Intelligent risk prediction method for ecological utilization of mine water

Abstract

The invention discloses an intelligent risk prediction method for ecological utilization of mine water. The method comprises the following steps: constructing a three-dimensional geological coordinate system based on mine distribution; calculating a pollution degree coefficient of the mine water and a purification degree coefficient of the purified mine water; evaluating the mine water purification effect of the purification equipment, analyzing the water purification capacity of the purification equipment and the quality of mine water discharged by a mine, and constructing an optimal distribution model; and planning to convey the mine water to surrounding purification equipment based on the optimal distribution model, calculating the risk probability of the purified mine water on ecological utilization after distribution is completed, and evaluating the risk of the mine water output by the mine on ecological utilization. The comprehensive utilization mode of replacing surface water and underground water with mine water is optimized and perfected, and the influence of coal mining on ecology and rivers is reduced to the maximum extent. On the basis of the maximum purification capacity of the mine area, prediction of the influence of mine water on ecological utilization is achieved, and an important scientific basis is provided for reasonable utilization of mine water resources and ecological environment protection.

Description

Technical Field

[0001] The present invention relates to the field of mine water ecological utilization, and in particular to a risk intelligent prediction method for mine water ecological utilization. Background Art

[0002] Mine water is a large amount of wastewater generated during coal mining. Its ecological utilization can not only alleviate water shortages but also reduce environmental pollution. However, this ecological utilization of mine water carries various risks, including water pollution, ecological damage, and water resource waste. Furthermore, abandoned mines also transport groundwater to the surface, which can be used for ecological purposes. However, since coal mining damages the geological structure of mines and promotes the release of underground pollutants, mine water must be purified before it can be used ecologically.

[0003] However, the continuous purification of mine water using purification equipment can lead to a decrease in purification capacity due to aging and malfunctioning of the equipment, resulting in the discharged mine water failing to meet the requirements for ecological utilization. Real-time adjustment and allocation of mine water purification capacity within mining development areas and assessment of ecological utilization risks are key to the safe use of mine water. Therefore, an intelligent risk prediction method for the ecological utilization of mine water is urgently needed. Summary of the Invention

[0004] In response to the above-mentioned deficiencies in the prior art, the present invention provides an intelligent risk prediction method for the ecological utilization of mine water, which evaluates the purification capacity of mine water in real time, analyzes and allocates the utilization rate of purification equipment, and analyzes and evaluates the risks of the ecological utilization of mine water on the premise of maximizing the water purification capacity of the mine distribution area.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is: Provided is a risk intelligent prediction method for mine water ecological utilization, which includes: Step S1: According to the distribution of mines in the coal mining area, a three-dimensional geological coordinate system is constructed based on the distribution of mines, and the coordinates of each mine in the three-dimensional geological coordinate system are obtained. , i Number the mine; Step S2: collecting water quality data of mine water discharged from the mine, as well as standard water quality data for ecological use of mine water, calculating the pollution degree coefficient of the mine water, and collecting water quality data of the mine water after being purified by purification equipment, calculating the purification degree coefficient of the purified mine water; Step S3: Calculate the purification capacity decay rate of the purification equipment over time, evaluate the mine water purification effect of the purification equipment, and analyze the water purification capacity of the purification equipment and the quality of the mine water discharged from the mine; Step S4: constructing an optimization allocation model for allocating water sources of mine water with poor quality and malfunctioning purification equipment to surrounding purification equipment with good purification effects; Step S5: Based on the optimization distribution model, plan the delivery of mine water to surrounding purification equipment. After the distribution is completed, calculate the risk probability of the purified mine water on ecological utilization, and evaluate the risk of the mine water output from the mine on ecological utilization.

[0006] Furthermore, step S2 includes: Step S21: Collect water quality data of mine water discharged from the mine within a set historical period , N is the number of types of water quality data, For the N Water quality data, standard water quality data based on mine water ecological use , For the N Standard water quality data to calculate the pollution degree coefficient of mine water w 1; ; in, For the n Water quality data, n Number the types of water quality data; Step S22: Collecting water quality data of mine water discharged from the mine after being purified by purification equipment , calculate the purification degree coefficient of the mine water after purification w 2; ; Step S23: According to the pollution degree coefficient w 1 and the purification degree coefficient w 2Calculate the purification capacity coefficient of the purification equipment installed in each mine , .

[0007] Furthermore, step S3 includes: Step S31: Obtain the purification capacity coefficient data set of the purification equipment over time , T is the usage time of the current purification equipment, For usage time T Calculated purification capacity coefficient; Step S32: Calculating the purification capacity decay rate of the purification equipment over time; ; in, t For the use time of purification equipment, For usage timet Calculated purification capacity coefficient; Step S33: Setting the allowable value of the purification capacity attenuation rate ,like , the purification effect of the mine water of the purification equipment is poor, and the process goes to step S34; otherwise, the purification effect of the mine water of the purification equipment is good, and the process goes back to step S21 to continue monitoring the water quality data of the mine water and the water quality data after purification; Step S34: Calculate usage time T Pollution degree coefficient of discharged mine water ; ; in, For usage time T Water quality coefficient of discharged mine water; Step S35: Based on usage time T The maximum value of the pollution degree coefficient calculated previously , and set the fluctuation threshold allowed for the pollution degree coefficient ,like , then determine the mine i The quality of the mine water output is poor and exceeds the purification capacity of the purification equipment; if , it is judged that the water purification capacity of the purification equipment is reduced and the purification equipment is faulty.

[0008] Furthermore, step S4 includes: Step S41: Get each output mine with poor mine water quality u , and obtain the mine u Coordinates in the 3D geological coordinate system ; and obtain all malfunctioning purification equipment e , and obtain purification equipment e Coordinates in the 3D geological coordinate system ; Step S42: Based on the mine u Coordinates of surrounding mine water purification equipment with good purification effect , v The number of the purification equipment with good mine water purification effect, and based on the purification equipment v The current purification degree coefficient, the construction will be mine u Output mine water and input purification equipment e Optimal distribution model for mine water to surrounding purification equipment, mine u Output mine water and input purification equipment e The source of mine water is recorded as U ; ; in, k To receive water U The purification equipment number, K To receive water U The number of purification equipment, To receive water U Purification equipment k During use time T +1 purification capacity coefficient matrix, For purification equipment k During use time T +1 purification capacity coefficient, To receive water U Purification equipment in use time T The purification capacity coefficient matrix, For purification equipment k During use time T The purification capacity coefficient, For all purification equipment k The coordinate matrix of For output water U All mine coordinates With the coordinate matrix The calculation function of the distance between each coordinate element in is used to calculate the output water source U The mine with coordinate matrix The distances between the purification equipment corresponding to the inner coordinate elements and; is the spatial correlation weight coefficient, A collection of purification equipment with good mine water purification effect, is the fluctuation threshold allowed for the purification capacity coefficient of the purification equipment, It is the transportation distance threshold in the mine water purification process.

[0009] Furthermore, step S5 includes: Step S51: Planning each mine based on the optimization allocation model u Purify equipment around k After the mine is transported and the distribution is completed, the water quality data output by each purification equipment is counted , calculate the risk probability of ecological utilization caused by purified mine water; ; in, G is the risk prediction duration, is the cumulative risk factor, The output of the purification equipment after allocation N Water quality data, Risk prediction duration G The corresponding risk probability; Step S52: Setting the risk probability threshold , evaluate the risk prediction duration G Ecological utilization risks of mine water discharged from mines; like , the discharged mine water will pose a risk to ecological utilization, otherwise, it will not pose a risk.

[0010] The present invention has the following beneficial effects: It analyzes and evaluates the purification capacity of mine water based on real-time purification equipment, comprehensively utilizing the different purification capabilities of each purification device to ensure optimal purification capacity within the mine area. Based on the process of varying mine water quantity and quality, it optimizes and improves the comprehensive utilization model of mine water as a substitute for surface water and groundwater, minimizing the impact of coal mining on the ecology and rivers. Based on the maximum purification capacity of the mine area, it predicts the impact of mine water on ecological utilization, providing an important scientific basis for the rational use of mine water resources and ecological environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 Flowchart of the intelligent risk prediction method for mine water ecological utilization. DETAILED DESCRIPTION

[0012] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0013] This embodiment is implemented based on several mines distributed in the coal mining development area. The mine water discharged from the mines is purified by purification equipment and then discharged into the ecological water supply system for ecological utilization. The purification system is connected to the purification pipeline system. Each mine is matched with a purification equipment. The discharged mine water is directly purified by the purification equipment. Each purification equipment is connected through the purification pipeline system to form a purification network. The distribution of mine water is achieved by the switch valves on the purification pipeline. The mine water purified by the purification equipment is then collected and input into the ecological water supply system.

[0014] Each switch valve, purification equipment and water quality collection sensor group is connected to the processor. A risk intelligent prediction module is built in the processor to execute the risk intelligent prediction method for mine water ecological utilization of this embodiment. The collected water quality data is input into the risk intelligent prediction module.

[0015] like Figure 1 As shown, a risk intelligent prediction method for mine water ecological utilization includes: Step S1: According to the distribution of mines in the coal mining area, a three-dimensional geological coordinate system is constructed based on the distribution of mines, and the coordinates of each mine in the three-dimensional geological coordinate system are obtained. , i Number the mine.

[0016] Step S2: Collect water quality data of mine water discharged from the mine, as well as standard water quality data for ecological use of mine water, calculate the pollution degree coefficient of the mine water, and collect water quality data of the mine water after being purified by purification equipment, and calculate the purification degree coefficient of the purified mine water.

[0017] For example, agricultural irrigation is a key area of ecological utilization for mine water. According to the "Agricultural Irrigation Water Quality Standard" (GB5084-2021), the pH of mine water used for agricultural irrigation must be maintained between 5.5 and 8.5. This is because within this pH range, crop roots are better able to absorb nutrients from the soil. Excessively acidic or alkaline water can hinder nutrient absorption and even damage crop roots. Chemical oxygen demand (COD), a key indicator of organic pollutant levels in water, should not exceed 200 mg / L for wet crops, 300 mg / L for dry crops, and 100 mg / L for vegetables. Excessively high COD indicates the presence of significant amounts of organic pollutants in the water. During irrigation, these pollutants deplete dissolved oxygen in the soil, affecting the normal activity of soil microorganisms and, in turn, negatively impacting crop growth and development. Controlling heavy metal levels is crucial. For example, mercury (Hg) levels must not exceed 0.001 mg / L, cadmium (Cd) levels must not exceed 0.01 mg / L, and lead (Pb) levels must not exceed 0.2 mg / L. Once heavy metals accumulate in the soil, they not only reduce soil fertility but also enter the food chain through crop absorption, posing a serious threat to human health. Furthermore, the suspended matter content in mine water must be strictly controlled, typically below 100 mg / L. Excessive suspended matter can clog soil pores, affecting soil aeration and water permeability, and hindering the respiration and growth of crop roots.

[0018] Water quality requirements for ecological landscape water replenishment: The water quality of mine water used for ecological landscape water replenishment must meet the relevant standards for landscape water bodies. Generally speaking, its turbidity should be controlled below 10NTU to ensure that the water body is clear and transparent to meet people's viewing needs. Excessive turbidity will make the water body appear turbid, affecting the aesthetics of the landscape. The ammonia nitrogen content should not exceed 1.0mg / L, and the total phosphorus content should not exceed 0.2mg / L. Ammonia nitrogen and total phosphorus are the main factors leading to eutrophication of water bodies. If the content exceeds the standard, it is easy to cause excessive reproduction of algae, resulting in hypoxia in the water body, destroying the ecological balance of the ecological landscape water body, and causing adverse phenomena such as algal blooms, which not only affect the landscape effect, but also threaten the survival of aquatic organisms.

[0019] Step S2 specifically includes: Step S21: Collect water quality data of mine water discharged from the mine within a set historical period , N is the number of types of water quality data, For the N Water quality data, standard water quality data based on mine water ecological use , For the N Standard water quality data to calculate the pollution degree coefficient of mine water w 1; ; in, For the n Water quality data, n Number the types of water quality data; Step S22: Collecting water quality data of mine water discharged from the mine after being purified by purification equipment , calculate the purification degree coefficient of the mine water after purification w 2; ; Step S23: According to the pollution degree coefficient w 1 and the purification degree coefficient w 2Calculate the purification capacity coefficient of the purification equipment installed in each mine , .

[0020] Step S3: Calculate the purification capacity decay rate of the purification equipment over time, evaluate the mine water purification effect of the purification equipment, and analyze the water purification capacity of the purification equipment and the quality of the mine water discharged from the mine. Step S3 specifically includes: Step S31: Obtain the purification capacity coefficient data set of the purification equipment over time , T is the usage time of the current purification equipment, For usage time T Calculated purification capacity coefficient; Step S32: Calculating the purification capacity decay rate of the purification equipment over time; ; in, t For the use time of purification equipment, For usage time t Calculated purification capacity coefficient; Step S33: Setting the allowable value of the purification capacity attenuation rate ,like , the purification effect of the mine water of the purification equipment is poor, and the process goes to step S34; otherwise, the purification effect of the mine water of the purification equipment is good, and the process goes back to step S21 to continue monitoring the water quality data of the mine water and the water quality data after purification; Step S34: Calculate usage time T Pollution degree coefficient of discharged mine water ; ; in, For usage time T Water quality coefficient of discharged mine water; Step S35: Based on usage time T The maximum value of the pollution degree coefficient calculated previously , and set the fluctuation threshold allowed for the pollution degree coefficient ,like , then determine the mine i The quality of the mine water output is poor and exceeds the purification capacity of the purification equipment; if , it is judged that the water purification capacity of the purification equipment is reduced and the purification equipment is faulty.

[0021] Sudden changes in the quality of mine water output may be due to the collapse of geological structures under the mine or groundwater pollution. The purification equipment cannot meet the sudden change in water quality, and water needs to be transferred to other purification equipment to reduce the purification load.

[0022] Step S4: Construct an optimization allocation model to allocate the water source of mine water with poor quality and malfunctioning purification equipment to the surrounding purification equipment with good purification effect. Step S4 specifically includes: Step S41: Get each output mine with poor mine water quality u , and obtain the mine u Coordinates in the 3D geological coordinate system ; and obtain all malfunctioning purification equipment e , and obtain purification equipment e Coordinates in the 3D geological coordinate system ; Step S42: Based on the mine u Coordinates of surrounding mine water purification equipment with good purification effect , v The number of the purification equipment with good mine water purification effect, and based on the purification equipment v The current purification degree coefficient, the construction will be mine u Output mine water and input purification equipment e Optimal distribution model for mine water to surrounding purification equipment, mine uOutput mine water and input purification equipment e The source of mine water is recorded as U ; ; in, k To receive water U The purification equipment number, K To receive water U The number of purification equipment, To receive water U Purification equipment k During use time T +1 purification capacity coefficient matrix, For purification equipment k During use time T +1 purification capacity coefficient, To receive water U Purification equipment in use time T The purification capacity coefficient matrix, For purification equipment k During use time T The purification capacity coefficient, For all purification equipment k The coordinate matrix of For output water U All mine coordinates With the coordinate matrix The calculation function of the distance between each coordinate element in is used to calculate the output water source U The mine with coordinate matrix The distances between the purification equipment corresponding to the inner coordinate elements and; is the spatial correlation weight coefficient, A collection of purification equipment with good mine water purification effect, is the fluctuation threshold allowed for the purification capacity coefficient of the purification equipment, It is the transportation distance threshold in the mine water purification process.

[0023] This invention optimizes distribution based on the goals of minimizing the impact of distributed mine water on the purification capacity of surrounding purification equipment and minimizing transportation distance. This effectively improves the overall purification capacity of the mine area while also enhancing the quality of the output mine water. By calculating the difference between the distributed mine water before and after receiving it, the difference between the distributed mine water and the purification equipment is reduced.

[0024] Step S5: Based on the optimization distribution model, plan the delivery of mine water to surrounding purification equipment. After the distribution is completed, calculate the risk probability of the purified mine water to ecological utilization and evaluate the risk of the mine water output to ecological utilization. Step S5 specifically includes: Step S51: Planning each mine based on the optimization allocation model u Purify equipment around k After the mine is transported and the distribution is completed, the water quality data output by each purification equipment is counted , calculate the risk probability of ecological utilization caused by purified mine water; ; in, G is the risk prediction duration, is the cumulative risk factor, The output of the purification equipment after allocation N Water quality data, Risk prediction duration G The corresponding risk probability; The present invention quantifies the risk of purified mine water on ecological utilization based on risk triggering conditions and risk accumulation prediction, obtains risk probability prediction indicators, and realizes the prediction of the impact of mine water on ecological utilization.

[0025] Step S52: Setting the risk probability threshold , evaluate the risk prediction duration G Ecological utilization risks of mine water discharged from mines; like , the discharged mine water will pose a risk to ecological utilization, otherwise, it will not pose a risk.

[0026] This method analyzes and evaluates the purification capacity of mine water using real-time purification equipment, comprehensively utilizing the varying purification capabilities of each device to ensure optimal purification capacity within the mine area. Based on the heterogeneity of mine water quantity and quality, it optimizes and improves the comprehensive utilization model of mine water as a substitute for surface water and groundwater, minimizing the impact of coal mining on the ecology and rivers. Based on the maximum purification capacity of the mine area, it predicts the ecological impact of mine water, providing an important scientific basis for the rational use of mine water resources and ecological protection.

Claims

1. A risk intelligent prediction method for mine water ecological utilization, characterized in that: include: Step S1: constructing a three-dimensional geological coordinate system based on the distribution of mines in the coal mining area, and obtaining the coordinates of each mine in the three-dimensional geological coordinate system; Step S2: collecting water quality data of mine water discharged from the mine, as well as standard water quality data for ecological use of mine water, calculating the pollution degree coefficient of the mine water, and collecting water quality data of the mine water after being purified by purification equipment, calculating the purification degree coefficient of the purified mine water; Step S3: Calculate the purification capacity decay rate of the purification equipment over time, evaluate the mine water purification effect of the purification equipment, and analyze the water purification capacity of the purification equipment and the quality of the mine water discharged from the mine; Step S4: constructing an optimization allocation model for allocating water sources of mine water with poor quality and malfunctioning purification equipment to surrounding purification equipment with good purification effects; Step S5: Based on the optimization distribution model, plan the delivery of mine water to surrounding purification equipment. After the distribution is completed, calculate the risk probability of the purified mine water on ecological utilization, and evaluate the risk of the mine water output from the mine on ecological utilization.

2. The risk intelligent prediction method for mine water ecological utilization according to claim 1 is characterized in that: The step S2 comprises: Step S21: Collect water quality data of mine water discharged from the mine within a set historical period , N is the number of types of water quality data, For the N Water quality data, standard water quality data based on mine water ecological use , For the N Standard water quality data to calculate the pollution degree coefficient of mine water w 1; ； in, For the n Water quality data, n Number the types of water quality data; Step S22: Collecting water quality data of mine water discharged from the mine after being purified by purification equipment , calculate the purification degree coefficient of the mine water after purification w 2; ； Step S23: According to the pollution degree coefficient w 1 and the purification degree coefficient w 2Calculate the purification capacity coefficient of the purification equipment installed in each mine , .

3. The risk intelligent prediction method for mine water ecological utilization according to claim 2 is characterized in that: The step S3 comprises: Step S31: Obtain the purification capacity coefficient data set of the purification equipment over time , T is the usage time of the current purification equipment, For usage time T Calculated purification capacity coefficient; Step S32: Calculating the purification capacity decay rate of the purification equipment over time; ； in, t For the use time of purification equipment, For usage time t Calculated purification capacity coefficient; Step S33: Setting the allowable value of the purification capacity attenuation rate ,like , the purification effect of the mine water of the purification equipment is poor, and the process goes to step S34; otherwise, the purification effect of the mine water of the purification equipment is good, and the process goes back to step S21 to continue monitoring the water quality data of the mine water and the water quality data after purification; Step S34: Calculate usage time T Pollution degree coefficient of discharged mine water ; ； in, For usage time T Water quality coefficient of discharged mine water; Step S35: Based on usage time T The maximum value of the pollution degree coefficient calculated previously , and set the fluctuation threshold allowed for the pollution degree coefficient ,like , then determine the mine i The quality of the mine water output is poor and exceeds the purification capacity of the purification equipment; if , it is judged that the water purification capacity of the purification equipment is reduced and the purification equipment is faulty.

4. The risk intelligent prediction method for mine water ecological utilization according to claim 3 is characterized in that: The step S4 comprises: Step S41: Get each output mine with poor mine water quality u , and obtain the mine u Coordinates in the 3D geological coordinate system ; and obtain all malfunctioning purification equipment e , and obtain purification equipment e Coordinates in the 3D geological coordinate system ; Step S42: Based on the mine u Coordinates of surrounding mine water purification equipment with good purification effect , v The number of the purification equipment with good mine water purification effect, and based on the purification equipment v The current purification degree coefficient, the construction will be mine u Output mine water and input purification equipment e Optimal distribution model for mine water to surrounding purification equipment, mine u Output mine water and input purification equipment e The source of mine water is recorded as U ; ； in, k To receive water U The purification equipment number, K To receive water U The number of purification equipment, To receive water U Purification equipment k During use time T +1 purification capacity coefficient matrix, For purification equipment k During use time T +1 purification capacity coefficient, To receive water U Purification equipment in use time T The purification capacity coefficient matrix, For purification equipment k During use time T The purification capacity coefficient, For all purification equipment k The coordinate matrix of For output water U All mine coordinates With the coordinate matrix The calculation function of the distance between each coordinate element in is used to calculate the output water source U The mine with coordinate matrix The distances between the purification equipment corresponding to the inner coordinate elements and; is the spatial correlation weight coefficient, A collection of purification equipment with good mine water purification effect, is the fluctuation threshold allowed for the purification capacity coefficient of the purification equipment, It is the transportation distance threshold in the mine water purification process.

5. The intelligent risk prediction method for mine water ecological utilization according to claim 4 is characterized in that: The step S5 comprises: Step S51: Planning each mine based on the optimization allocation model u Purify equipment around k After the mine is transported and the distribution is completed, the water quality data output by each purification equipment is counted , calculate the risk probability of ecological utilization caused by purified mine water; ； in, G is the risk prediction duration, is the cumulative risk factor, The output of the purification equipment after allocation N Water quality data, Risk prediction duration G The corresponding risk probability; Step S52: Setting the risk probability threshold , evaluate the risk prediction duration G Ecological utilization risks of mine water discharged from mines; like , the discharged mine water will pose a risk to ecological utilization, otherwise, it will not pose a risk.

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