantification function to obtain the diffusion capacity coefficient of the corresponding heavy metal pollutant;

[0019] The diffusion capacity coefficients of the heavy metal pollutants are summed to obtain the diffusion capacity coefficients of the corresponding heavy metals.

[0020] Preferably, generating the diffusion resistance coefficient based on the distribution area, content of adhesion material and porosity of each region includes:

[0021] Substituting the porosity and adhesion content of each region into a set quantification function to obtain a quantitative value of its impact on the diffusion of heavy metal pollutants; the adhesion material includes organic matter in the soil, such as humus; clay minerals, such as montmorillonite, illite, and kaolinite; and metal oxides or hydroxides such as iron, aluminum, and manganese in the soil;

[0022] The diffusion resistance coefficient used to represent the influence of the area on the diffusion of heavy metal pollutants is generated based on the product of the quantitative value and the distribution area;

[0023] The diffusion resistance coefficient of each area on each set diffusion path is obtained in turn.

[0024] Preferably, the set diffusion path is a line segment of a set length in a set direction with the heavy metal pollution source as the starting point; a sector is made with the center of the heavy metal pollution source and the set diffusion path as one side, and the set diffusion path is divided into several regional segments at equal distances, and the sector is divided based on the regional segments to obtain regions.

[0025] Preferably, generating the heavy metal retention amount based on historical environmental data and preliminary diffusion rate comprises:

[0026] Extract the temperature and humidity values corresponding to each time period in the historical data, and adjust each preliminary diffusion rate based on the temperature and humidity values to obtain a corrected diffusion rate under the corresponding environmental conditions;

[0027] The heavy metal retention amount of the time period is generated based on the product of the corrected diffusion rate and the duration of the corresponding time period; the heavy metal retention amount of each time period in the same area is summed up to obtain the heavy metal retention amount of the corresponding area.

[0028] Preferably, adjusting each preliminary diffusion rate based on the temperature value and the humidity value to obtain the modified diffusion rate comprises:

[0029] Obtain the concentration of heavy metal pollutants and the corresponding preliminary diffusion rate of each area, as well as the distance between the center of each area and the heavy metal pollution source; based on the concentration of heavy metal pollutants and distance, find the corresponding attenuation factor in the attenuation factor search standard;

[0030] The preliminary diffusion rate was corrected based on the attenuation factor to obtain the theoretical diffusion rate that was affected by the distance from the heavy metal pollutant source.

[0031] The theoretical diffusion rate is corrected based on the temperature and humidity values to obtain the corrected diffusion rate for the corresponding area under the corresponding environmental conditions.

[0032] Preferably, generating the heavy metal retention amount in a time period based on the product of the corrected diffusion rate and the duration of the corresponding time period includes:

[0033] Obtaining the modified diffusion rate for each area and each time period on the set diffusion path; recording the product of the modified diffusion rate and the length of the corresponding time period as the heavy metal diffusion amount of the area in the time period;

[0034] Obtain the heavy metal diffusion amount in each area and time period in turn;

[0035] Obtain the heavy metal diffusion amounts of the target area and the area above the target area, and mark the heavy metal diffusion amount of the above area as the heavy metal transfer amount; record the difference between the heavy metal transfer amount and the heavy metal diffusion amount as the heavy metal retention amount of the target area in the corresponding time period.

[0036] Preferably, generating an early warning report based on the heavy metal retention amount includes:

[0037] Obtain the heavy metal retention amount in each area and determine whether the heavy metal retention amount in each area is greater than the set heavy metal content threshold; if yes, mark the area as a heavily polluted area; if not, mark the area as a lightly polluted area.

[0038] Another aspect of the present application provides a mining area heavy metal pollutant risk early warning system, comprising: a data acquisition module, a data analysis model, an interactive display module and a database;

[0039] The data acquisition module acquires pollution data and geological characteristic data through a data acquisition device connected thereto; the pollution data includes several types of pollutants, their corresponding pollution source concentrations, and pollutant characteristic data; the geological characteristic data includes distribution area, content of adhesive substances in the soil, and porosity;

[0040] The data analysis module generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristics of the heavy metal pollutants; obtains a certain amount of historical environmental data of the mining area within a set time through a database connected to it, and generates the heavy metal retention amount of each area based on the historical environmental data and the preliminary diffusion rate; and generates an early warning report based on the heavy metal retention amount;

[0041] Interactive display module: obtain early warning reports and display early warning reports.

[0042] Compared with the prior art, the present invention has the following advantages:

[0043] 1. This application obtains pollution data corresponding to each heavy metal pollutant in the mining area; as well as several geological characteristic data on each set diffusion path; generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristic data of the heavy metal pollutants; obtains several historical environmental data of the mining area within a set time, and generates the heavy metal retention in each area based on the historical environmental data and the preliminary diffusion rate; generates an early warning report based on the heavy metal retention; analyzes the characteristics of each heavy metal pollutant, and at the same time analyzes the impact of the soil in each area on the diffusion of heavy metals, and then estimates the heavy metals in each area based on the diffusion environment and time, and generates corresponding alarm signals according to the estimation results; realizes a comprehensive analysis of the area around the mining area, and improves the efficiency of heavy metal early warning in the mining area.

[0044] 2. This application analyzes each heavy metal pollutant and then conducts a comprehensive analysis of the pollution diffusion of heavy metals to make the analysis results more accurate.

[0045] 3. This application significantly improves early warning efficiency and reduces errors caused by manual intervention and subjective judgment through automated and intelligent analysis methods.

[0046] 4. This application generates early warning reports and visualization support, enabling environmental management departments to promptly identify pollution risks, take targeted measures to prevent the spread and harm of heavy metal pollutants, and improve the overall level and effectiveness of environmental management. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0048] Figure 1 This is a schematic diagram of the steps of the risk warning method in this application;

[0049] Figure 2 This is a schematic diagram of the module connection of the risk warning system in this application. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions of this application in conjunction with the embodiments. Obviously, the embodiments described are only a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0051] See also Figure 1 The first aspect of the present application provides a method for early warning of heavy metal pollutant risks in mining areas, comprising:

[0052] Obtain pollution data corresponding to each heavy metal pollutant in the mining area. Different mining areas have different resources, so the corresponding heavy metal pollutants are also different. According to the type of resources mined in the mining area, the type of heavy metal pollutants corresponding to it can be obtained; as well as a number of geological characteristic data on each set diffusion path; the set diffusion path is a line segment of a set length in a set direction with the heavy metal pollution source as the starting point; with the center of the heavy metal pollution source and the set diffusion path as one side, the set diffusion path is divided into a number of regional segments at equal distances, and the sector is divided into regions based on the regional segments; the geological characteristic data is relevant data of the soil in the corresponding region, including the distribution area, the content of adhesive substances in the soil, and the porosity;

[0053] Generate a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristics of heavy metal pollutants; the preliminary diffusion rate is a theoretical diffusion rate based on theoretical analysis of the influence of the characteristics of heavy metal pollutants and the geological characteristics of the diffusion area on the diffusion of heavy metal pollutants;

[0054] Obtain some historical environmental data of the mining area within the set time, and generate the heavy metal retention in each area based on the historical environmental data and the preliminary diffusion rate; the heavy metal retention is the estimated retention of heavy metals in each area after being affected by the environment and diffusion; and generate an early warning report based on the heavy metal retention.

[0055] This embodiment obtains pollution data corresponding to each heavy metal pollutant in the mining area; and a number of geological characteristic data on each set diffusion path; generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristic data of the heavy metal pollutants; obtains a number of historical environmental data of the mining area within a set time, and generates the heavy metal retention amount of each area based on the historical environmental data and the preliminary diffusion rate; generates an early warning report based on the heavy metal retention amount; analyzes the characteristics of each heavy metal pollutant, and at the same time analyzes the impact of the soil in each area on the diffusion of heavy metals, and then estimates the heavy metals in each area based on the diffusion environment and time, and generates corresponding alarm signals according to the estimation results; achieves a comprehensive analysis of the area around the mining area, and improves the efficiency of heavy metal early warning in the mining area.

[0056] Generate preliminary diffusion rates of heavy metals based on pollution data and geological characteristics of heavy metal pollutants, including:

[0057] Extract the types of pollutants in the pollution data. Since one heavy metal may correspond to multiple heavy metal pollutants, and the characteristics of each heavy metal pollutant are different, this embodiment will perform differentiated analysis on different heavy metal pollutants belonging to the same heavy metal to improve the accuracy of the final analysis; the pollution type is a certain pollutant compound or ion corresponding to the heavy metal; the corresponding pollution source concentration and pollutant characteristic data; the pollution source concentration can be understood as the pollutant concentration at the source of the pollutant such as the mine entrance or waste storage area; the pollutant characteristic data is input into the stability evaluation model to obtain the stability score of the heavy metal pollutant, and the diffusion capacity coefficient for evaluating the diffusion capacity of the corresponding heavy metal is generated based on the pollution source concentration and stability score corresponding to each pollutant type; the diffusion capacity coefficient is the total diffusion capacity of each pollutant corresponding to the heavy metal. When the diffusion capacity coefficient is larger, it means that the ability of the heavy metal to diffuse with its various pollutants is stronger;

[0058] The distribution area, soil adhesion content, and porosity of the geological characteristics data of each region were extracted, and the diffusion resistance coefficient was generated based on the distribution area, adhesion content, and porosity of each region. The diffusion resistance coefficient is the resistance of the soil to the diffusion of heavy metals. The larger the diffusion resistance coefficient, the greater the influence of the soil in the corresponding area on the diffusion of heavy metals, the slower the diffusion rate of heavy metals in the area, and the greater the potential for heavy metal retention.

[0059] The difference between the diffusion capacity coefficient and the diffusion resistance coefficient is recorded as the diffusion rate coefficient of the corresponding area, and the product of the diffusion rate coefficient and the set unit diffusion rate is recorded as the preliminary diffusion rate of the heavy metal in the corresponding area. It can be understood that in this embodiment, by setting the values of the various parameters in different quantization functions, the diffusion capacity coefficient and the diffusion resistance coefficient are within the same range, and quantitative calculation can be performed. At the same time, by setting the unit diffusion rate, the difference between the diffusion capacity coefficient and the diffusion resistance coefficient is converted into a preliminary diffusion rate.

[0060] This embodiment conducts a comprehensive analysis of each heavy metal based on the characteristics of the heavy metal itself and the characteristics of its propagation medium, so that the propagation of the heavy metal can be accurately grasped.

[0061] The stability evaluation model is obtained through artificial intelligence model training, including: obtaining a number of pollutant characteristic data and their corresponding stability scores through a database, wherein the pollutant characteristic data are the forms of the corresponding heavy metal pollutants, such as ionic state, molecular state, complex and precipitate, boiling point and ionic strength and other related parameters affecting their stability; the stability score is an expert's score of the ability of heavy metal pollutants to exist in nature based on the relevant parameters of the heavy metal pollutants in the pollutant characteristics, for example, the higher the boiling point, the higher the stability of the corresponding heavy metal pollutant, the higher the stability score is set, and the weaker the diffusion ability under the same environmental conditions; for example, if the compound form is ionic and easily soluble in water, the corresponding stability is lower, the lower the stability score is set, and the stronger the diffusion ability under the same environmental conditions; integrating a number of pollutant characteristic data and stability scores into a number of training data and test data;

[0062] The artificial intelligence model is trained using training data, and the trained artificial intelligence model is tested using test data; specifically, the pollutant characteristic data in the test data is input into the trained artificial intelligence model to obtain an output stability score, and it is determined whether the difference between the stability score and the stability score recorded in the corresponding test data is less than a set threshold. If so, it means that the group of test data has passed the test and the next group of test data is tested; if not, the group of test data is retested; finally, after a set proportion of test data has passed the test, a stability evaluation model is obtained with the pollutant characteristic data as input and the stability score as output; wherein, the artificial intelligence model includes a BP neural network model and an RBF neural network model.

[0063] Generating the corresponding heavy metal diffusion capacity coefficient based on the pollution source concentration and stability score corresponding to each pollutant type, including: obtaining the stability score and pollution source concentration of each heavy metal pollutant; substituting the stability score and pollution source concentration into the set diffusion capacity quantification function to obtain the corresponding heavy metal pollutant diffusion capacity coefficient; summing the diffusion capacity coefficients of each heavy metal pollutant to obtain the corresponding heavy metal diffusion capacity coefficient;

[0064] Among them, the diffusion capacity quantification function is:

[0065] KN=H(WN,WP)

[0066] Wherein, KN is the diffusion capacity coefficient, H() is the set diffusion capacity quantification function, WN is the pollution source concentration, and WP is the stability score. H() includes at least two sub-functions, one of which is used to quantify the impact of the pollution source on the diffusion capacity, and this sub-function is an increasing function; the other is used to quantify the impact of the stability score on the diffusion capacity, and this sub-function is a decreasing function. The diffusion capacity quantification function in this embodiment is:

[0067]

[0068] Among them, DWN is the set unit pollution source concentration, which is used to remove the dimension of the pollution source concentration. δ1 is the set adjustment coefficient one. The specific value is set according to expert experience and can be used to limit the range of the influence of the pollution source concentration on the diffusion capacity coefficient in conjunction with the unit pollution source concentration. DWP is the set unit stability score. δ2 is the set adjustment coefficient two. The specific value is set according to expert experience and can be used to limit the range of the influence of the stability score on the diffusion capacity coefficient in conjunction with the unit stability score.

[0069] This embodiment quantifies the influence of the properties of heavy metal pollutants on the diffusion of pollutants by setting a diffusion capacity quantification function; when the concentration of the pollution source is greater, the diffusion driving force of the corresponding pollutant is greater, and the corresponding diffusion capacity coefficient is greater; when the properties of the pollutant are more unstable, the diffusion capacity is stronger, such as pollutants that are easily volatile or easily soluble, which diffuse with the air or water flow, so the corresponding diffusion capacity coefficient is set to be larger; since the same heavy metal may have multiple heavy metal pollutants of different properties, different heavy metal pollutants have different properties; this embodiment analyzes each heavy metal pollutant and then conducts a comprehensive analysis of the pollution diffusion of the heavy metal, so that the analysis results are more accurate.

[0070] Generating a diffusion resistance coefficient based on the distribution area, content of adhesion material, and porosity of each region includes: substituting the porosity and content of adhesion material of each region into a set quantization function to obtain a quantitative value of its effect on the diffusion of heavy metal pollutants; the adhesion material includes organic matter in the soil, such as humus; clay minerals, such as montmorillonite, illite, and kaolinite; and the sum of the content of metal oxides or hydroxides such as iron, aluminum, and manganese in the soil;

[0071] The diffusion resistance coefficient used to represent the influence of the area on the diffusion of heavy metal pollutants is generated based on the product of the quantitative value and the distribution area;

[0072] The diffusion resistance coefficient of each area on each set diffusion path is obtained in turn.

[0073] Specifically, the porosity and the content of the corresponding adhesion substances in each region are marked as KXD and XFN, respectively; the distribution area is marked as FM;

[0074] The corresponding diffusion resistance coefficient KS is calculated by the formula KS = FM × [L (KXD) + M (XFN)];

[0075] Wherein, L() is the quantization function corresponding to the porosity, and M() is the quantization function corresponding to the adhesion material content; since the greater the adhesion material content in the soil, the greater the possibility of heavy metal pollutants being adsorbed when diffusing in the soil, the greater the diffusion resistance, and the larger the corresponding quantization value; the quantization value is positively correlated with the corresponding adhesion material content, so the quantization function M() in this embodiment is an increasing function; when the porosity of the soil is greater, the speed at which the corresponding soil spreads heavy metal pollutants is faster, the corresponding diffusion resistance is smaller, and the quantization value is smaller; the quantization value is negatively correlated with the corresponding soil porosity, so the quantization function L() in this embodiment is a decreasing function; specifically, in one embodiment, the quantization function M(XFN)=ε1×e XFN; Among them, ε1 is the adjustment coefficient, the specific value is set according to expert experience, and is used to adjust the influence of the adhesion material content on the diffusion resistance; L(KXD)=ε2×e -KXD ; Among them, ε2 is the adjustment coefficient, the specific value of which is set according to expert experience and is used to adjust the impact of soil porosity on diffusion resistance; at the same time, ε1 and ε2 also play the function of removing units.

[0076] The heavy metal inventory is generated based on historical environmental data and preliminary diffusion rates; including:

[0077] Extract the temperature and humidity values corresponding to each time period in the historical data, and adjust each preliminary diffusion rate based on the temperature and humidity values to obtain the corrected diffusion rate under the corresponding environmental conditions; specifically, obtain the heavy metal pollutant concentration and the preliminary diffusion rate corresponding to each area, as well as the distance between the center of each area and the heavy metal pollution source; obtain the corresponding attenuation factor based on the attenuation factor search standard based on the heavy metal pollutant concentration and distance; the attenuation factor lookup table is obtained in the following way: experts use the theoretically constructed diffusion model of each heavy metal pollutant under the set environment to obtain the ratio of the diffusion rate of the heavy metal pollutant source at different distances to the diffusion rate at the heavy metal pollutant source, and record it as the attenuation factor at the corresponding distance; integrate the heavy metal pollutant source and its attenuation factors at different distances into an attenuation factor lookup table; Susou sets the environment to the same temperature, humidity and soil environment;

[0078] The preliminary diffusion rate is corrected based on the attenuation factor to obtain the theoretical diffusion rate affected by the distance from the heavy metal pollutant source; the theoretical diffusion rate is corrected based on the temperature and humidity values to obtain the corrected diffusion rate for the corresponding area under the corresponding environmental conditions; specifically, through the formula The corresponding corrected diffusion rate XS is calculated; among them, WD is the temperature value of the corresponding area, DWD is the set unit temperature; SD is the humidity value of the corresponding area, DSD is the set unit humidity; LS is the theoretical diffusion rate; ε and δ are the adjustment factors for the influence of temperature and humidity on the diffusion rate of heavy metals, respectively, and the specific values are set according to expert experience; when the temperature rises, the molecular motion will become more active, and the corresponding diffusion rate will increase; when the humidity increases, the water content in the soil increases, which is conducive to the diffusion of substances. At the same time, there is a certain probability that pollutants in the air will settle into the soil, which will increase the pollutant content in the soil and further increase the diffusion rate.

[0079] Generating the heavy metal retention amount of the time period based on the product of the modified diffusion rate and the duration of the corresponding time period; including: obtaining the modified diffusion rate of each area and each time period on the set diffusion path; recording the product of the modified diffusion rate and the duration of the corresponding time period as the heavy metal diffusion amount of the area in the time period;

[0080] Obtain the heavy metal diffusion amount in each area and time period in turn;

[0081] Obtain the heavy metal diffusion amount of the target area and the area above the target area, and mark the heavy metal diffusion amount of the above area as the heavy metal transfer amount; record the difference between the heavy metal transfer amount and the heavy metal diffusion amount as the heavy metal retention amount of the target area in the corresponding time period;

[0082] The heavy metal retention in each time period of the same area is summed up to obtain the heavy metal retention in the corresponding area.

[0083] Generate an early warning report based on the heavy metal retention amount, including: obtaining the heavy metal retention amount in each area, and judging whether the heavy metal retention amount in each area is greater than the set heavy metal content threshold; if yes, mark the area as a heavily polluted area; if not, mark the area as a lightly polluted area.

[0084] See also Figure 2 , another aspect of the present application provides a mining area heavy metal pollutant risk early warning system, comprising: a data acquisition module, a data analysis model, an interactive display module and a database;

[0085] The data acquisition module acquires pollution data and geological characteristic data through a data acquisition device connected thereto; the pollution data includes several types of pollutants, their corresponding pollution source concentrations, and pollutant characteristic data; the geological characteristic data includes distribution area, content of adhesive substances in the soil, and porosity;

[0086] The data analysis module generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristics of the heavy metal pollutants; obtains a certain amount of historical environmental data of the mining area within a set time through a database connected to it, and generates the heavy metal retention amount of each area based on the historical environmental data and the preliminary diffusion rate; and generates an early warning report based on the heavy metal retention amount;

[0087] Interactive display module: obtain early warning reports and display early warning reports.

[0088] Some of the data in the above formula are calculated by removing the dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0089] How this application works:

[0090] The present application obtains pollution data corresponding to each heavy metal pollutant in the mining area; and a number of geological characteristic data on each set diffusion path; generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristic data of the heavy metal pollutants; obtains a number of historical environmental data of the mining area within a set time, and generates the heavy metal retention in each area based on the historical environmental data and the preliminary diffusion rate; generates an early warning report based on the heavy metal retention; analyzes the characteristics of each heavy metal pollutant, and at the same time analyzes the impact of the soil in each area on the diffusion of heavy metals, and then estimates the heavy metals in each area based on the diffusion environment and time, and generates corresponding alarm signals according to the estimation results; thereby improving the efficiency of heavy metal early warning in mining areas.

[0091] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. A method for early warning of heavy metal pollutant risks in mining areas, characterized in that: include: Obtain pollution data corresponding to each heavy metal pollutant in the mining area; and several geological characteristic data on each assumed diffusion path; Generate preliminary diffusion rates of corresponding heavy metals based on pollution data of heavy metal pollutants and geological characteristics data; Obtain some historical environmental data of the mining area within a set time, and generate the heavy metal retention in each area based on the historical environmental data and preliminary diffusion rate; Generate early warning reports based on heavy metal retention.

2. A mining area heavy metal pollutant risk early warning method according to claim 1, characterized in that: Generate preliminary diffusion rates of heavy metals based on pollution data and geological characteristics of heavy metal pollutants, including: Extracting pollution source concentrations and pollutant characteristic data corresponding to each pollutant type in the pollution data; inputting the pollutant characteristic data into the stability evaluation model to obtain a stability score for the heavy metal pollutant; and generating a diffusion capacity coefficient for evaluating the diffusion capacity of the corresponding heavy metal based on the pollution source concentrations and stability scores corresponding to each pollutant type; Extract the distribution area, content of soil adhesives and porosity from the geological characteristic data of each region, and generate the diffusion resistance coefficient based on the distribution area, content of soil adhesives and porosity of each region; The difference between the diffusion capacity coefficient and the diffusion resistance coefficient is recorded as the diffusion rate coefficient of the corresponding area, and the product of the diffusion rate coefficient and the set unit diffusion rate is recorded as the initial diffusion rate of the heavy metal in the corresponding area.

3. A mining area heavy metal pollutant risk early warning method according to claim 2, characterized in that: The stability evaluation model is obtained through artificial intelligence model training, including: Acquire a number of pollutant characteristic data and their corresponding stability scores from a database, and integrate the pollutant characteristic data and stability scores into a number of training data and test data; The artificial intelligence model is trained using training data, and the trained artificial intelligence model is tested using test data; ultimately, a stability evaluation model is obtained whose input is pollutant characteristic data and whose output is a stability score; wherein, the artificial intelligence model includes a BP neural network model and an RBF neural network model.

4. A mining area heavy metal pollutant risk early warning method according to claim 2, characterized in that: The method of generating the corresponding heavy metal diffusion capacity coefficient based on the pollution source concentration and stability score corresponding to each pollutant type includes: Obtain the stability score and pollution source concentration of each heavy metal pollutant; substitute the stability score and pollution source concentration into the set diffusion capacity quantification function to obtain the diffusion capacity coefficient of the corresponding heavy metal pollutant; The diffusion capacity coefficients of the heavy metal pollutants are summed to obtain the diffusion capacity coefficients of the corresponding heavy metals.

5. The method for early warning of heavy metal pollutant risk in mining areas according to claim 1, characterized in that: The diffusion resistance coefficient is generated based on the distribution area, content of adhesion material and porosity of each region, including: Substituting the porosity and adhesion content of each area into the set quantification function to obtain the quantitative value of its influence on the diffusion of heavy metal pollutants, the diffusion resistance coefficient representing the influence of the area on the diffusion of heavy metal pollutants is generated based on the product of the quantitative value and the distribution area; The diffusion resistance coefficient of each area on each set diffusion path is obtained in turn.

6. A mining area heavy metal pollutant risk early warning method according to claim 1, characterized in that: The heavy metal inventory is generated based on historical environmental data and preliminary diffusion rates; including: Extract the temperature and humidity values corresponding to each time period in the historical data, and adjust each preliminary diffusion rate based on the temperature and humidity values to obtain a corrected diffusion rate under the corresponding environmental conditions; The heavy metal retention amount of the time period is generated based on the product of the corrected diffusion rate and the duration of the corresponding time period; the heavy metal retention amount of each time period in the same area is summed up to obtain the heavy metal retention amount of the corresponding area.

7. A mining area heavy metal pollutant risk early warning method according to claim 6, characterized in that: Adjusting each preliminary diffusion rate based on the temperature value and the humidity value to obtain the modified diffusion rate includes: Obtain the concentration of heavy metal pollutants and the corresponding preliminary diffusion rate of each area, as well as the distance between the center of each area and the heavy metal pollution source; based on the concentration of heavy metal pollutants and distance, find the corresponding attenuation factor in the attenuation factor search standard; The preliminary diffusion rate was corrected based on the attenuation factor to obtain the theoretical diffusion rate that was affected by the distance from the heavy metal pollutant source. The theoretical diffusion rate is corrected based on the temperature and humidity values to obtain the corrected diffusion rate for the corresponding area under the corresponding environmental conditions.

8. A mining area heavy metal pollutant risk early warning method according to claim 6, characterized in that: The heavy metal retention amount in the corresponding period is generated based on the product of the modified diffusion rate and the duration of the corresponding period, including: Obtaining the modified diffusion rate for each area and each time period on the set diffusion path; recording the product of the modified diffusion rate and the length of the corresponding time period as the heavy metal diffusion amount of the area in the time period; Obtain the heavy metal diffusion amount in each area and time period in turn; Obtain the heavy metal diffusion amounts of the target area and the area above the target area, and mark the heavy metal diffusion amount of the above area as the heavy metal transfer amount; record the difference between the heavy metal transfer amount and the heavy metal diffusion amount as the heavy metal retention amount of the target area in the corresponding time period.

9. The method for early warning of heavy metal pollutant risk in mining areas according to claim 1, characterized in that: The generation of an early warning report based on the heavy metal retention amount includes: Obtain the heavy metal retention amount in each area and determine whether the heavy metal retention amount in each area is greater than the set heavy metal content threshold; if yes, mark the area as a heavily polluted area; if not, mark the area as a lightly polluted area.

10. A mining area heavy metal pollutant risk warning system, based on the application of a mining area heavy metal pollutant risk warning method according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, data analysis model, interactive display module and database; The data acquisition module acquires pollution data and geological characteristic data through a data acquisition device connected thereto; the pollution data includes several types of pollutants, their corresponding pollution source concentrations, and pollutant characteristic data; the geological characteristic data includes distribution area, content of adhesive substances in the soil, and porosity; The data analysis module generates a preliminary diffusion rate of the corresponding heavy metal based on the pollution data and geological characteristics of the heavy metal pollutants; obtains a certain amount of historical environmental data of the mining area within a set time through a database connected to it, and generates the heavy metal retention amount of each area based on the historical environmental data and the preliminary diffusion rate; Generate early warning reports based on heavy metal retention; Interactive display module: obtain early warning reports and display early warning reports.

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