Water treatment agent dosage control method, device, equipment, medium and product

Abstract

The invention relates to the technical field of water treatment, and discloses a water treatment agent dosage control method, device and equipment, a medium and a product, and the water treatment agent dosage control method comprises the following steps: obtaining water quality analysis data of target water quality; the method comprises the following steps: based on system inlet water quality data, simulating water quality change conditions of a chemical agent under different influence factors through Visual MINTEQ software, and determining water quality condition data when the chemical agent treatment effect is optimal; when the system feeds back that water quality data is abnormal after medicament adding, correcting water quality indexes based on a mathematical method; the chemical form and the concentration of the abnormal water quality index are simulated and determined through Visual MINTEQ software; calculating the dosage of a water treatment agent based on the chemical form and concentration of the abnormal water quality index, the water quality condition data and a chemical water treatment method; and training the neural network model based on the water treatment agent dosage and the water quality condition data to obtain a water treatment agent model, and calculating the water treatment agent dosage. The control accuracy of the dosage can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water treatment, and specifically relates to a method, device, equipment, medium and product for controlling the dosage of water treatment chemicals. Background Art

[0002] Water treatment chemicals in a water treatment system can remove harmful substances in water and improve water quality. There are various types of water treatment agents, including reducing agents, scale inhibitors, bactericides, flocculants, etc. These water treatment chemicals play a crucial role in the water treatment process and can effectively remove impurities, odors, harmful substances, etc. in water.

[0003] In recent years, with the progress of water treatment technology and the strictness of environmental protection regulations, the market demand has been continuously increasing. Modern water treatment chemicals, including traditional products such as coagulants, flocculants, bactericides and scale inhibitors, urgently need to be upgraded.

[0004] However, the current water treatment technology cannot adaptively adjust the dosage of chemicals and cannot achieve precise control and real-time optimization in the water treatment process. Summary of the Invention

[0005] In view of this, the present invention provides a method, device, equipment, medium and product for controlling the dosage of water treatment chemicals to improve the accuracy of dosage control.

[0006] The present invention provides a method for controlling the dosage of water treatment chemicals, which includes: obtaining water quality analysis data of the target water quality, where the water quality analysis data includes system inlet water quality data and water quality data after adding chemicals; based on the system inlet water quality data, simulating the water quality changes of chemical agents under different influencing factors through Visual MINTEQ software to determine the water quality condition data when the treatment effect of the chemical agent is optimal; when the system feedbacks that the water quality data after adding chemicals is abnormal, correcting the water quality index based on a mathematical method and simulating to determine the chemical form and concentration of the abnormal water quality index through Visual MINTEQ software; calculating the dosage of water treatment chemicals based on the chemical form and concentration of the abnormal water quality index, the water quality condition data and the chemical water treatment method; training a neural network model based on the dosage of water treatment chemicals and the water quality condition data to obtain a water treatment chemical model, and calculating the dosage of water treatment chemicals.

[0007] In this implementation manner, by determining the optimal water quality condition data based on the system influent water quality data and the water quality changes under different chemical agent influencing factors, various factors affecting the dosing effect of water treatment chemicals can be considered, providing accurate optimal treated water quality information for subsequent model training; through the chemical water treatment method, the chemical dosing amount can be strictly calculated, and the water treatment chemical model trained by combining the optimal water quality conditions and the optimal chemical dosing amount can accurately calculate the water treatment chemical dosing amount to adjust the dosing system. This application combines the chemical method with the digital method to adaptively adjust the chemical dosing amount, which can scientifically and accurately improve the accuracy of the water treatment chemical dosing amount in the water treatment system.

[0008] In an alternative implementation manner, based on the system influent water quality data, the water quality changes under different influencing factors of chemical agents are simulated by Visual MINTEQ software to determine the water quality condition data when the treatment effect of the chemical agent is optimal, including: determining multiple simulation schemes based on different influencing factors of the chemical agent; using the median of the system influent water quality data as the input data of Visual MINTEQ software to simulate the water quality changes of the target water quality under different simulation schemes; determining the water quality condition data corresponding to the lowest target index concentration based on the water quality changes.

[0009] In this implementation manner, by simulating the water quality under various influencing factors and comprehensively considering various possible situations, the accuracy of water quality simulation can be improved.

[0010] In an alternative implementation manner, when the water quality data is abnormal after the chemical agent is added as feedback by the system, the water quality index is corrected based on a mathematical method, and the chemical form and concentration of the abnormal water quality index are determined by simulating with Visual MINTEQ software, including: when the water quality analysis data is abnormal, obtaining multiple groups of water quality index data, where each group of water quality index data includes the system influent water quality data and the corresponding water quality data after the chemical agent is added; correcting the multiple groups of water quality index data based on the entropy weight method and the Delphi method to obtain the corrected water quality data; using the corrected water quality data as the input data of Visual MINTEQ software to determine the real-time water quality distribution data, and determining the chemical form and concentration of the abnormal water quality index based on the real-time water quality distribution data.

[0011] In an alternative implementation manner, correcting the multiple groups of water quality index data based on the entropy weight method and the Delphi method to obtain the corrected water quality data includes: constructing a water quality analysis result decision matrix of the water quality index under multiple groups of water quality index data; determining the index contribution degree of the water quality index based on the water quality analysis result decision matrix; determining the index weight of the water quality index based on the index contribution degree; determining the corrected water quality data of the water quality index under each group of water quality index data based on the index weight.

[0012] In this implementation, when the water quality is abnormal, the detected data is corrected to eliminate the instantaneous error of detection, and further improve the accuracy of subsequent detection. Among them, the entropy weight method is used to calculate the weights of various indicators through mathematical formulas, without relying on expert scoring or subjective judgment, thus effectively avoiding the interference of human factors and further improving the objectivity of data correction.

[0013] In an alternative implementation, calculating the dosage of water treatment chemicals based on the chemical form and concentration of abnormal water quality indicators, water quality condition data, and chemical water treatment methods includes: determining the water treatment chemical formula based on the chemical form of abnormal water quality indicators and chemical water treatment methods; calculating the dosage of water treatment chemicals based on the water treatment chemical formula, the concentration of abnormal water quality indicators, and water quality condition data.

[0014] In this implementation, calculating the dosage of water treatment chemicals in combination with chemical treatment methods, the method based on chemical formulas can ensure the objectivity and accuracy of the dosage.

[0015] In a second aspect, the present invention provides a device for controlling the dosage of water treatment chemicals. The device for controlling the dosage of water treatment chemicals includes: an acquisition module for acquiring water quality analysis data of target water quality, where the water quality analysis data includes system inlet water quality data and water quality data after adding chemicals; a simulation module for simulating the water quality changes of chemical agents under different influencing factors through VisualMINTEQ software based on the system inlet water quality data, and determining the water quality condition data when the water treatment effect is optimal; a determination module for correcting water quality indicators based on a mathematical method and simulating and determining the chemical form of abnormal water quality indicators through Visual MINTEQ software when the system feedbacks that the water quality data after adding chemicals is abnormal; a calculation module for calculating the dosage of water treatment chemicals based on the chemical form and concentration of abnormal water quality indicators, water quality condition data, and chemical water treatment methods; a training module for training a neural network model based on the dosage of water treatment chemicals and water quality condition data to obtain a water treatment chemical agent model, and calculating the dosage of water treatment chemicals.

[0016] In an alternative implementation, the simulation module includes: a first determination unit for determining multiple simulation schemes based on different influencing factors of chemical agents; a simulation unit for using the median of the system inlet water quality data as the input data of VisualMINTEQ software to simulate the water quality changes of target water quality under different simulation schemes; a second determination unit for determining the water quality condition data corresponding to the lowest concentration of the target indicator based on the water quality changes.

[0017] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the water treatment chemical dosage control method according to the first aspect or any corresponding embodiment thereof.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored. The computer instructions are used to cause a computer to execute the water treatment chemical dosage control method according to the first aspect or any corresponding embodiment thereof.

[0019] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, which are used to cause a computer to execute the water treatment chemical dosage control method according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 is a schematic flowchart of a water treatment chemical dosage control method according to an embodiment of the present invention;

[0022] Figure 2 is a schematic flowchart of another water treatment chemical dosage control method according to an embodiment of the present invention;

[0023] Figure 3 is a schematic flowchart of yet another water treatment chemical dosage control method according to an embodiment of the present invention;

[0024] Figure 4 is a structural block diagram of a water treatment chemical dosage control device according to an embodiment of the present invention;

[0025] Figure 5 is a schematic hardware structure diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0027] According to an embodiment of the present invention, an embodiment of a method for controlling the dosage of a water treatment chemical is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0028] In this embodiment, a method for controlling the dosage of a water treatment chemical is provided. Figure 1 It is a flowchart of a method for controlling the dosage of a water treatment chemical according to an embodiment of the present invention. It should be noted that if there are substantially the same results, this embodiment is not limited to Figure 1 the process order shown. As Figure 1 shown, the process includes the following steps:

[0029] Step S101, obtain the water quality analysis data of the target water quality.

[0030] Among them, the water quality analysis data includes the water quality data of the system inlet water and the water quality data after adding the chemical agent.

[0031] Specifically, a multi-parameter water quality analysis instrument is arranged at the inlet of the water treatment system, and the multi-parameter water quality analysis instrument is used to collect the water quality data of the system inlet water to characterize the water quality before adding the chemical agent; a monitor is arranged behind the water treatment chemical addition point of the water treatment system, and the monitor is used to collect the water quality data after adding the chemical agent to characterize the water quality after adding the chemical agent.

[0032] Step S102, based on the water quality data of the system inlet water, simulate the water quality change of the chemical agent under different influencing factors through Visual MINTEQ software, and determine the water quality condition data when the treatment effect of the chemical agent is optimal.

[0033] Among them, Visual MINTEQ software is a computer program used to simulate chemical reactions in aqueous solutions, and can be used to calculate the existence forms and distribution of various elements under different conditions (pH value, redox potential, organic ligand concentration, etc.).

[0034] Among them, the influencing factors of chemical agents include the target index concentration, pH value, and temperature value. Specifically, for different chemical agents, the influencing factors are different. The agents in the solution of the present application include novel bioenzymes, nanomaterials, intelligent agents, etc.

[0035] Specifically, the present application uses the system influent water quality data and specific agent influencing factor values as a simulation scheme, and uses Visual MINTEQ software to simulate the changes and distributions of various index elements in the water quality under current conditions, and determines the water quality conditions corresponding to the optimal agent treatment effect, that is, the content of index elements in the water quality, temperature value, pH value, etc.

[0036] In one implementation, multiple simulation schemes are set according to different pH values and different temperature values. For each simulation scheme, the water treatment results are simulated, and the simulation scheme corresponding to the best treatment effect is obtained.

[0037] Step S103, when the system feedbacks that the water quality analysis data is abnormal, the water quality index is corrected based on a mathematical method, and the chemical form and concentration of the abnormal water quality index are determined by simulating with Visual MINTEQ software.

[0038] Perform water quality anomaly analysis on the system influent water quality data and the water quality data after adding agents. When the system feedbacks water quality anomalies, further obtain the chemical form and concentration of the abnormal water quality index.

[0039] Specifically, a mathematical method is used to correct the water quality index to reduce water quality monitoring errors, and Visual MINTEQ software is used to simulate the abnormal water quality conditions under current conditions to determine the chemical form and concentration of the existing abnormal water quality index. Among them, the abnormal water quality index may be Cl - , OCl - etc.

[0040] In one implementation, the system influent water quality data is subjected to water quality detection. When the system influent water quality data is abnormal, that is, the concentration of the water quality index of one or more chemical forms in the system influent water quality data is greater than the preset concentration, it indicates that the current dosage of the agent cannot adjust the abnormal index of the target water quality to the normal value, and the dosage of the agent needs to be adjusted.

[0041] In another implementation, the water quality data after adding agents is subjected to water quality detection. When the water quality data after adding agents is abnormal, that is, the concentration of the water quality index of one or more chemical forms in the water quality data after adding agents is greater than the preset concentration, it indicates that the abnormal index of the target water quality has not been adjusted to the normal value after adding the agent at the agent addition point, and the dosage of the agent needs to be adjusted.

[0042] In another implementation, water quality detection is performed on the water quality data of the system inlet water and the water quality data after adding chemicals. When the water quality data of the system inlet water and / or the water quality data after adding chemicals is abnormal, the chemical dosage needs to be adjusted.

[0043] Step S104, calculate the chemical dosage of the water treatment chemical based on the chemical form and concentration of the abnormal water quality index, the water quality condition data, and the chemical water treatment method.

[0044] According to the abnormal water quality index and the corresponding chemical water treatment method, calculate the chemical dosage of the water treatment chemical when reducing the abnormal water quality index from the current abnormal water quality index concentration to reach the water quality condition data based on the chemical method.

[0045] Exemplarily, when it is determined that the abnormal water quality index is Cl - , the chemical water treatment method is the reducing agent treatment method, the water treatment chemical is the reducing agent, use the chemical equation of the chlorine removal principle by the reducing agent, and determine the corresponding reducing agent dosage according to the Cl - concentration.

[0046] Step S105, train a neural network model based on the chemical dosage of the water treatment chemical and the water quality condition data to obtain a water treatment chemical model, and calculate the chemical dosage of the water treatment chemical.

[0047] Use the chemical dosage of the water treatment chemical and the water quality condition data as the design input, calculate the optimal chemical dosage of the water treatment chemical with an artificial neural network model, and feedback it to the chemical dosing device through the water treatment system control process for real-time chemical dosage adjustment.

[0048] The water treatment chemical dosage control method provided in this embodiment can determine the optimal water quality condition data based on the water quality data of the system inlet water and the water quality changes under different chemical influencing factors, and can consider various factors affecting the chemical dosing effect of the water treatment chemical, providing accurate optimal treated water quality information for subsequent model training; through the chemical water treatment method, the chemical dosage can be strictly calculated, and the water treatment chemical model trained by combining the optimal water quality condition and the optimal chemical dosage can accurately calculate the chemical dosage of the water treatment chemical to adjust the chemical dosing system. This application combines the chemical method with the digital method to adaptively adjust the chemical dosage, which can scientifically and accurately improve the accuracy of the chemical dosage of the water treatment chemical in the water treatment system.

[0049] In this embodiment, a water treatment chemical dosage control method is provided. Figure 2 It is a schematic flowchart of another water treatment chemical dosage control method according to an embodiment of the present invention. It should be noted that if there are substantially the same results, this embodiment is not limited to Figure 2 the process sequence shown. As Figure 2 shown, this process includes the following steps:

[0050] Step S201: Obtain the water quality analysis data of the target water quality.

[0051] Among them, the water quality analysis data includes the system influent water quality data and the water quality data after adding chemical agents. For details, please refer to Figure 1 Step S101 of the illustrated embodiment, which will not be elaborated here.

[0052] Step S202: Based on the system influent water quality data, use Visual MINTEQ software to simulate the water quality changes under different influencing factors of chemical agents, and determine the water quality condition data when the treatment effect of the chemical agent is optimal.

[0053] Specifically, the above step S202 includes:

[0054] Step S2021: Determine multiple simulation schemes based on different influencing factors of chemical agents.

[0055] First, by querying relevant water treatment literature, determine the agent influencing factors that affect the use effect of water treatment agents. Among them, for different agent implementation effects, there are different agent influencing factors. For example, the agent influencing factors that affect the effect of coagulants include pH value, temperature value, and mixing speed; the agent influencing factors that affect the effect of reducing agents include pH value and temperature value.

[0056] Furthermore, determine the simulation experiment schemes according to the agent influencing factors. Specifically, control one of the agent influencing factors to be fixed and change other agent influencing factors; or control multiple agent influencing factors to be fixed and change other agent influencing factors; or control all agent influencing factors to change, and specify multiple simulation experiment schemes.

[0057] Exemplarily, the pollutant index targeted by this application is Cl - and OCl - , use a reducing agent to remove chlorine, and simulate multiple simulation experiment schemes for chlorine removal by the reducing agent.

[0058] Among them, the principle of chlorine removal by the reducing agent is 2NaHSO3 + 2HOCl → H2SO4 + 2HCl + Na2SO4. Therefore, the redox couple in this step is Cl - / OCl - , and it is necessary to simulate the ion concentration changes of Cl - and OCl - under the influencing factors.

[0059] Among them, the common devices for detecting the results of chlorine removal by reducing agents in the desalination system are ORP meters (online analyzers of oxidation-reduction potential) or online residual chlorine detection instruments. The factors that affect the ORP meter or the online residual chlorine detection instrument are pH value and temperature value. Respectively take the pH value and the temperature value as the variable agent influencing factors, and specify the simulation experiment scheme as:

[0060] The first scenario: Simulate the variation of the concentrations of Cl - and OCl - ions at the same temperature value with different pH values.

[0061] The second scenario: Simulate the variation of the concentrations of Cl - and OCl - ions at the same pH value with different temperature values.

[0062] The third scenario: Simulate the variation of the concentrations of Cl - and OCl - ions at different temperature values and different pH values.

[0063] Step S2022: Use the median of the system influent water quality data as the input data for the Visual MINTEQ software to simulate the water quality changes under different simulation scenarios for the target water quality.

[0064] Specifically, in this application, the system influent water quality data and specific chemical agent influence factor values are used as the simulation scenarios, and the median of the system influent water quality data is used as the input data for the Visual MINTEQ software to simulate the changes and distributions of various index elements in the water quality under the current conditions.

[0065] Exemplarily, obtain the median of each parameter index of the system influent water quality data of the demineralized water treatment system. Among them, the parameter indexes include fluoride ion, nitrate nitrogen, pH value, water hardness (Ca 2+ , Mg 2+ ions), potassium ion, sodium ion, chloride ion and other multiple parameters.

[0066] Input the median of each parameter index of the above system influent water quality data into the Visual MINTEQ software, and simulate the water quality changes according to the above three scenarios.

[0067] Exemplarily, taking the first scenario as an example, simulate the concentrations of Cl - and OCl -The change in ion concentration. For the real-time target water quality, under the Multi-problem / Sweep module of Visual MINTEQ software, select Sweep: one parameter is varied (indicating that only one parameter is changed); then choose sweep component (select the component or parameter to be scanned), select the pH value, and set the relevant parameters, including State the number of problems (specify the number of problems), Start value (starting value), and Increment between values (increment value). The value of Increment between values (increment value) is set to 0.1.

[0068] Using the above simulation method, under different influencing factors, the changes in the concentrations of Cl - and OCl - ions are obtained.

[0069] Step S2023: Determine the water quality condition data corresponding to the lowest target index concentration based on the change in water quality.

[0070] Among them, for different chemical treatment targets, the optimal water quality conditions are different. That is, determine the target index of the chemical treatment. When the concentration of the target index after chemical treatment is the lowest, the corresponding water quality is the best.

[0071] In one implementation, when the chemical is a reducing agent and the target index is Cl - and OCl - , when the concentrations of Cl - and OCl - ions are the lowest, the water quality is the best. Obtain the concentration data, temperature value, pH value, etc. corresponding to the lowest concentrations of Cl - and OCl - ions.

[0072] In this implementation, by simulating the water quality under various influencing factors and comprehensively considering various possible situations, the accuracy of water quality simulation is improved.

[0073] Step S203: When the water quality analysis data is abnormal, correct the water quality index based on a mathematical method, and simulate through Visual MINTEQ software to determine the chemical form and concentration of the abnormal water quality index.

[0074] Specifically, the above step S203 includes:

[0075] Step S2031: When the water quality analysis data is abnormal, obtain multiple groups of water quality index data.

[0076] Among them, each water quality index data group includes the system influent water quality data and the corresponding water quality data after adding medicament.

[0077] Perform water quality detection on the system influent water quality data and the water quality data after adding medicament. When the system influent water quality data and / or the water quality data after adding medicament are abnormal. That is, the concentration of the water quality index in the system influent water quality data is greater than the preset concentration, or the concentration of the water quality index in the water quality data after adding medicament is greater than the preset concentration, and the dosage of the medicament needs to be adjusted.

[0078] Furthermore, obtain multiple groups of system influent water quality data and the corresponding water quality data after adding medicament.

[0079] Exemplarily, obtain no less than 10 groups of water quality data obtained in step S201 and the corresponding water quality data after adding medicament.

[0080] Step S2032, correct multiple water quality index data groups based on the entropy weight method and the Delphi method to obtain corrected water quality data.

[0081] Among them, the entropy weight method (Entropy Weight Method, EWM) is an objective weighting method based on the information entropy theory to determine the weights of evaluation indicators. By calculating the information entropy of each indicator, the degree of difference of each indicator value is measured, so as to allocate reasonable weights to each indicator.

[0082] Among them, the Delphi method is a structured prediction and decision-making method, mainly used to collect and synthesize expert opinions, and then make corresponding decisions.

[0083] In some alternative embodiments, the above step S2032 includes:

[0084] Step a1, construct a decision matrix of water quality analysis results for water quality indicators under multiple water quality index data groups.

[0085] Specifically, for m water quality indicators and b groups of water quality index data groups. The decision matrix of water quality analysis results for m water quality indicators and b groups of water quality index data groups is constructed as:

[0086]

[0087] Among them, X is the decision matrix of water quality analysis results, W m is the water quality index scheme m, X n is the water quality index data group attribute n, x mn is the evaluation object under the scheme m and the attribute n, where n = 1, 2,...; m = 1, 2,...

[0088] Step a2, determine the index contribution degree of the water quality indicators based on the decision matrix of water quality analysis results.

[0089] Specifically, the calculation method for calculating the index contribution degree is as follows:

[0090]

[0091] where p xy represents the contribution degree of the x-th water quality index scheme W under the y-th water quality index attribute. Among them, y = 1, 2, 3,..., n, x = 1, 2, 3,..., m. E x represents the total contribution degree of all m water quality index schemes to the y-th water quality index attribute. y

[0092] Among them, the constant K is set to K = 1 / lnm to ensure 0 ≤ E y ≤ 1. When the contribution degrees of the schemes W under a certain water quality index attribute X are almost equal, the total contribution degree E y is approximately equal to 1. When the contribution degrees of the schemes W under a certain water quality index attribute X are all equal, the weight of this attribute X is 0, that is, the influence of this attribute on the entire decision-making is ignored.

[0093] Step a3, determine the index weight of the water quality index based on the index contribution degree.

[0094] First, determine the consistency as:

[0095] d y = 1 - E y .

[0096] Among them, the magnitude of the attribute is determined by the differences of all the schemes under this attribute. It is used to represent the consistency degree of the contribution degrees of each water quality index scheme under the y-th water quality index attribute.

[0097] Furthermore, determine the index weight w y of the water quality index y as:

[0098]

[0099] Step a4, determine the corrected water quality data of the water quality index under each water quality index data group based on the index weight.

[0100] For the corrected water quality index concentration C xy of the x-th water quality index scheme under the y-th water quality index attribute, it is:

[0101] C xy = A xy × w y .

[0102] Among them, A xy ​is the initial water quality index concentration of the x-th water quality index scheme under the y-th water quality index attribute.

[0103] Step S2033: Use the corrected water quality data as the input data of Visual MINTEQ software to determine the real-time water quality distribution data, and determine the abnormal water quality index concentration based on the real-time water quality distribution data.

[0104] Input the corrected water quality data into Visual MINTEQ software, and use Visual MINTEQ software to simulate the morphological distribution of the current real-time target water quality to obtain the real-time water quality distribution data.

[0105] Compare the real-time water quality distribution with the standard water quality distribution data to determine the abnormal water quality index and the corresponding abnormal water quality index concentration. The subsequent method performs chemical agent addition treatment on the abnormal water quality index with anomalies.

[0106] In this implementation mode, when the water quality is abnormal, the detected data is corrected to eliminate the instantaneous error of detection, and further improve the accuracy of subsequent detection. Among them, the entropy weight method is used to calculate the weight of each index through a mathematical formula, which does not require relying on expert scoring or subjective judgment, thus effectively avoiding the interference of human factors and further improving the objectivity of data correction.

[0107] Step S204: Calculate the dosage of water treatment chemicals based on the chemical form and concentration of abnormal water quality indicators, water quality condition data, and chemical water treatment methods.

[0108] Specifically, the above step S204 includes: Step S2041: Determine the water treatment chemical formula based on the chemical form of the abnormal water quality indicator and the chemical water treatment method.

[0109] Determine the water treatment chemical formula according to the chemical form of the abnormal water quality indicator with anomalies and the corresponding chemical treatment method.

[0110] Exemplarily, when the abnormal water quality indicator is Cl - and OCl - , the chemical treatment method is the chlorine removal method with a reducing agent, and the corresponding water treatment chemical is the reducing agent NaHSO3.

[0111] Exemplarily, when the abnormal water quality indicator is Cl - and OCl - , and the water treatment chemical is the reducing agent NaHSO3, the chemical formula of the chlorine removal principle with a reducing agent is 2NaHSO3 + 2HOCl → H2SO4 + 2HCl + Na2SO4.

[0112] Step S2042: Calculate the dosage of water treatment chemicals based on the water treatment chemical formula, the sum of abnormal water quality indicators, and water quality condition data.

[0113] According to the concentration of abnormal water quality indicators, water quality condition data, and the water treatment chemical formula of the water treatment agent, and calculate the dosage of the water treatment agent based on the concentration of the abnormal water quality indicators obtained by simulation.

[0114] Exemplarily, based on the current abnormal real-time water quality distribution data and the optimal water quality condition data, determine the concentrations of HOCl, H2SO4, HCl, and Na2SO4, and further calculate the concentration of the reducing agent NaHSO3 to obtain the dosage of the water treatment agent.

[0115] Step S205, train a neural network model based on the dosage of the water treatment agent and the water quality condition data to obtain a water treatment agent model, and calculate the dosage of the water treatment agent.

[0116] Establish an artificial neural network model through a function, where the training function, network learning function, and performance function are determined. The transfer between the input layer and the hidden layer uses the logsig function, and the transfer between the hidden layer and the output layer uses the purelin function. The training result is obtained through the trainlm function. The output layer uses one neuron, select an appropriate method to determine the number of neurons in the hidden layer, and determine the number of neurons in the hidden layer through repeated simulation to construct a water treatment agent model.

[0117] Specifically, use the dosage of the water treatment agent and the water quality condition data as the design input, calculate the optimal dosage of the water treatment agent with the artificial neural network model, and feedback it to the dosing device through the water treatment system control process for real-time dosage adjustment.

[0118] Furthermore, further monitor the water quality after dosing, judge whether water quality indicators such as turbidity, pH value, and pollutant concentration meet the expectations to evaluate the prediction results. When they do not meet the expectations, further adjust the neural network model. It is also possible to achieve intelligent decision-making for chemical dosing through the Internet of Things and big data analysis, improve the self-adaptability and efficiency of the water treatment system. The application of the intelligent dosing system and on-line monitoring technology realizes the precise control and real-time optimization of the water treatment process.

[0119] The method for controlling the dosage of the water treatment agent provided in this embodiment can determine the optimal water quality condition data based on the system inlet water quality data and the water quality changes under different chemical agent influencing factors, and can consider various factors affecting the dosing effect of the water treatment agent, providing accurate optimal treated water quality information for subsequent model training; through the chemical water treatment method, the dosage can be strictly calculated, and the water treatment agent model trained in combination with the optimal water quality condition and the optimal dosage can accurately calculate the dosage of the water treatment agent to adjust the dosing system, scientifically and accurately improving the accuracy of the dosage of the water treatment agent in the water treatment system.

[0120] The present invention takes into account the factors affecting the dosing effect of water treatment agents, determines the effect of the dosing agent under various water quality environments, eliminates the error of the on-line water quality analyzer, and uses the above results as the design input to domesticate through an artificial neural network model to obtain the optimal dosing amount of the water treatment agent, and adjusts the dosing system in real time, scientifically and accurately improving the accuracy of the dosing amount of the water treatment agent in the water treatment system.

[0121] In this embodiment, a method for controlling the dosing amount of water treatment agents is provided. Figure 3 It is a schematic flow chart of another method for controlling the dosing amount of water treatment agents according to an embodiment of the present invention. It should be noted that if there are substantially the same results, this embodiment is not limited to Figure 3 the flow sequence shown.

[0122] As Figure 3 shown, in this specific example, the solution of the present application is applied to the demineralized water system. A multi-parameter analyzer and an instrument analyzer after the reducing agent addition point are installed in the demineralized water system, and the corresponding water quality analysis data is collected.

[0123] Furthermore, determine the factors affecting the effect of the reducing agent, such as pH value and temperature value, and analyze the effect of the reducing agent under different influencing factors. Specifically as follows:

[0124] a) The change of the reducing agent effect when the pH values are different and the temperature value is the same.

[0125] b) The change of the reducing agent effect when the pH value is the same and the temperature values are different.

[0126] c) The change of the reducing agent effect when the pH values and the temperature values are different.

[0127] d) Analyze the optimal conditions for the effect of the reducing agent: the optimal pH value, temperature value and the corresponding effect value.

[0128] Furthermore, when it is detected that the water quality is abnormal after the system feeds back the reducing agent, it means that the reduction effect is poor and the reducing agent needs to be continuously increased. Then, the water quality parameters are corrected by the entropy weight method to reduce the instantaneous error. Specifically as follows: a) Establish a decision matrix; b) Calculate the contribution degree; c) Calculate the total contribution degree; d) Calculate the consistency degree; e) Calculate the weight; f) Calculate the corrected concentration. For details, please refer to step S2032 and will not be elaborated here.

[0129] Furthermore, calculate the dosing amount of the reducing agent in combination with the optimal conditions for the effect of the reducing agent.

[0130] Furthermore, perform training calculations on the artificial neural network model in combination with the dosing amount and the optimal conditions for the effect of the reducing agent to obtain the accurate addition amount of the reducing agent and feedback the dosing to the demineralized water system.

[0131] In this embodiment, a device for controlling the dosage of water treatment chemicals is further provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0132] This embodiment provides a device for controlling the dosage of water treatment chemicals, as Figure 4 shown, including:

[0133] An acquisition module 401, configured to acquire water quality analysis data of the target water quality, where the water quality analysis data includes system influent water quality data and water quality data after adding chemicals.

[0134] A simulation module 402, configured to simulate the water quality changes of chemical agents under different influencing factors through Visual MINTEQ software based on the system influent water quality data, and determine the water quality condition data when the treatment effect of the chemical agent is optimal.

[0135] A determination module 403, configured to, when the water quality data after adding chemicals fed back by the system is abnormal, correct the water quality index based on a mathematical method, and simulate and determine the chemical form and concentration of the abnormal water quality index through Visual MINTEQ software.

[0136] A calculation module 404, configured to calculate the dosage of water treatment chemicals based on the chemical form and concentration of the abnormal water quality index, the water quality condition data, and the chemical water treatment method.

[0137] A training module 405, configured to train a neural network model based on the dosage of water treatment chemicals and the water quality condition data to obtain a water treatment chemical model, and calculate the dosage of water treatment chemicals.

[0138] In some alternative implementation manners, the simulation module 402 includes:

[0139] A first determination unit, configured to determine multiple simulation schemes based on different influencing factors of chemical agents.

[0140] A simulation unit, configured to use the median of the system influent water quality data as the input data of the Visual MINTEQ software to simulate the water quality changes of the target water quality under different simulation schemes.

[0141] A second determination unit, configured to determine the water quality condition data corresponding to the lowest target index concentration based on the water quality changes.

[0142] In some alternative implementation manners, the determination module 403 includes:

[0143] A first acquisition unit, configured to acquire multiple water quality index data groups when the water quality analysis data is abnormal, where each water quality index data group includes system influent water quality data and corresponding water quality data after adding chemical agents.

[0144] A correction unit, configured to correct the multiple water quality index data groups based on the entropy weight method and the Delphi method to obtain corrected water quality data.

[0145] A third determination unit, configured to use the corrected water quality data as input data for Visual MINTEQ software to determine real-time water quality distribution data, and determine the chemical form and concentration of abnormal water quality indexes based on the real-time water quality distribution data.

[0146] In some alternative embodiments, the correction unit includes:

[0147] A construction subunit, configured to construct a water quality analysis result decision matrix of water quality indexes under multiple water quality index data groups.

[0148] A first calculation subunit, configured to determine the index contribution degree of water quality indexes based on the water quality analysis result decision matrix.

[0149] A second calculation subunit, configured to determine the index weight of water quality indexes based on the index contribution degree.

[0150] A third calculation subunit, configured to determine the corrected water quality data of water quality indexes under each water quality index data group based on the index weight.

[0151] In some alternative embodiments, the calculation module 404 includes:

[0152] A third determination unit, configured to determine a water treatment chemical formula based on the chemical form of the abnormal water quality index and the chemical water treatment method.

[0153] A calculation unit, configured to calculate the dosage of water treatment chemical agents based on the water treatment chemical formula, the concentration of abnormal water quality indexes, and water quality condition data.

[0154] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding foregoing embodiments, and will not be elaborated herein.

[0155] The water treatment chemical agent dosage control device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0156] The embodiment of the present invention further provides a computer device having the aboveFigure 4 The water treatment chemical dosing control device shown

[0157] Please refer to Figure 5 , Figure 5 which is a schematic structural diagram of a computer device provided by an alternative embodiment of the present invention. As Figure 5 shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 5 In

[0158] , a processor 10 is taken as an example

[0159] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments

[0160] The memory 20 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 may optionally include a memory remotely provided relative to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and their combinations

[0161] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid state drive; the memory 20 may further include a combination of the above types of memory.

[0162] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected by a bus or other means. Figure 5 Take connection by bus as an example.

[0163] The input device 30 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the computer device, such as touch screen, keypad, mouse, trackpad, touchpad, pointing stick, one or more mouse buttons, trackball, joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., LED), and a haptic feedback device (e.g., vibration motor), etc. The above display device includes but is not limited to liquid crystal display, light emitting diode, display and plasma display. In some alternative embodiments, the display device may be a touch screen.

[0164] The embodiments of the present invention also provide a computer-readable storage medium. The methods according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented by downloading through a network the original computer code stored in a remote storage medium or a non-transitory machine-readable storage medium and to be stored in a local storage medium, so that the methods described herein can be stored in such software processes on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk or a solid state drive, etc.; further, the storage medium may further include a combination of the above types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor or the hardware, the methods shown in the above embodiments are implemented.

[0165] A part of the present invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the present invention through the operations of the computer. Those skilled in the art should understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Herein, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0166] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for controlling the dosage of water treatment agents, characterized in that, The method includes: Obtaining water quality analysis data of the target water quality, where the water quality analysis data includes system influent water quality data and water quality data after adding chemical agents; Based on the system influent water quality data, simulating the water quality changes of chemical agents under different influencing factors through Visual MINTEQ software, and determining the water quality condition data when the treatment effect of the chemical agent is optimal; When the system feedbacks that the water quality data after adding chemical agents is abnormal, correcting the water quality index based on a mathematical method, and simulating and determining the chemical form and concentration of the abnormal water quality index through Visual MINTEQ software; Calculating the dosage of water treatment agents based on the chemical form and concentration of the abnormal water quality index, the water quality condition data, and the chemical water treatment method; Training a neural network model based on the dosage of water treatment agents and the water quality condition data to obtain a water treatment agent model, and calculating the dosage of water treatment agents.

2. The method for controlling the dosage of water treatment agent according to claim 1, characterized in that, The step of, based on the system influent water quality data, simulating the water quality changes of chemical agents under different influencing factors through Visual MINTEQ software, and determining the water quality condition data when the treatment effect of the chemical agent is optimal, includes: Determining multiple simulation schemes based on different influencing factors of the chemical agent; Taking the median of the system influent water quality data as the input data of the Visual MINTEQ software, and simulating the water quality changes of the target water quality under different simulation schemes; Determining the water quality condition data corresponding to the lowest target index concentration based on the water quality changes.

3. The method for controlling the dosage of water treatment agent according to claim 1, characterized in that The step of, when the system feedbacks that the water quality data after adding chemical agents is abnormal, correcting the water quality index based on a mathematical method, and simulating and determining the chemical form and concentration of the abnormal water quality index through Visual MINTEQ software, includes: When the water quality analysis data is abnormal, obtaining multiple water quality index data groups, where each water quality index data group includes the system influent water quality data and the corresponding water quality data after adding chemical agents; Correcting multiple water quality index data groups based on the entropy weight method and the Delphi method to obtain corrected water quality data; Taking the corrected water quality data as the input data of the Visual MINTEQ software, determining the real-time water quality distribution data, and determining the chemical form and concentration of the abnormal water quality index based on the real-time water quality distribution data.

4. The method for controlling the dosage of the water treatment agent according to claim 3, characterized in that, The step of correcting multiple water quality index data groups based on the entropy weight method and the Delphi method to obtain corrected water quality data includes: Constructing a water quality analysis result decision matrix of water quality indexes under multiple water quality index data groups; Determining the index contribution degree of the water quality index based on the water quality analysis result decision matrix; Determining the index weight of the water quality index based on the index contribution degree; Determining the corrected water quality data of the water quality index under each water quality index data group based on the index weight.

5. The method for controlling the dosage of water treatment agent according to claim 3, characterized in that, The step of calculating the dosage of water treatment agents based on the chemical form and concentration of the abnormal water quality index, the water quality condition data, and the chemical water treatment method includes: Determining the water treatment chemical formula based on the chemical form of the abnormal water quality index and the chemical water treatment method; Calculate the dosage of water treatment chemicals based on the water treatment chemical formula, the concentration of the abnormal water quality index, and the water quality condition data.

6. A dosing control device for water treatment chemicals, characterized in that The device includes: An acquisition module for acquiring water quality analysis data of the target water quality, where the water quality analysis data includes system influent water quality data and water quality data after adding chemicals; A simulation module for simulating the water quality changes of chemical agents under different influencing factors based on the system influent water quality data through Visual MINTEQ software, and determining the water quality condition data when the treatment effect of the chemical agent is optimal; A determination module for, when the system feedbacks that the water quality data after adding chemicals is abnormal, correcting the water quality index based on a mathematical method, and simulating and determining the chemical form and concentration of the abnormal water quality index through Visual MINTEQ software; A calculation module for calculating the dosage of water treatment chemicals based on the chemical form and concentration of the abnormal water quality index, the water quality condition data, and the chemical water treatment method; A training module for training a neural network model based on the dosage of water treatment chemicals and the water quality condition data to obtain a water treatment chemical model, and calculating the dosage of water treatment chemicals.

7. The water treatment chemical dosage control device according to claim 6, wherein The simulation module includes: A first determination unit for determining multiple simulation schemes based on different influencing factors of the chemical agent; A simulation unit for using the median of the system influent water quality data as the input data of the Visual MINTEQ software to simulate the water quality changes of the target water quality under different simulation schemes; A second determination unit for determining the water quality condition data corresponding to the lowest target index concentration based on the water quality changes.

8. A computer device, characterized in that, Includes: A memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the water treatment chemical dosage control method according to any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that, Computer instructions are stored on the computer-readable storage medium, and the computer instructions are used to cause a computer to execute the water treatment chemical dosage control method according to any one of claims 1 to 5.

10. A computer program product, characterized in that, Includes computer instructions, and the computer instructions are used to cause a computer to execute the water treatment chemical dosage control method according to any one of claims 1 to 5.

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