Chemical adding control method and system for industrial sewage treatment

Abstract

The invention is suitable for the technical field of sewage treatment, and provides a chemical adding control method and system for industrial sewage treatment, and the system comprises a real-time monitoring module, a pollution source recognition module, a feedback model construction module, a chemical adding scheme optimization module, a chemical diffusion monitoring module, and a chemical adding effect evaluation module. According to the method, a dosing system based on microbial community feedback and sewage source analysis based on a geographic information system (GIS) are fused, namely, pollution sources in sewage are tracked and analyzed in combination with the GIS technology, the structure and function of microbial communities are analyzed through the pollution sources, the use of chemicals is dynamically adjusted, and the sewage source analysis efficiency is improved. To promote the growth of specific microorganisms to treat specific contaminants. Meanwhile, the medicament can be pushed to be accurately fed by sensing eddy current or sound waves of water flow, and medicament waste is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of sewage treatment, and in particular relates to a dosing control method and system for industrial sewage treatment. Background Art

[0002] Sewage treatment is the process of purifying sewage to meet the water quality requirements for reuse. Sewage treatment is widely used in various fields such as construction, agriculture, transportation, energy, petrochemicals, environmental protection, urban landscape, medical care, and catering. It is also increasingly entering the daily lives of ordinary people. The upstream suppliers of the sewage treatment industry are mainly manufacturers of sewage treatment equipment and suppliers of sewage treatment chemicals. With the rapid development of cities, more and more pollutants are released into the water environment, so various sewage treatment equipment came into being to treat sewage to deal with the pollution caused by sewage to the environment.

[0003] Traditional sewage treatment often relies on fixed dosing schemes and lacks flexibility in response to changes in sewage composition, resulting in inaccurate use of chemicals and increased resource waste. Secondly, existing technologies often have information isolation problems in pollution source tracking and microbial community analysis, and cannot effectively integrate geographic information and microbial ecological data, which limits the comprehensive understanding of pollution sources and the optimization of treatment strategies, making it difficult to effectively improve the ecological efficiency of sewage treatment and failing to give full play to the natural advantages of microorganisms in sewage purification. Summary of the invention

[0004] The object of the present invention is to provide a method for controlling dosing in industrial wastewater treatment, aiming to solve the technical problems existing in the prior art identified in the background technology.

[0005] The present invention is implemented as follows: a method for controlling dosing in industrial wastewater treatment, the method comprising: Real-time monitoring of various parameters of industrial wastewater, recording changes in water quality, obtaining regularly collected wastewater samples, performing high-throughput sequencing, analyzing microbial species, abundance, and functional characteristics, collecting geographic information of wastewater treatment areas, and monitoring water flow status through eddy current sensors to obtain real-time flow rate and direction information; Combine water quality monitoring data with geographic information to identify and track pollutants from sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology; Based on pollution source analysis and microbial community characteristics, a feedback model is constructed to identify the treatment requirements corresponding to different pollutants; According to the feedback model and the needs of microbial ecology, formulate dosing plans, select and optimize drug formulations; Based on the flow rate and direction information, the diffusion of the agent in the water flow is monitored using an acoustic sensor. Combined with real-time monitoring data, the timing of agent injection is calculated and the agent injection strategy is adjusted. Continuously monitor changes in sewage quality and microbial communities after dosing, and regularly evaluate the effects of dosing.

[0006] As a further solution of the present invention, the water quality monitoring data is combined with geographic information to identify and track pollutants in sewage sources, and the relationship between pollution source characteristics and microbial communities is analyzed to determine the impact of different pollution sources on microbial ecology, specifically including: Integrate real-time monitored water quality data and geographic information into the same multidimensional database and in the same format; Combine historical data of geographic information with real-time monitoring data, analyze the relationship between concentration changes and locations of specific pollutants based on changes in water quality monitoring data, determine the source and flow path of pollutants, and identify potential pollution source locations within the sewage treatment area; Classify pollutants from different sources and analyze the effects of various pollution sources on microbial communities in sewage, including their diversity, abundance, and functional characteristics; Integrate the information on microbial species and abundance obtained from high-throughput sequencing with pollution source data to conduct structural analysis of microbial communities and analyze the composition and changes of microbial communities under different pollution sources; Assess the sensitivity of different pollution sources to specific microbial populations and identify the factors by which pollution sources affect microbial communities.

[0007] As a further solution of the present invention, the source of the pollutants is determined using the following algorithm: ; in, It indicates the concentration of pollutants in sewage. represents the intercept, i.e., the pollutant concentration when all features are zero, is the regression coefficient of each characteristic, indicating the influence of pollution source characteristics on pollutant concentration. Represents the characteristic parameters of different pollution sources, is the error term.

[0008] As a further solution of the present invention, the flow path of the pollutant is determined including: Establish a spatial grid based on the sewage area and set the initial pollutant concentration in each grid cell , and set the time step ; Calculate the rate of change of pollutant concentration: ; in, Indicates that within a specific grid, over time Changes in pollutant concentrations The rate of change, represents the pollutant concentration at a specified point, is the diffusion coefficient, which indicates the diffusion capacity of pollutants in water. is the Laplace operator, which represents the spatial variation of concentration, is the water velocity vector, It indicates the change of pollutants with the movement of water flow, that is, the effect of flow on concentration distribution. The product of flow velocity and pollutant concentration indicates the influence of flow path. is the source term, which represents the input and output of pollutants; In each time step, the concentration of each grid cell is updated according to the obtained concentration change rate: ; Track the flow of pollutants based on flow rate. Update the location of pollutants in each grid cell based on current concentration and flow rate information: ; ; ; in, are the velocity components of the water flow in three directions; For each time step, the location of the pollutant is recorded to form the flow trajectory of the pollutant .

[0009] As a further solution of the present invention, the feedback model is constructed based on pollution source analysis and microbial community characteristics to identify the treatment requirements corresponding to different pollutants, specifically including: For the collected sewage samples, analyze the pollutant composition of different sewage samples, identify the main pollutants, and classify the pollution sources according to the characteristics of the pollutants; A feedback model was established, with pollutant concentration, pollutant flow path, microbial abundance and environmental parameters as input variables to obtain the dosage of chemical dosage, microbial growth status and sewage treatment effect.

[0010] As a further solution of the present invention, the obtaining of the dosage of the reagent, the growth state of the microorganisms and the sewage treatment effect specifically includes: Calculate the dosage of the drug based on the input variables : ; in, Indicates at time The pollutant concentration, Indicates at time The abundance of microorganisms, represents environmental variables that affect microbial growth and the efficacy of pharmaceutical agents, Indicates the flow of pollutants in the water body, that is, the flow trajectory of pollutants; They represent the influence coefficients of pollutant concentration, microbial abundance, environmental parameters and flow path on the dosage of the agent; Defining microbial growth states : ; in, represents the initial microbial abundance, represents the maximum growth rate of microorganisms, The environmental carrying capacity, It indicates the inhibition coefficient of pollutants on microbial growth; Analyze the sewage treatment effect based on the dosage of the agent and the growth status of microorganisms: ; in, It indicates the effect of sewage treatment, reflects the degree of removal of pollutants without edema, and indicates the effective treatment capacity of microorganisms, that is, the contribution of unit microorganisms to pollutant removal. and A coefficient that represents the difficulty of pollutant treatment, that is, the inhibitory effect of pollutant concentration on treatment effectiveness.

[0011] As a further solution of the present invention, the dosing scheme is formulated based on the feedback model and combined with the needs of microbial ecology, and the drug formulation is selected and optimized, specifically including: Based on the analysis results of the feedback model, analyze the treatment requirements of different pollutants, calculate the removal rate target and the required dosage of reagents for each pollutant; Combined with high-throughput sequencing results, evaluate the ability of different microorganisms to treat specific pollutants and identify the types of microorganisms that need support; Select the type of agent based on pollutant treatment requirements and evaluate the effect of the agent on the target microbial species; Combine the characteristics of different medicines to calculate and formulate medicine formulas: ; in, is the removal rate of the target pollutant, which represents the removal requirements of all pollutants in the target sewage. For the The amount of medicine administered, For the The removal ability of the agent on the target pollutant, Indicates the number of drug types, that is, the total number of different drugs used in the prescription.

[0012] As a further solution of the present invention, the calculation of the removal rate target of each pollutant and the required dosage of the agent is as follows: ; in, is the removal rate target, indicating the removal effect of the target pollutant. is the concentration of pollutants in the influent, is the concentration of pollutants in the effluent; ; in, is the dosage of the drug, which means the dosage of the drug that needs to be administered per unit time. is the sewage treatment capacity, that is, the total volume of water entering during the treatment process, It is the mass of pollutants that can be removed per unit of reagent.

[0013] As a further solution of the present invention, based on the flow velocity and flow direction information, the diffusion of the agent in the water flow is monitored by using an acoustic sensor, and the timing of the agent injection is calculated in combination with the real-time monitoring data, and the agent injection strategy is adjusted, which specifically includes: The distribution and mixing degree of the agent in the water flow is monitored by an acoustic sensor; Calculate the timing of drug delivery based on the real-time flow rate, flow direction, and drug diffusion conditions monitored by the acoustic sensor: ; in, For the timing of drug administration, is the diffusion distance of the drug, is the water flow velocity, To compensate for the time.

[0014] Another object of the present invention is to provide a dosing control system for industrial wastewater treatment, the system comprising: The real-time monitoring module is used to monitor various parameters of industrial wastewater in real time, record changes in water quality, obtain regularly collected wastewater samples, perform high-throughput sequencing, analyze microbial species, abundance and functional characteristics, collect geographic information of the wastewater treatment area, and monitor water flow status through eddy current sensors to obtain flow rate and direction information in real time; The pollution source identification module is used to combine water quality monitoring data with geographic information to identify and track pollutants in sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology; Feedback model building module, which is used to build feedback models based on pollution source analysis and microbial community characteristics to identify the treatment requirements corresponding to different pollutants; The dosing scheme optimization module is used to formulate dosing schemes, select and optimize drug formulations based on the feedback model and the needs of microbial ecology; The medicine diffusion monitoring module is used to monitor the diffusion of medicine in the water flow based on the flow rate and flow direction information using an acoustic sensor, and calculate the timing of medicine injection and adjust the medicine injection strategy in combination with real-time monitoring data; The dosing effect evaluation module is used to continuously monitor the changes in sewage quality and microbial communities after dosing, and regularly evaluate the dosing effect.

[0015] The beneficial effects of the present invention are:

[0016] This method combines the dosing system based on microbial community feedback and the sewage source analysis based on the geographic information system (GIS). It uses GIS technology to track and analyze the pollution sources in sewage, analyze the structure and function of the microbial community through the pollution sources, and dynamically adjust the use of agents to promote the growth of specific microorganisms to treat specific pollutants. At the same time, it can promote the precise delivery of agents by sensing the eddy currents or sound waves of the water flow, reducing the waste of agents.

[0017] Based on the feedback model, the strategy for using the agent can be continuously adjusted according to real-time data, thereby improving the efficiency of sewage treatment and reducing agent waste. The diffusion of the agent in the flowing water is monitored by an acoustic sensor, and combined with the flow rate and flow direction information, the accurate timing and location of the agent delivery are ensured, further improving the accuracy and efficiency of the treatment. In addition, by continuously monitoring the water quality and changes in the microbial community after the addition of the agent, the effect of the addition is regularly evaluated, making the entire sewage treatment process more scientific and intelligent, and ultimately achieving a more efficient and environmentally friendly sewage treatment solution. This systematic treatment method not only improves the efficiency of sewage treatment, but also helps to promote the growth of specific microorganisms, thereby effectively treating specific pollutants and promoting the in-depth development of overall environmental protection work.

[0018] In addition, through the feedback of microbial communities, the growth of specific microorganisms can be promoted, the ecological efficiency of sewage treatment can be improved, and the burden on the environment can be reduced. Based on the data analysis results, scientific decision-making support is provided, and specific management and control suggestions are provided to sewage treatment managers. Ultimately, by optimizing the dosing plan and reducing the use of chemical agents, the sustainable development of sewage treatment can be promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart of a method for controlling dosing in industrial wastewater treatment provided by an embodiment of the present invention; Figure 2A flowchart for identifying and tracking pollutants in sewage sources, analyzing the relationship between pollution source characteristics and microbial communities, and determining the impact of different pollution sources on microbial ecology provided by an embodiment of the present invention; Figure 3 A flowchart of building a feedback model based on pollution source analysis and microbial community characteristics to identify treatment requirements corresponding to different pollutants provided in an embodiment of the present invention; Figure 4 A flow chart for formulating a dosing plan, selecting and optimizing a drug formulation based on a feedback model and combining the needs of microbial ecology provided in an embodiment of the present invention; Figure 5 A flow chart of monitoring the diffusion of a drug in a water flow and calculating the timing of drug injection and adjusting the drug injection strategy in combination with real-time monitoring data provided by an embodiment of the present invention; Figure 6 A structural block diagram of a dosing control system for industrial wastewater treatment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0022] Figure 1 A flowchart of a method for controlling dosing in industrial wastewater treatment provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method includes: S100 monitors various parameters of industrial wastewater in real time, records changes in water quality, obtains regularly collected wastewater samples, performs high-throughput sequencing, analyzes microbial species, abundance, and functional characteristics, collects geographic information of wastewater treatment areas, and monitors water flow status through eddy current sensors to obtain flow rate and direction information in real time; In this step, a sensor network will be used to monitor water quality parameters such as pH, dissolved oxygen, turbidity, and heavy metal ion concentration in real time to ensure the timeliness and accuracy of the data. Sewage samples are regularly collected from the sewage treatment system and high-throughput sequencing is performed to obtain microbial species and abundance data. Bioinformatics methods are used to analyze the functional characteristics of microorganisms and identify key microorganisms and their ecological roles. In addition, combined with GIS technology, geographic information of the sewage treatment area is collected and integrated, and a geographic database is established. The sewage flow path and pollution source distribution are obtained through high-resolution satellite images and ground measurements. The speed and direction of the water flow are monitored by eddy current sensors, and the flow rate and direction information are obtained in real time. Changes in flow status are recorded so that dynamic adjustments can be made when the agent is added.

[0023] This method can quickly respond to changes in sewage quality and provide timely data support for subsequent dosing control. Combined with GIS technology, it can accurately identify pollution sources and their flow paths, and improve the ability to track pollution sources. At the same time, water quality monitoring, microbial analysis and geographic information systems are integrated into a multidimensional database, which greatly improves data availability and analysis efficiency. Through real-time data analysis, the dosing strategy can be dynamically adjusted to ensure the accuracy of drug delivery and reduce waste.

[0024] S200 combines water quality monitoring data with geographic information to identify and track pollutants from sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology; This method uses high-throughput sequencing technology to deeply analyze the types, abundance and functional characteristics of microorganisms in sewage, and then combines it with geographic information to form a multidimensional database. This integration can not only record water quality changes in real time, but also clarify the relationship between changes in concentrations of specific pollutants and pollution sources by analyzing the relationship between historical data and real-time monitoring data, which helps to identify potential pollution sources in sewage treatment areas. By classifying and evaluating pollutants from different sources and their effects on microbial communities, it is possible to reveal the effects of various pollution sources on microbial diversity, abundance and functional characteristics, thereby further optimizing the sewage treatment process.

[0025] By conducting in-depth analysis of the data obtained in step S100, the relationship between the concentration change of specific pollutants and their geographical location can be identified, thereby accurately determining the source of the pollutants and their flow paths. This data integration capability enables the sewage treatment system to have a higher level of intelligence and can track potential pollution sources in real time. For example, the system can detect abnormal increases in pollutant concentrations in a specific period of time by comparing water quality data in different time periods, and find the possible location of pollution sources based on geographic information, and take corresponding treatment measures in a timely manner.

[0026] In addition, classifying pollutants from different sources and analyzing their effects on microbial communities in sewage can provide a deeper understanding of the specific effects of these pollution sources on microbial diversity, abundance, and functional characteristics. By integrating the microbial data obtained by high-throughput sequencing with the characteristics of the pollution sources, the structural analysis of the microbial community can be performed. This not only helps to identify which microorganisms are most sensitive to specific pollutants, but also reveals the potential impact of pollution sources on the composition and changes of microbial communities, thereby providing a basis for optimizing dosing plans.

[0027] like Figure 2 As shown, the water quality monitoring data is combined with geographic information to identify and track pollutants in sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology, including: S210, integrates real-time monitored water quality data and geographic information into the same multidimensional database and in the same format; S220, combining historical data of geographic information with real-time monitoring data, analyzing the relationship between changes in concentrations of specific pollutants and locations based on changes in water quality monitoring data, determining the sources and flow paths of pollutants, and identifying the locations of potential pollution sources within the sewage treatment area; S230, classify pollutants from different sources and analyze the effects of various pollution sources on the microbial communities in sewage, including their diversity, abundance and functional properties; S240, integrates the information on microbial species and abundance obtained by high-throughput sequencing with pollution source data, conducts structural analysis of microbial communities, and analyzes the composition and changes of microbial communities under different pollution sources; S250, evaluate the sensitivity of different pollution sources to specific microbial populations and identify the factors that affect the microbial community by pollution sources.

[0028] In this step, the source of the pollutants is determined using the following algorithm: ; in, It indicates the concentration of pollutants in sewage. represents the intercept, i.e., the pollutant concentration when all features are zero, is the regression coefficient of each characteristic, indicating the influence of pollution source characteristics on pollutant concentration. Represents the characteristic parameters of different pollution sources, is the error term.

[0029] In this step, determining the flow path of the pollutant includes: Establish a spatial grid based on the sewage area and set the initial pollutant concentration in each grid cell , and set the time step ; Calculate the rate of change of pollutant concentration: ; in, Indicates that within a specific grid, over time Changes in pollutant concentrations The rate of change, represents the pollutant concentration at a specified point, is the diffusion coefficient, which indicates the diffusion capacity of pollutants in water. is the Laplace operator, which represents the spatial variation of concentration, is the water velocity vector, It indicates the change of pollutants with the movement of water flow, that is, the effect of flow on concentration distribution. The product of flow velocity and pollutant concentration indicates the influence of flow path. is the source term, which represents the input and output of pollutants; In each time step, the concentration of each grid cell is updated according to the obtained concentration change rate ; Track the flow of pollutants based on flow rate. Update the location of pollutants in each grid cell based on current concentration and flow rate information: ; ; ; in, are the velocity components of the water flow in three directions; For each time step, the location of the pollutant is recorded to form the flow trajectory of the pollutant .

[0030] S300, based on pollution source analysis and microbial community characteristics, builds a feedback model to identify the treatment requirements corresponding to different pollutants; This step can identify the main pollutants by carefully analyzing the pollutant composition of different sewage samples. The characteristics of these main pollutants will serve as the basis for classifying pollution sources. For example, some pollutants may be highly toxic, while others may inhibit the growth of microorganisms. After identifying these characteristics, pollution sources can be divided into different categories, so that more targeted measures can be taken in the subsequent treatment process.

[0031] In the process of establishing the feedback model, the pollutant concentration, pollutant flow path, microbial abundance and environmental parameters are used as input variables to dynamically calculate the dosage of the agent, the microbial growth status and the sewage treatment effect. The feedback model here can not only reflect the changes in sewage treatment in real time, but also continuously adjust the dosing plan according to real-time data. For example, if the concentration of a certain pollutant is monitored to rise, the system can quickly calculate the required dosage of the agent to ensure the best treatment effect.

[0032] By integrating multiple input variables into the feedback model, the system can monitor and analyze changes in the sewage treatment process in real time, thereby adjusting the dosing strategy in a timely manner. This dynamic adjustment mechanism greatly improves the flexibility of sewage treatment and avoids the waste of resources caused by improper dosage of chemicals in traditional methods. In addition, real-time feedback based on sewage treatment effects can provide a scientific basis for the growth status of microorganisms, making the system more efficient in dealing with different types of pollutants.

[0033] Through this comprehensive approach, the sewage treatment process achieves closed-loop management from data collection to decision-making execution, ensuring coordination and cooperation among all links.

[0034] like Figure 3 As shown, based on the pollution source analysis and microbial community characteristics, a feedback model is constructed to identify the treatment requirements corresponding to different pollutants, including: S310, for the collected sewage samples, analyzing the pollutant composition of different sewage samples, identifying the main pollutants, and classifying the pollution sources according to the characteristics of the pollutants; S320, a feedback model is established, with pollutant concentration, pollutant flow path, microbial abundance and environmental parameters as input variables to obtain the dosage of the agent, the growth status of the microorganisms and the sewage treatment effect.

[0035] In this step, the acquisition of the dosage of the reagent, the growth status of the microorganisms and the sewage treatment effect specifically includes: Calculate the dosage of the drug based on the input variables : ; in, Indicates at time The pollutant concentration, Indicates at time The abundance of microorganisms, represents environmental variables that affect microbial growth and the efficacy of pharmaceutical agents, Indicates the flow of pollutants in the water body, that is, the flow trajectory of pollutants; They represent the influence coefficients of pollutant concentration, microbial abundance, environmental parameters and flow path on the dosage of the agent; Defining microbial growth states : ; in, represents the initial microbial abundance, represents the maximum growth rate of microorganisms, The environmental carrying capacity, It indicates the inhibition coefficient of pollutants on microbial growth; Analyze the sewage treatment effect based on the dosage of the agent and the growth status of microorganisms: ; in, It indicates the effect of sewage treatment, reflects the degree of removal of pollutants without edema, and indicates the effective treatment capacity of microorganisms, that is, the contribution of unit microorganisms to pollutant removal. and A coefficient that represents the difficulty of pollutant treatment, that is, the inhibitory effect of pollutant concentration on treatment effectiveness.

[0036] S400, based on the feedback model and combined with the needs of microbial ecology, formulate dosing plans, select and optimize drug formulations; Based on the analysis results of the feedback model, the system sets the removal rate targets for different pollutants. The removal rate targets and the required dosage of reagents for each pollutant are calculated through monitoring data. This process involves setting the removal rate target, determining the removal rate target for each pollutant within a specific time based on historical data and current water quality conditions; and calculating the required dosage of reagents based on the removal rate target and the input variables in the feedback model. Secondly, the treatment capacity of different microorganisms for specific pollutants is evaluated in combination with the results of high-throughput sequencing to identify the types of microorganisms that need to be supported. The specific steps include identifying the types of microorganisms that have significant removal effects on specific pollutants by analyzing the structure of microbial communities, and evaluating their actual treatment capacity in the sewage treatment process based on the functional characteristics of microorganisms. Then, based on the pollutant treatment requirements, the appropriate type of reagent is selected and its impact on the target microorganism is evaluated, which includes evaluating the removal efficiency of different reagents for pollutants based on literature and experimental data, and analyzing whether the reagents will inhibit or promote the growth and reproduction of target microorganisms. Finally, the reagent formula is calculated and formulated based on the characteristics of different reagents.

[0037] Through detailed pollutant analysis and microbial evaluation, the system can develop a highly targeted dosing plan to ensure that each pollutant can be removed efficiently. Through the dynamic characteristics of the feedback model, the dosage and formula of the agent can be adjusted in time according to the changes in water quality, which improves the flexibility of the treatment process; resource conservation, by accurately calculating the dosage of the required agent, minimizes the waste of agents, reduces treatment costs, and improves economic benefits; environmental friendliness, selects agents that are compatible with microorganisms, avoids negative impacts on the ecosystem, and promotes the sustainable development of sewage treatment.

[0038] like Figure 4 As shown, according to the feedback model and combined with the needs of microbial ecology, a dosing plan is formulated, and the drug formulation is selected and optimized, specifically including: S410, based on the analysis results of the feedback model, analyzing the treatment requirements of different pollutants, and calculating the removal rate target and the required dosage of the reagent for each pollutant; S420, combined with high-throughput sequencing results, evaluates the ability of different microorganisms to treat specific pollutants and identifies the types of microorganisms that need support; S430, selecting the type of agent based on the pollutant treatment requirements and evaluating the effect of the agent on the target microbial species; S440, calculate and formulate pharmaceutical formulas based on the characteristics of different pharmaceuticals: ; in, is the removal rate of the target pollutant, which represents the removal requirements of all pollutants in the target sewage. For the The amount of medicine administered, For the The removal ability of the agent on the target pollutant, Indicates the number of drug types, that is, the total number of different drugs used in the prescription.

[0039] In this step, the removal rate target of each pollutant and the required dosage of the agent are calculated, specifically: ; in, is the removal rate target, indicating the removal effect of the target pollutant. is the concentration of pollutants in the influent, is the concentration of pollutants in the effluent; ; in, is the dosage of the drug, which means the dosage of the drug that needs to be administered per unit time. is the sewage treatment capacity, that is, the total volume of water entering during the treatment process, It is the mass of pollutants that can be removed per unit of reagent.

[0040] S500, based on flow rate and flow direction information, uses acoustic sensors to monitor the diffusion of the agent in the water flow, and combines real-time monitoring data to calculate the timing of agent injection and adjust the agent injection strategy; This step uses an acoustic sensor to monitor the distribution and mixing of the agent in the water flow. This process can obtain the diffusion of the agent in the sewage and its interaction with the water flow in real time. By analyzing the data collected by the acoustic sensor, the system can determine the uniformity and concentration distribution of the agent, thus providing a basis for subsequent agent placement.

[0041] The system can accurately calculate the time required for the agent to reach the target mixing point, thus ensuring that the agent is released at the best time. Specifically, first, the speed and direction of the agent's diffusion in the water flow are calculated based on the water flow velocity monitored by real-time flow rate; then, the release time of the agent is dynamically determined based on the diffusion distance of the agent and the required mixing degree.

[0042] Through real-time monitoring and the use of acoustic wave sensors, the system can accurately determine the diffusion of the agent in the water flow, thereby achieving precise delivery and greatly improving the efficiency of dosing. At the same time, dynamic calculation of the timing of delivery can effectively avoid delayed or premature delivery of the agent, ensuring the optimal contact time between the agent and the sewage, thereby improving the treatment effect and reducing agent consumption. In addition, this step also reduces the waste of resources caused by improper delivery by optimizing the timing of the use of the agent, further improving the economy and environmental protection of the system.

[0043] like Figure 5 As shown, based on the flow rate and flow direction information, the diffusion of the agent in the water flow is monitored by using an acoustic sensor, and the timing of the agent injection is calculated in combination with the real-time monitoring data, and the agent injection strategy is adjusted, which specifically includes: S510, monitoring the distribution and mixing degree of the agent in the water flow by means of an acoustic wave sensor; S520, calculating the timing of drug delivery based on the real-time flow velocity, flow direction, and drug diffusion conditions monitored by the acoustic sensor: ; in, For the timing of drug administration, is the diffusion distance of the drug, is the water flow velocity, To compensate for the time.

[0044] S600 continuously monitors changes in wastewater quality and microbial communities after dosing, and regularly evaluates dosing effects.

[0045] Figure 6 The structural block diagram of a dosing control system for industrial wastewater treatment provided by the embodiment of the present invention is as follows: Figure 6 As shown, the system comprises: The real-time monitoring module 100 is used to monitor various parameters of industrial wastewater in real time, record changes in water quality, obtain regularly collected wastewater samples, perform high-throughput sequencing, analyze microbial species, abundance and functional characteristics, collect geographic information of the wastewater treatment area, and monitor water flow status through eddy current sensors to obtain flow velocity and flow direction information in real time; The pollution source identification module 200 is used to combine water quality monitoring data with geographic information to identify and track pollutants in sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology; The feedback model building module 300 is used to build a feedback model based on pollution source analysis and microbial community characteristics to identify the treatment requirements corresponding to different pollutants; The dosing scheme optimization module 400 is used to formulate a dosing scheme, select and optimize the drug formulation according to the feedback model and the needs of the microbial ecology; The medicine diffusion monitoring module 500 is used to monitor the diffusion of the medicine in the water flow based on the flow rate and flow direction information using an acoustic wave sensor, and calculate the timing of medicine injection and adjust the medicine injection strategy in combination with real-time monitoring data; The dosing effect evaluation module 600 is used to continuously monitor the changes in sewage quality and microbial community after dosing, and regularly evaluate the dosing effect.

[0046] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0047] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0048] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0049] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for controlling dosing in industrial wastewater treatment, characterized in that: The method comprises: Real-time monitoring of various parameters of industrial wastewater, recording changes in water quality, obtaining regularly collected wastewater samples, performing high-throughput sequencing, analyzing microbial species, abundance, and functional characteristics, collecting geographic information of wastewater treatment areas, and monitoring water flow status through eddy current sensors to obtain real-time flow rate and direction information; Combine water quality monitoring data with geographic information to identify and track pollutants from sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology; Based on pollution source analysis and microbial community characteristics, a feedback model is constructed to identify the treatment requirements corresponding to different pollutants; According to the feedback model and the needs of microbial ecology, formulate dosing plans, select and optimize drug formulations; Based on the flow rate and direction information, the diffusion of the agent in the water flow is monitored using an acoustic sensor. Combined with real-time monitoring data, the timing of agent injection is calculated and the agent injection strategy is adjusted. Continuously monitor changes in sewage quality and microbial communities after dosing, and regularly evaluate the effects of dosing.

2. The method according to claim 1, characterized in that The water quality monitoring data is combined with geographic information to identify and track pollutants in sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology, including: Integrate real-time monitored water quality data and geographic information into the same multidimensional database and in the same format; Combine historical data of geographic information with real-time monitoring data, analyze the relationship between concentration changes and locations of specific pollutants based on changes in water quality monitoring data, determine the source and flow path of pollutants, and identify potential pollution source locations within the sewage treatment area; Classify pollutants from different sources and analyze the effects of various pollution sources on microbial communities in sewage, including their diversity, abundance, and functional characteristics; Integrate the information on microbial species and abundance obtained from high-throughput sequencing with pollution source data to conduct structural analysis of microbial communities and analyze the composition and changes of microbial communities under different pollution sources; Assess the sensitivity of different pollution sources to specific microbial populations and identify the factors by which pollution sources affect microbial communities.

3. The method according to claim 2, characterized in that The source of the pollutants is determined using the following algorithm: ； in, It indicates the concentration of pollutants in sewage. represents the intercept, i.e., the pollutant concentration when all features are zero, is the regression coefficient of each characteristic, indicating the influence of pollution source characteristics on pollutant concentration. Represents the characteristic parameters of different pollution sources, is the error term.

4. The method according to claim 3, characterized in that Determining the flow path of the pollutant comprises: Establish a spatial grid based on the sewage area and set the initial pollutant concentration in each grid cell , and set the time step ; Calculate the rate of change of pollutant concentration: ； in, Indicates that within a specific grid, over time Changes in pollutant concentrations The rate of change, represents the pollutant concentration at a specified point, is the diffusion coefficient, which indicates the diffusion capacity of pollutants in water. is the Laplace operator, which represents the spatial variation of concentration, is the water velocity vector, It indicates the change of pollutants with the movement of water flow, that is, the effect of flow on concentration distribution. The product of flow velocity and pollutant concentration indicates the influence of flow path. is the source term, which represents the input and output of pollutants; In each time step, the concentration of each grid cell is updated according to the obtained concentration change rate: ； Track the flow of pollutants based on flow rate. Update the location of pollutants in each grid cell based on current concentration and flow rate information: ； ； ； in, are the velocity components of the water flow in three directions; For each time step, the location of the pollutant is recorded to form the flow trajectory of the pollutant .

5. The method according to claim 4, characterized in that Based on the pollution source analysis and microbial community characteristics, a feedback model is constructed to identify the treatment requirements corresponding to different pollutants, including: For the collected sewage samples, analyze the pollutant composition of different sewage samples, identify the main pollutants, and classify the pollution sources according to the characteristics of the pollutants; A feedback model was established, with pollutant concentration, pollutant flow path, microbial abundance and environmental parameters as input variables to obtain the dosage of chemical dosage, microbial growth status and sewage treatment effect.

6. The method according to claim 5, characterized in that The obtaining of the dosage of the reagent, the growth status of the microorganisms and the sewage treatment effect specifically includes: Calculate the dosage of the drug based on the input variables : ； in, Indicates at time The pollutant concentration, Indicates at time The abundance of microorganisms, represents environmental variables that affect microbial growth and the efficacy of pharmaceutical agents, Indicates the flow of pollutants in the water body, that is, the flow trajectory of pollutants; They represent the influence coefficients of pollutant concentration, microbial abundance, environmental parameters and flow path on the dosage of the agent; Defining microbial growth states : ； in, represents the initial microbial abundance, represents the maximum growth rate of microorganisms, The environmental carrying capacity, It indicates the inhibition coefficient of pollutants on microbial growth; Analyze the sewage treatment effect based on the dosage of the agent and the growth status of microorganisms: ； in, It indicates the effect of sewage treatment, reflects the degree of removal of pollutants without edema, and indicates the effective treatment capacity of microorganisms, that is, the contribution of unit microorganisms to pollutant removal. and A coefficient that represents the difficulty of pollutant treatment, that is, the inhibitory effect of pollutant concentration on treatment effectiveness.

7. The method according to claim 6, characterized in that According to the feedback model, combined with the needs of microbial ecology, a dosing plan is formulated, and the drug formulation is selected and optimized, specifically including: Based on the analysis results of the feedback model, analyze the treatment requirements of different pollutants, calculate the removal rate target and the required dosage of reagents for each pollutant; Combined with high-throughput sequencing results, evaluate the ability of different microorganisms to treat specific pollutants and identify the types of microorganisms that need support; Select the type of agent based on pollutant treatment requirements and evaluate the effect of the agent on the target microbial species; Combine the characteristics of different medicines to calculate and formulate medicine formulas: ； in, is the removal rate of the target pollutant, which represents the removal requirements of all pollutants in the target sewage. For the The amount of medicine administered, For the The removal ability of the agent on the target pollutant, Indicates the number of drug types, that is, the total number of different drugs used in the prescription.

8. The method according to claim 7, characterized in that The above calculations are as follows: ； in, is the removal rate target, indicating the removal effect of the target pollutant. is the concentration of pollutants in the influent, is the concentration of pollutants in the effluent; ； in, is the dosage of the drug, which means the dosage of the drug that needs to be administered per unit time. is the sewage treatment capacity, that is, the total volume of water entering during the treatment process, It is the mass of pollutants that can be removed per unit of reagent.

9. The method according to claim 7, characterized in that: Based on the flow rate and flow direction information, the diffusion of the agent in the water flow is monitored by using an acoustic sensor, and the timing of the agent injection is calculated in combination with the real-time monitoring data, and the agent injection strategy is adjusted, which specifically includes: The distribution and mixing degree of the agent in the water flow is monitored by an acoustic sensor; Calculate the timing of drug delivery based on the real-time flow rate, flow direction, and drug diffusion conditions monitored by the acoustic sensor: ； in, For the timing of drug administration, is the diffusion distance of the drug, is the water flow velocity, To compensate for the time.

10. A dosing control system for industrial wastewater treatment, characterized in that: The system comprises: The real-time monitoring module is used to monitor various parameters of industrial wastewater in real time, record changes in water quality, obtain regularly collected wastewater samples, perform high-throughput sequencing, analyze microbial species, abundance and functional characteristics, collect geographic information of the wastewater treatment area, and monitor water flow status through eddy current sensors to obtain flow rate and direction information in real time; The pollution source identification module is used to combine water quality monitoring data with geographic information to identify and track pollutants in sewage sources, analyze the relationship between pollution source characteristics and microbial communities, and determine the impact of different pollution sources on microbial ecology; Feedback model building module, which is used to build feedback models based on pollution source analysis and microbial community characteristics to identify the treatment requirements corresponding to different pollutants; The dosing scheme optimization module is used to formulate dosing schemes, select and optimize drug formulations based on the feedback model and the needs of microbial ecology; The medicine diffusion monitoring module is used to monitor the diffusion of medicine in the water flow based on the flow rate and flow direction information using an acoustic sensor, and calculate the timing of medicine injection and adjust the medicine injection strategy in combination with real-time monitoring data; The dosing effect evaluation module is used to continuously monitor the changes in sewage quality and microbial communities after dosing, and regularly evaluate the dosing effect.

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