Intelligent control system and method for mine water underground treatment, medium and electronic equipment

Abstract

The invention relates to an intelligent control system and method for mine water underground treatment, a medium and electronic equipment.The system comprises a water quality online monitoring module, an automatic control module, an intelligent chemical adding module and a calibration optimization module, and the system responds to mine water quality changes in real time based on mine water quality online monitoring data and a chemical adding prediction model; the agent adding strategy is dynamically adjusted, accurate agent adding is achieved, the mine water underground treatment effect is effectively improved, the operation and maintenance cost of an underground treatment system is reduced, and the reliability is improved. The control system disclosed by the invention has relatively high automation and intelligence levels, can adapt to complex water quality conditions and large-scale mine water treatment requirements, provides an efficient, economic and environment-friendly solution for mine area water resource management, and has a wide application prospect.

Description

Technical Field

[0001] The present disclosure relates to an intelligent control system, method, medium and electronic device for underground treatment of mine water. Background Art

[0002] Mine water is a by-product water generated during coal mining, usually containing a large amount of suspended solids (including particulate impurities such as coal powder and rock powder) and hardness ions (mainly calcium and magnesium ions), and needs to be treated before being discharged or reused. Most of the existing mine water treatment methods rely on ground treatment systems, pumping mine water to the ground and performing treatment such as hardness removal, sedimentation, and filtration through ground facilities. However, ground treatment systems usually require the construction of large sedimentation ponds, filtration devices, and chemical dosing equipment, occupying a large amount of ground space. At the same time, it is necessary to transport mine water to the ground over a long distance, which not only increases energy consumption but also has problems such as pipeline blockage and unstable transportation. In addition, the sludge generated during the ground treatment process also needs to be additionally treated and disposed of, increasing the operating cost and environmental burden.

[0003] To overcome the deficiencies of ground treatment systems, underground treatment technologies have gradually received attention and application. By directly performing hardness removal and purification treatment on mine water underground, the pumping volume of mine water can be effectively reduced, the transportation energy consumption can be reduced, the demand for ground facilities and the problem of ground disposal of sludge can be reduced, and it has high economic efficiency and environmental protection. The underground treatment technology of mine water has characteristics such as multi-variables, strong coupling, empirical nature, large time delay, and large water quality fluctuations, and still faces many problems in practical applications. For example, the existing underground treatment control system has insufficient response ability to water quality changes, and it is easy to have problems such as waste of chemicals or insufficient dosing, resulting in unstable treatment effects, and it will also cause problems such as fouling and failure of treatment equipment, affecting the continuity and reliability of the system, increasing the maintenance cost, and restricting the popularization and application of underground treatment technologies. Summary of the Invention

[0004] The purpose of the present disclosure is to provide an intelligent control system, method, medium and electronic device for underground treatment of mine water.

[0005] To achieve the above purpose, in the first aspect of the present disclosure, an intelligent control system for underground treatment of mine water is provided, and the system includes an on-line water quality monitoring module, an automatic control module, an intelligent chemical dosing module, and a calibration and optimization module; The on-line water quality monitoring module is used to monitor the water quality parameters of the raw mine water and the treated mine water in real time, and send the water quality parameters to the automatic control module and the calibration and optimization module; The automatic control module is used to determine a chemical dosing strategy according to the water quality parameters of the raw mine water and a chemical dosing prediction model, and send a chemical dosing control signal to the intelligent chemical dosing module; The intelligent chemical dosing module is used to receive the chemical dosing control signal and perform chemical dosing operations according to the chemical dosing strategy; The calibration and optimization module is used to calibrate the chemical dosing strategy according to the water quality parameters of the mine water effluent and optimize the chemical dosing prediction model.

[0006] Optionally, the water quality parameters include at least one of pH value, turbidity, hardness, alkalinity, content of water quality interference factors, and flow rate.

[0007] Optionally, the water quality on-line monitoring module includes a first water quality on-line monitoring unit and a second water quality on-line monitoring unit; the first water quality on-line monitoring unit is used to monitor the water quality parameters of the raw mine water in real time and send the water quality parameters of the raw mine water to the automatic control module; the second water quality on-line monitoring unit is used to monitor the water quality parameters of the mine water effluent in real time and send the water quality parameters of the mine water effluent to the calibration and optimization module.

[0008] Optionally, the chemical dosing strategy includes at least one of the types of chemicals dosed, dosing sequence, dosing amount, and dosing rate.

[0009] Optionally, the automatic control module includes a first data acquisition unit, a prediction model establishment unit, a dosing strategy determination unit, and a control signal generation unit; The first data acquisition unit is used to acquire the water quality parameters of the raw mine water and is also used to acquire historical mine water treatment data; The prediction model establishment unit is used to establish one or more chemical dosing prediction models according to the historical mine water treatment data; The dosing strategy determination unit is used to determine the mine water treatment process according to the water quality parameters of the raw mine water, determine the applicable chemical dosing prediction model according to the mine water treatment process, and determine the chemical dosing strategy for the current mine water quality according to the chemical dosing prediction model; The control signal generation unit is used to generate a chemical dosing control signal according to the chemical dosing strategy and send the chemical dosing control signal to the intelligent chemical dosing module.

[0010] Optionally, the intelligent chemical dosing module includes a signal receiving unit and a dosing control unit. The signal receiving unit is used to receive the chemical dosing control signal, and the dosing control unit performs chemical dosing operations according to the chemical dosing strategy.

[0011] Optionally, the calibration and optimization module includes a second data acquisition unit, a data analysis unit, a strategy calibration unit, and a self-learning unit; The second data acquisition unit is used to acquire the water quality parameters of the mine water effluent; The data analysis unit is used to calculate the deviation value between the water quality parameters of the mine water discharge and the set target value; The strategy calibration unit is used to calibrate the chemical dosing strategy according to the deviation value; The self-learning unit is used to adaptively optimize the chemical dosing prediction model according to the calibrated chemical dosing strategy through machine learning algorithms.

[0012] In a second aspect of the present disclosure, there is provided an intelligent control method for underground treatment of mine water, which is applied to the system as described in the first aspect of the present disclosure. The method includes: The water quality online monitoring module is used to monitor the water quality parameters of the raw mine water and the mine water discharge in real time, and send the water quality parameters to the automatic control module and the calibration and optimization module; The automatic control module is used to determine the chemical dosing strategy according to the water quality parameters of the raw mine water and the chemical dosing prediction model, and send a chemical dosing control signal to the intelligent chemical dosing module; The intelligent chemical dosing module receives the chemical dosing control signal and performs the chemical dosing operation according to the chemical dosing strategy; The calibration and optimization module is used to calibrate the chemical dosing strategy according to the water quality parameters of the mine water discharge and optimize the chemical dosing prediction model.

[0013] In a third aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium, on which a computer program is stored. The program, when executed by a processor, implements the steps of the method described in the second aspect of the present disclosure.

[0014] In a fourth aspect of the present disclosure, there is provided an electronic device, including: A memory, on which a computer program is stored; A processor, configured to execute the computer program in the memory to implement the steps of the method described in the second aspect of the present disclosure.

[0015] Through the above technical solutions, the intelligent control system for underground treatment of mine water in the present disclosure is based on the online monitoring data of mine water quality and the chemical dosing prediction model, responds to the changes in mine water quality in real time, dynamically adjusts the chemical dosing strategy, realizes the precise dosing of chemicals, effectively improves the effect of underground treatment of mine water, reduces the operation and maintenance costs of the underground treatment system, and improves the reliability. The control system of the present disclosure has a high level of automation and intelligence, can adapt to complex water quality conditions and large-scale mine water treatment requirements, provides an efficient, economical and environmentally friendly solution for the management of mine water resources in mining areas, and has broad application prospects.

[0016] Other features and advantages of the present disclosure will be described in detail in the following detailed description section. Brief Description of the Drawings

[0017] The drawings are used to provide a further understanding of the present disclosure, and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings: Figure 1 is a block diagram of an intelligent control system for underground treatment of mine water shown according to an exemplary embodiment.

[0018] Figure 2 is a schematic structural diagram of an intelligent control system for underground treatment of mine water shown according to an exemplary embodiment applied to an underground mine water treatment system.

[0019] Figure 3 is a flowchart of an intelligent control method for underground treatment of mine water shown according to an exemplary embodiment.

[0020] Figure 4 is a block diagram of an electronic device shown according to an exemplary embodiment.

[0021] Figure 5 is the hardness situation of the purified water outlet in Example 2.

[0022] Description of the Reference Numerals 1 - raw water tank, 2 - chemical tank, 3 - intelligent control system, 4 - dosing premixing tank / pipeline mixer, 5 - diversion trough, 6 - pipeline filter, 7 - filtered diversion trough, 8 - online water quality and quantity monitoring instrument. Detailed Description of the Embodiments

[0023] The following details the specific embodiments of the present disclosure with reference to the drawings. It should be understood that the specific embodiments described herein are only for the purpose of illustrating and explaining the present disclosure, and are not intended to limit the present disclosure.

[0024] In the first aspect of the present disclosure, an intelligent control system for underground treatment of mine water is provided. Referring to Figure 1 , the system includes an online water quality monitoring module 101, an automatic control module 102, an intelligent dosing module 103, and a calibration and optimization module 104.

[0025] In view of the characteristics of multi-variables, strong coupling, empiricism, large time delay, and large water quality fluctuations in the dosing process of underground mine water treatment, the present disclosure proposes an intelligent control system for underground mine water treatment. Through the interconnection between the on-line water quality monitoring module, the automatic control module, the intelligent dosing module, and the calibration and optimization module, it can respond to the changes in the water quality of mine water in real time, dynamically adjust the dosing strategy of chemicals, and achieve precise dosing of chemicals. The control system of the present disclosure is designed specifically for the underground mine water treatment system, can adapt to the complex underground environment, supports the whole-process monitoring and feedback control of the underground treatment system, effectively improves the operation efficiency, stability, and reliability of the underground mine water treatment system, and provides strong technical support for the efficient utilization of mine water resources and environmental protection.

[0026] The on-line water quality monitoring module 101 is used to monitor the water quality parameters of the raw mine water and the treated mine water in real time, and send the water quality parameters to the automatic control module 102 and the calibration and optimization module 104. The on-line water quality monitoring module 101 can monitor the key water quality parameters of mine water in real time, and work in coordination with the automatic control module 102 and the calibration and optimization module 104 through data transmission to ensure the precise control and efficient operation of the entire system. Among them, the mine water includes the raw mine water and the treated mine water. The raw mine water refers to the initial raw water entering the underground mine water treatment system and the water body during the treatment process (including the mixed water after chemical dosing and the water body in the sedimentation reaction). Its water quality is usually complex and fluctuating, and may contain suspended particles, hardness ions (such as calcium, magnesium), dissolved salts (such as sulfates, carbonates), and other impurities. The water quality of the raw mine water directly affects the efficiency and effect of the subsequent treatment process, and it is necessary to monitor its key parameters in real time; the treated mine water refers to the mine water treated by the underground treatment system, and its water quality should meet the mine water use or discharge standards. The water quality parameters of the treated mine water are the core feedback information for system calibration and optimization, and also an important basis for evaluating the treatment effect; by monitoring the water quality parameters of the raw mine water and the treated mine water in real time, it provides data support for system closed-loop control and intelligent optimization. Among them, the water quality parameters may include at least one of pH value, turbidity, hardness, alkalinity, content of water quality interference factors (such as iron ions, free CO2, etc.), and flow rate. The above parameters cover the main chemical, physical, and flow characteristics of mine water during the treatment process, can comprehensively reflect the water quality of mine water, and improve the control accuracy and stability of the system.

[0027] In a specific embodiment, the on-line water quality monitoring module 101 includes a first on-line water quality monitoring unit and a second on-line water quality monitoring unit. Among them, the first on-line water quality monitoring unit is used to monitor the water quality parameters of the raw mine water in real time and send the water quality parameters to the automatic control module 102. Thus, when the raw mine water flows into the underground treatment system, the first on-line water quality monitoring unit collects the real-time water quality parameters of the raw mine water and transmits the data to the automatic control module 102 for input into the chemical dosing prediction model. The second on-line water quality monitoring unit is used to monitor the water quality parameters of the mine water outlet in real time and send the water quality parameters to the calibration and optimization module 104. Thus, the second on-line water quality monitoring unit can detect in real time whether the water quality parameters of the mine water outlet after passing through the treatment system meet the standards. The outlet data is also transmitted to the calibration and optimization module 104, which can be used to evaluate the treatment effect, calibrate the chemical dosing strategy, and optimize the chemical dosing prediction model.

[0028] The acquisition of water quality parameters can be achieved by using existing technical means in the art, such as through various sensing devices and auxiliary devices, etc., to ensure the real-time and accuracy of the monitoring results. In addition, technical equipment such as diversion containers dedicated to water quality monitoring can be installed according to the specific conditions of the monitoring points to optimize the detection environment and meet the requirements of on-line testing. Some diversion containers can be built with pre-treatment functions (such as hardness detection after removing suspended solids by filtration), enabling the on-line water quality monitoring module 101 to operate efficiently in a complex mine water environment. The acquisition period of water quality parameters can be set according to the specific parameter types. For example, pH value and turbidity can be monitored in real time, and the detection of parameters such as hardness and alkalinity requires a certain period. Therefore, the acquisition period can be set to intervals from several minutes to several hours to cope with water quality fluctuations. In addition, according to the flow direction of the mine water, multiple monitoring points can be arranged at the raw water inlet, key reaction nodes, and water outlet respectively to form a full-process monitoring and provide the system with fast response capabilities.

[0029] The automatic control module 102 is used to determine the chemical dosing strategy according to the water quality parameters of the raw mine water and the chemical dosing prediction model, and send a chemical dosing control signal to the intelligent chemical dosing module 103. The automatic control module 102 can input the built-in chemical dosing prediction model according to the real-time water quality data provided by the on-line water quality monitoring module 101, dynamically calculate the optimal chemical dosing strategy, and generate a control signal to send to the intelligent chemical dosing module 103 to ensure the precise control and efficient operation of the mine water treatment process.

[0030] Among them, the chemical dosing prediction model is a relationship model between the water quality characteristics of mine water and the chemical usage method, which is used to dynamically predict the optimal chemical dosing strategy. It can adapt to the complexity and volatility of mine water quality, ensure the maximization of treatment efficiency, minimize chemical consumption, and ensure the stable compliance of the effluent quality. This model can be modeled through systematic analysis of experimental data or actual application data (including mine water quality conditions and chemical usage methods), and after being verified effective, it is used to guide chemical dosing. In actual operation, real-time water quality parameters are input into the model, and then the model can dynamically calculate and output the current optimal chemical dosing strategy.

[0031] The chemical dosing strategy is the chemical dosing method obtained according to the chemical dosing prediction model, which may specifically include at least one of the types of chemicals dosed, dosing sequence, dosing amount, and dosing rate. The chemicals may include common chemicals used in mine water treatment in the art, such as hardness removers, pH regulators, flocculants, etc. The dosing sequence of chemicals refers to the order of multiple chemicals when multiple chemicals need to be dosed.

[0032] In one implementation, the chemical dosing prediction model can be established based on historical mine water treatment data. The historical mine water treatment data may include chemical types, chemical dosage, key water quality parameters, and influent water volume, etc. After the above data can be optionally preprocessed (such as normalization, denoising, etc.), a suitable statistical analysis method (such as correlation analysis, regression analysis, machine learning, etc.) is selected, and then a quantitative relationship formula with the chemical type and dosing amount as the objective function and the key influent water quality parameters of mine water as variables is established.

[0033] Exemplarily, the chemical dosing prediction model may include the following formula (1): m = M(H Ca + 2H Mg + C CO2 + C Fe + α) / Ɛ (1) Wherein, m represents the dosing amount of the chemical (g / m 3 ); M represents the relative molecular weight of the chemical; H Ca represents the calcium ion hardness (mmol / L); H Mg represents the magnesium ion hardness (mmol / L); C CO2 represents the content of free CO2 in the original mine water (mmol / L); C Ferepresents the iron ion content in the raw mine water (mmol / L); α represents the excess amount of the reagent (mmol / L), and the values are as follows: when the turbidity < 10 NTU, α is 0.2 - 0.4; when 10 NTU < turbidity < 1000 NTU, α is 0.1 - 0.2; when the turbidity > 1000 NTU, α = 0 - 0.1; Ɛ represents the purity of the industrial-grade reagent (%). All the above concentrations are calculated as equivalent concentrations. This model is applicable to the situation where the quality of the raw mine water has a molar mass alkalinity greater than the hardness, and the reagent types can be lime or NaOH.

[0034] Also, by way of example, the reagent dosage prediction model may include the following formulas (2) and (3): m1 = M1(Ao + H Mg + C CO2 + C Fe + α) / Ɛ1 (2) m2 = M2(H Ca + β) / Ɛ2 (3) Among them, m1 and m2 respectively represent the dosage of the first reagent and the second reagent (g / m 3 ); M1 and M2 respectively represent the relative molecular weights of the first reagent and the second reagent; Ao represents the total alkalinity (mmol / L); H Ca represents the calcium ion hardness (mmol / L); H Mg represents the magnesium ion hardness (mmol / L); C CO2 represents the content of free CO2 in the raw mine water (mmol / L); C Fe represents the iron ion content in the raw mine water (mmol / L); α represents the excess amount of the first reagent (mmol / L), and the values are as follows: when the turbidity < 10 NTU, α is 0.2 - 0.4; when 10 NTU < turbidity < 1000 NTU, α is 0.1 - 0.2; when the turbidity > 1000 NTU, α = 0 - 0.1; β represents the excess amount of the second reagent, generally taking 1.0 - 1.2 mmol / L. Ɛ1 and Ɛ2 respectively represent the purities of the first reagent and the second reagent (%); all the above concentrations are calculated as equivalent concentrations. This model is applicable to the situation where the quality of the raw mine water has a molar mass alkalinity less than the hardness, the first reagent type can be lime or NaOH, and the second reagent type can be Na2CO3.

[0035] In a specific embodiment, the automatic control module 102 includes a first data acquisition unit, a prediction model establishment unit, a dosing strategy determination unit, and a control signal generation unit. Among them, the first data acquisition unit is connected to the online water quality monitoring module 101, and is used to acquire the water quality parameters of the raw mine water, and is also used to acquire historical mine water treatment data; the prediction model establishment unit is connected to the first data acquisition unit, and is used to establish one or more chemical dosing prediction models according to the historical mine water treatment data, and these models are used to characterize the chemical dosing methods under different mine water treatment processes; the dosing strategy determination unit is respectively connected to the first data acquisition unit and the prediction model, and is used to determine the mine water treatment process according to the water quality parameters of the raw mine water, determine the applicable chemical dosing prediction model according to the mine water treatment process, input the water quality parameters of the raw mine water into its applicable chemical dosing prediction model, and determine the chemical dosing strategy for the current mine water quality according to the chemical dosing prediction model. Among them, the mine water treatment process may include common mine water treatment methods in the art, such as the double-alkali process, the lime softening process, the sodium hydroxide softening process, etc.; the control signal generation unit is connected to the dosing strategy determination unit, and is used to generate a chemical dosing control signal according to the chemical dosing strategy, and send the chemical dosing control signal to the intelligent chemical dosing module 103. By integrating the mine water treatment process judgment logic and the chemical dosing prediction model, the intelligent decision-making of mine water treatment is realized, and the treatment efficiency and the stability of the effluent quality are improved.

[0036] The intelligent chemical dosing module 103 is used to receive the chemical dosing control signal and perform the chemical dosing operation according to the chemical dosing strategy. The intelligent chemical dosing module 103 can dynamically perform the optimization operations of chemical type selection, dosing amount adjustment, dosing sequence, and dosing rate according to the chemical dosing control signal generated by the automatic control module 102, and has the functions of real-time response, dynamic adjustment, and intelligent control, and can adapt to complex water quality conditions to ensure the stability and high efficiency of the mine water treatment effect.

[0037] In a specific embodiment, the intelligent chemical dosing module 103 includes a signal receiving unit and a dosing control unit. The signal receiving unit is used to receive the chemical dosing control signal, and the dosing control unit performs the chemical dosing operation according to the chemical dosing strategy. The intelligent chemical dosing module 103 can independently complete the chemical dosing operation, or rely on the chemical dosing component of the underground treatment system to complete the chemical dosing task, adapting to different mine water treatment requirements and system configuration conditions.

[0038] The calibration and optimization module 104 is used to calibrate the chemical dosing strategy according to the water quality parameters of the mine water effluent and optimize the chemical dosing prediction model. The calibration and optimization module 104 can monitor the effect of chemical dosing in real time, calculate the deviation value of the current strategy, and dynamically calibrate the chemical dosing strategy. At the same time, it optimizes the chemical dosing prediction model to improve the long-term adaptability and treatment efficiency of the system.

[0039] In a specific embodiment, the calibration and optimization module 104 includes a second data acquisition unit, a data analysis unit, a strategy calibration unit, and a self-learning unit. Among them, the second data acquisition unit is connected to the on-line water quality monitoring module 101 and is used to acquire the water quality parameters of the mine water effluent. The data analysis unit is connected to the second data acquisition unit and is used to calculate the deviation value between the water quality parameters of the mine water effluent and the set target value. For example, the target pH value is 9.5 - 10.5, and the current pH value is 9, then the deviation value between the current pH value and the target pH value is -0.5. If the current pH value is 11, then the deviation value between the current pH value and the target pH value is 0.5. The strategy calibration unit is used to calibrate the chemical dosing strategy according to the deviation value. For example, when the deviation value between the current pH value and the target pH value is -0.5, the chemical dosing strategy is calibrated to continue dosing until the pH value reaches 9.5. When the deviation value between the current pH value and the target pH value is 0.5, the chemical dosing strategy is calibrated to stop dosing until the pH value reaches 10.5. The self-learning unit is used to adaptively optimize the chemical dosing prediction model through machine learning algorithms according to the calibrated chemical dosing strategy, realizing feedback closed-loop control. Thus, by evaluating the effect of the chemical dosing strategy in real time and dynamically optimizing the treatment process, the system can adapt to long-term water quality changes, improve the stability and reliability of the system, and reduce the operating cost.

[0040] In a specific embodiment, the system further includes a communication module for data interaction with the ground monitoring center. Through the communication module, the ground monitoring center can obtain information such as the operating status of the mine water underground treatment system, water quality monitoring data, and chemical dosing strategies in real time, and remotely monitor and control the system. At the same time, the communication module supports the upload of alarm information and the issuance of remote instructions, making the control process more visual and flexible, ensuring the efficient operation and safety of the system in a complex environment, and improving the intelligent level of the system.

[0041] The following uses specific examples to illustrate the present disclosure.

[0042] Figure 2It is a schematic structural diagram of an intelligent control system for underground treatment of mine water in an exemplary embodiment of the present disclosure applied to an underground mine water treatment system. In this underground mine water treatment system, the raw water tank 1 is used to store untreated mine water, the chemical tank 2 is used to store various chemicals required during the treatment process. The chemical dosing premixing tank / pipeline mixer 4 is used to fully mix the chemicals output from the chemical tank 2 with the mine water from the raw water tank 1. After preliminary treatment, the mine water flows into the diversion trough 5, and the precipitated particles and suspended solids formed after chemical treatment are removed by the pipeline filter 6 and enter the filtered diversion trough 7. Both the raw water and the produced water pipelines are equipped with on-line water quality and water volume monitoring instruments 8. Through the intelligent control system 3 of the present disclosure, functions such as real-time monitoring of water quality parameters, judgment of mine water treatment processes, generation of chemical dosing strategies, intelligent chemical dosing, strategy calibration, and model optimization are realized.

[0043] Figure 3 It is a flowchart of an intelligent control method for collaborative hardness removal and suspended solid treatment of mine water underground using the intelligent control system 3. After the mine water enters the underground treatment system, the water quality online monitoring module real-time collects the water quality parameters of the mine water and transmits them to the automatic control module. In the automatic control module, the appropriate mine water treatment process is automatically judged. In this embodiment, it is the collaborative hardness removal and suspended solid treatment process. The corresponding chemical dosing prediction model is called, and the chemical dosing strategy is determined. The intelligent chemical dosing module performs the chemical dosing operation according to the chemical dosing strategy to ensure that the chemicals and the mine water are fully mixed in the underground reservoir, completing the hardness precipitation and suspended solid removal treatment process, and generating purified water that meets the discharge or reuse standards. The water quality online monitoring module real-time monitors the water quality of the effluent, and feeds back the data to the calibration and optimization module and the automatic control module. The calibration and optimization module analyzes the deviation between the effluent water quality and the target value, calibrates the chemical dosing strategy, and optimizes the chemical dosing prediction model through a self-learning algorithm to improve the long-term stability of the system. Based on the same inventive concept, in the second aspect of the present disclosure, an intelligent control method for underground treatment of mine water is provided, which is applied to the system as described in the first aspect of the present disclosure. The method includes: Real-time monitor the water quality parameters of the raw mine water and the treated mine water through the water quality online monitoring module, and send the water quality parameters to the automatic control module and the calibration and optimization module; Through the automatic control module, determine the chemical dosing strategy according to the water quality parameters of the raw mine water and the chemical dosing prediction model, and send a chemical dosing control signal to the intelligent chemical dosing module; Receive the chemical dosing control signal through the intelligent chemical dosing module, and perform the chemical dosing operation according to the chemical dosing strategy; Through the calibration and optimization module, calibrate the chemical dosing strategy according to the water quality parameters of the treated mine water, and optimize the chemical dosing prediction model.

[0044] The specific manners in which the various modules perform operations in the above method have been described in detail in the foregoing embodiments of the system, and will not be elaborated herein.

[0045] Based on the same inventive concept, in a third aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that when the program is executed by a processor, the steps of the method described in the second aspect of the present disclosure are implemented.

[0046] Based on the same inventive concept, in a fourth aspect of the present disclosure, there is provided an electronic device Figure 4 which is a block diagram of an electronic device shown according to an exemplary embodiment. As Figure 4 shown, the electronic device 500 may include: a processor 501, a memory 502. The electronic device 500 may further include one or more of a multimedia component 503, an input / output (I / O) interface 504, and a communication component 505.

[0047] Among them, the processor 501 is used to control the overall operation of the electronic device 500 to complete all or part of the steps in the above control method. The memory 502 is used to store various types of data to support the operation of the electronic device 500. Such data may include, for example, instructions for any application or method operating on the electronic device 500, as well as application-related data. The memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc. The multimedia component 503 may include a screen and an audio component. The screen can be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal can be further stored in the memory 502 or sent through the communication component 505. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 504 provides an interface between the processor 501 and other interface modules, and the above other interface modules can be a keyboard, a mouse, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 505 is used for wired or wireless communication between the electronic device 500 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited herein. Accordingly, the communication component 505 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0048] In an exemplary embodiment, the electronic device 500 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for performing the above control method.

[0049] In another exemplary embodiment, there is also provided a computer-readable storage medium including program instructions, which implement the steps of the above control method when executed by a processor. For example, the computer-readable storage medium may be the above-mentioned memory 502 including program instructions, and the above program instructions may be executed by the processor 501 of the electronic device 500 to complete the above control method.

[0050] In another exemplary embodiment, there is also provided a computer-readable storage medium including program instructions, which implement the steps of the above control method when executed by a processor. For example, the non-transitory computer-readable storage medium may be the above-mentioned memory 502 including program instructions, and the above program instructions may be executed by the processor 501 of the electronic device 500 to complete the above control method. In another exemplary embodiment, there is also provided a computer program product, which includes a computer program executable by a programmable device, and the computer program has a code portion for performing the above control method when executed by the programmable device.

[0051] The present disclosure will be further described below by way of examples, but is not intended to limit the present disclosure.

[0052] Embodiment 1 This embodiment uses the control system as shown in Figure 1 Taking the treatment of mine water in a typical coal mine in Shendong area as an example, the water quality parameters of the raw mine water are collected in real time through the water quality online monitoring module as follows: Ca 2+ 145.4 mg / L, Mg 2+ 15.0 mg / L, HCO3 - 127.2 mg / L, turbidity 360 NTU, water volume 200 m 3 / h. The automatic control module determines the mine water treatment process and the chemical dosing strategy according to the chemical dosing prediction model. The double-alkali method treatment process is adopted, and the chemical types are sodium hydroxide and sodium carbonate, with the dosing amounts being 293 mg / L and 173 mg / L respectively. The intelligent chemical dosing module controls the precise dosing of chemicals. The pH in the underground reservoir control tank is 10.0, the hardness removal reaction is completed, the effluent turbidity is 17 NTU, and the average hardness removal rate is 90%.

[0053] Example 2 This example uses the control system as shown in Figure 1 . Taking the co-removal of suspended solids and hardness from mine water with a scale of 2 t / h in a certain mining area of Shendong as an example, the original water quality parameters of the mine water are: mine water with a salinity of 3986 mg / L and a hardness of 250 - 350 mg / L (calculated as CaCO3). The automatic control module determines the mine water treatment process and the chemical dosing strategy according to the chemical dosing prediction model. The co-removal of suspended solids and hardness treatment process is adopted, and the chemical type is lime, with the dosing amount being 285 mg / L. The intelligent chemical dosing module controls the precise dosing of chemicals. The pH in the underground reservoir control tank is 10.0, the co-removal reaction of suspended solids and hardness is completed, and the effluent quality is: the effluent turbidity < 20 NTU, and the average hardness removal rate is 89.67%.

[0054] The effluent hardness situation of the underground mine water treatment system in this example after running for 168 h is as shown in Figure 5 . It can be seen that there are obvious water quality fluctuations in the original mine water. By adjusting the operation parameters in real time through the intelligent control system, the effluent hardness is relatively stable.

[0055] Comparative Example Taking the mine water of a typical coal mine in the Shendong area in Example 1 as the treatment object, the double-alkali method treatment process is adopted. The chemical types are sodium hydroxide and sodium carbonate, and the dosing amounts are based on empirical values according to the influent hardness range, which are 350 mg / L and 150 mg / L respectively. It is impossible to adjust the dosing amount in real time according to water quality fluctuations. The pH in the control tank is 11.4, the average hardness removal rate is 85%, and the effluent turbidity is 17 NTU.

[0056] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept scope of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0057] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combination methods.

[0058] In addition, any combination can be made among various different embodiments of the present disclosure, as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

Claims

1. An intelligent control system for underground mine water treatment, characterized in that: The system includes an online water quality monitoring module, an automatic control module, an intelligent dosing module and a calibration optimization module; The water quality online monitoring module is used to monitor the water quality parameters of mine water source water and mine water outlet water in real time, and send the water quality parameters to the automatic control module and the calibration optimization module; The automatic control module is used to determine the agent dosing strategy according to the water quality parameters of the mine water and the agent dosing prediction model, and send the agent dosing control signal to the intelligent dosing module; The intelligent dosing module is used to receive the drug dosing control signal and perform the drug dosing operation according to the drug dosing strategy; The calibration optimization module is used to calibrate the reagent dosing strategy according to the water quality parameters of the mine water outlet and optimize the reagent dosing prediction model.

2. The system according to claim 1, wherein: The water quality parameters include at least one of pH value, turbidity, hardness, alkalinity, water quality interference factor content and flow rate.

3. The system according to claim 1, wherein: The water quality online monitoring module includes a first water quality online monitoring unit and a second water quality online monitoring unit; the first water quality online monitoring unit is used to monitor the water quality parameters of the mine water raw water in real time, and send the water quality parameters of the mine water raw water to the automatic control module; the second water quality online monitoring unit is used to monitor the water quality parameters of the mine water outlet in real time, and send the water quality parameters of the mine water outlet to the calibration optimization module.

4. The system according to claim 1, wherein: The drug dosing strategy includes at least one of the drug dosing type, dosing sequence, dosing amount and dosing acceleration rate.

5. The system according to claim 1, wherein: The automatic control module includes a first data acquisition unit, a prediction model establishment unit, a dosing strategy determination unit and a control signal generation unit; The first data acquisition unit is used to acquire water quality parameters of the raw mine water, and is also used to acquire historical mine water treatment data; The prediction model building unit is used to build one or more agent dosing prediction models according to the historical mine water treatment data; The dosing strategy determination unit is used to determine a mine water treatment process according to the water quality parameters of the mine water raw water, determine an applicable agent dosing prediction model according to the mine water treatment process, and determine an agent dosing strategy for the current mine water quality according to the agent dosing prediction model; The control signal generating unit is used to generate a medicine dosing control signal according to the medicine dosing strategy, and send the medicine dosing control signal to the intelligent medicine dosing module.

6. The system according to claim 1, wherein: The intelligent dosing module includes a signal receiving unit and a dosing control unit. The signal receiving unit is used to receive the drug dosing control signal. The dosing control unit performs the drug dosing operation according to the drug dosing strategy.

7. The system according to claim 1, wherein: The calibration optimization module includes a second data acquisition unit, a data analysis unit, a strategy calibration unit and a self-learning unit; The second data acquisition unit is used to acquire water quality parameters of the mine water outlet; The data analysis unit is used to calculate the deviation between the water quality parameter of the mine water and the set target value; The strategy calibration unit is used to calibrate the drug dosing strategy according to the deviation value; The self-learning unit is used to adaptively optimize the drug dosing prediction model through a machine learning algorithm according to the calibrated drug dosing strategy.

8. An intelligent control method for underground mine water treatment, characterized in that: Applied to the system as claimed in any one of claims 1 to 7, the method comprises: The water quality parameters of the raw water and the effluent of the mine water are monitored in real time by the water quality online monitoring module, and the water quality parameters are sent to the automatic control module and the calibration optimization module; Through the automatic control module, the agent dosing strategy is determined according to the water quality parameters of the mine water and the agent dosing prediction model, and the agent dosing control signal is sent to the intelligent dosing module; The intelligent dosing module receives the drug dosing control signal and performs the drug dosing operation according to the drug dosing strategy; Through the calibration optimization module, the reagent dosing strategy is calibrated according to the water quality parameters of the mine water outlet, and the reagent dosing prediction model is optimized.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to claim 8 are implemented.

10. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to claim 8.

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