A pure water treatment system for producing electrolyte hydrogen water

Abstract

The present invention discloses a pure water treatment system for producing electrolyte hydrogen water, belonging to the technical field of water treatment, including a water quality pretreatment module and a reverse osmosis module, and further including: an inlet water pressure regulation system, including: a data acquisition module, which real-time obtains the inlet water turbidity, solute concentration, water temperature, pH value, water production rate, concentrated water discharge rate and inlet water pressure of the water entering the reverse osmosis module; an inlet water quality evaluation module, which obtains an inlet water quality evaluation coefficient; a temperature evaluation module, which obtains a temperature damage coefficient; a water quality impact analysis module, which obtains a water quality impact coefficient; a liquid flow rate matching module, which obtains the liquid flow rate matching intensity of the water production rate and the concentrated water discharge rate; a water pressure determination module, which constructs a water pressure regulation model based on the inlet water pressure and the liquid flow rate matching intensity to output a target water pressure and adjusts the inlet water pressure to the target water pressure; the present invention can match the water production rate and the concentrated water discharge rate according to the impact of water quality and temperature on the membrane, and then dynamically adjust the inlet water pressure.

Description

Technical Field

[0001] The present invention belongs to the technical field of water treatment, and particularly relates to a pure water treatment system for producing electrolyte hydrogen water. Background Art

[0002] In recent years, with the increasing demand for high-quality drinking water and functional water (such as electrolyte hydrogen water), pure water treatment technology has gradually become a research hotspot. Reverse osmosis (RO) technology has been widely used in the field of pure water preparation due to its high desalination ability. However, existing pure water treatment devices still face many technical bottlenecks in practical applications.

[0003] Traditional reverse osmosis modules usually operate relying on fixed parameters, lacking a dynamic evaluation and regulation mechanism for the quality of influent water. For example, changes in indicators such as influent turbidity and solute concentration easily lead to membrane fouling and scaling, seriously affecting the membrane flux and service life. In addition, the influence of water temperature fluctuations on the performance of membrane materials is often ignored. Too high a temperature may cause membrane material expansion or a decrease in the desalination rate, while sudden temperature changes will instantaneously damage the stability of membrane flux. In the prior art, although some devices have introduced pretreatment units (such as multi-media filters, activated carbon adsorption, etc.), they lack a comprehensive evaluation based on real-time water quality data and are difficult to adjust the pretreatment strategy in a timely manner, resulting in the membrane system being in a non-optimal operating condition for a long time.

[0004] On the other hand, the regulation of influent water pressure mostly relies on empirical formulas or static threshold control and cannot adapt to dynamic interference factors such as pH value and pressure fluctuations. The matching problem between the water production rate and the concentrated water discharge rate has not been effectively solved, and the system efficiency often decreases or the energy consumption increases due to flow rate mismatch. Some technologies attempt to regulate the pressure through single-parameter feedback, but ignore the synergistic effects of water quality, temperature, and pH value, resulting in regulation lag or excessive oscillation and affecting the system stability. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a pure water treatment system for producing electrolyte hydrogen water, which solves the above problems.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A pure water treatment system for producing electrolyte hydrogen water, including a water quality pretreatment module and a reverse osmosis module, further including:

[0007] An influent water pressure regulation system for regulating the influent water pressure of the reverse osmosis module, including:

[0008] A data acquisition module for real-time obtaining the influent turbidity, solute concentration, water temperature, pH value, current water production rate, current concentrated water discharge rate, and current influent water pressure entering the reverse osmosis module;

[0009] An influent water quality assessment module constructs an influent water quality assessment model based on the influent turbidity and solute concentration to obtain an influent water quality evaluation coefficient;

[0010] A temperature evaluation module constructs a temperature damage model based on the water temperature and temperature fluctuation value to obtain a temperature damage coefficient;

[0011] A water quality impact analysis module constructs a water quality impact model based on the influent water quality evaluation coefficient and temperature damage coefficient to obtain a water quality impact coefficient;

[0012] A liquid flow rate matching module constructs a liquid matching model to obtain the liquid flow rate matching intensity of the water production rate and the concentrated water discharge rate under the current pH value, influent water pressure fluctuation, and water quality impact coefficient, and compares it with a preset intensity threshold. If the liquid flow rate matching intensity is not within the matching intensity threshold, a judgment message is formed;

[0013] A water pressure determination module constructs a water pressure adjustment model based on the current influent water pressure and liquid flow rate matching intensity, outputs a target water pressure, and adjusts the influent water pressure to the target water pressure.

[0014] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0015] Further technical solution: The steps of constructing an influent water quality assessment model based on the influent turbidity and solute concentration to obtain an influent water quality evaluation coefficient are as follows:

[0016] Normalize the turbidity and solute concentration by dividing the turbidity and solute concentration by their maximum allowable values respectively to obtain a turbidity index and a solute concentration index;

[0017] Import the turbidity index and solute concentration index into the constructed water quality assessment model to output a water quality evaluation coefficient. The water quality assessment model is expressed as: k w =αT i +βC i , k w represents the water quality evaluation coefficient, T i represents the turbidity index, C i represents the solute concentration index, and α and β represent the weights of the turbidity index and solute concentration index, and α + β = 1;

[0018] Compare the obtained water quality evaluation coefficient with a preset water quality evaluation coefficient threshold. If the water quality evaluation coefficient is not within the water quality evaluation coefficient threshold, adjust the raw water quality entering the reverse osmosis module until the water quality evaluation coefficient is within the water quality evaluation coefficient threshold.

[0019] Further technical solution: The role of α is to quantify the direct impact of turbidity on membrane fouling, and the role of β is to quantify the dominant impact of dissolved salts on membrane scaling and osmotic pressure.

[0020] Further technical solution: The specific steps for constructing a temperature damage model based on water temperature and temperature fluctuation value to obtain the temperature damage coefficient are as follows:

[0021] Import the current water temperature and temperature fluctuation value into the constructed temperature damage model to output the temperature damage coefficient. The temperature damage model is expressed as: k T represents the temperature damage coefficient, T represents the current temperature, T max represents the maximum allowable temperature, ΔT is the temperature fluctuation value equal to the difference between the current temperature value and the average temperature value (ΔT = |T - T avg |), γ represents the temperature level weight, δ represents the temperature fluctuation weight, μ represents the attenuation coefficient, and γ + δ = 1;

[0022] Compare the obtained temperature damage coefficient with the preset temperature damage coefficient threshold. If the temperature damage coefficient is not within the temperature damage coefficient threshold, start the temperature regulation system in the pure water treatment device to adjust the inlet water temperature of the reverse osmosis module to make the temperature damage coefficient within the temperature damage coefficient threshold.

[0023] Further technical solution: The role of γ is the risk of membrane material expansion or desalination rate decline caused by temperature, the role of δ is to capture the instantaneous impact of temperature mutation on membrane flux, and the role of μ is to determine the corresponding sensitivity of the exponential function 1 - e -μΔT to temperature fluctuation.

[0024] Further technical solution: The water quality impact model is expressed as: k im represents the water quality impact coefficient, k w represents the water quality evaluation coefficient, k T represents the temperature damage coefficient.

[0025] Further technical solution: The specific steps for obtaining the liquid flow rate matching intensity are as follows:

[0026] Obtain the pH value impact factor and the inlet water pressure fluctuation factor based on the current pH value and inlet water pressure fluctuation;

[0027] Import the pH value impact factor, the inlet water pressure fluctuation factor, the water production rate, the concentrated water discharge rate, and the water quality impact coefficient into the constructed liquid matching model to output the liquid flow rate matching intensity. The liquid matching model is expressed as:

[0028]

[0029] R m represents the liquid flow rate matching intensity, Q p represents the current water production rate, Q c represents the current concentrated water discharge rate, pHpun Denote the pH value influence factor as P pun Denote the influent water pressure fluctuation factor as k im Denote the water quality influence coefficient as Denote the covariance term of the product water production rate and the concentrated water discharge rate.

[0030] Further technical solution: The specific steps for adjusting the influent water pressure to the target water pressure are as follows:

[0031] The water pressure determination module receives the judgment information formed by the liquid flow rate matching module, imports the current influent water pressure and the liquid flow rate matching intensity into the constructed influent water pressure adjustment model, and outputs the target water pressure. The influent water pressure adjustment model is expressed as:

[0032] P t = p c (1 + k p (R avg - R m ))

[0033] P t Denote the target water pressure, p c Denote the current influent water pressure, k p Denote the proportionality coefficient, R avg Denote the mean value of the upper limit and the lower limit of the intensity threshold, R m Denote the liquid flow rate matching intensity.

[0034] Further technical solution: The pH value influence factor Aims to quantify the degree of deviation of the pH value from neutral and suppress the matching coefficient in an acidic or alkaline environment. The influent water pressure fluctuation factor Aims to quantify the negative impact of the influent water pressure fluctuation ΔP = |P c - P avg | on the system stability, p c Denote the current influent water pressure, P avg Denote the mean value of the pressure allowable range.

[0035] Further technical solution: The operations for adjusting the quality of the raw water entering the reverse osmosis module include replacing one or more of the resin filter, activated carbon filter, multi-media filter, and precision filter in the water quality pretreatment module.

[0036] The present invention provides a pure water treatment system for producing electrolyte hydrogen water, which has the following beneficial effects compared with the prior art:

[0037] 1. A pure water treatment system for producing electrolyte hydrogen water provided by this application can dynamically collect water quality parameters and construct a multi-dimensional evaluation model, adjust the inlet water pressure and pretreatment strategy in real time, and can match the water production rate and the concentrated water discharge rate according to the impact of water quality parameters on the membrane, and then dynamically adjust the inlet water pressure, effectively solving the problems of membrane pollution, low water production efficiency and high energy consumption caused by fixed parameters of traditional reverse osmosis modules, and having the advantages of improving system stability, extending the service life of the membrane and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic working flow diagram of the inlet water pressure adjustment system of the present invention.

[0039] Figure 2 It is a three-dimensional surface diagram of the water quality evaluation model in the embodiment of the present invention.

[0040] Figure 3 It is a curve graph of the temperature damage model in the embodiment of the present invention.

[0041] Figure 4 It is a three-dimensional surface diagram of the water quality impact model in the embodiment of the present invention.

[0042] Figure 5 It is a three-dimensional surface diagram of the liquid matching model in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to 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 used to limit the present invention.

[0044] The following describes the specific implementation of the present invention in detail with specific embodiments.

[0045] Please refer to Figure 1 , a pure water treatment system for producing electrolyte hydrogen water provided by an embodiment of the present invention, includes a water quality pretreatment module and a reverse osmosis module, and further includes:

[0046] An inlet water pressure adjustment system for adjusting the inlet water pressure of the reverse osmosis module, including:

[0047] A data collection module for real-time obtaining the inlet water turbidity, solute concentration, water temperature, pH value, current water production rate, current concentrated water discharge rate and current inlet water pressure entering the reverse osmosis module;

[0048] An inlet water quality evaluation module for constructing an inlet water quality evaluation model based on the inlet water turbidity and solute concentration to obtain an inlet water quality evaluation coefficient;

[0049] A temperature evaluation module that constructs a temperature damage model based on water temperature and temperature fluctuation values to obtain a temperature damage coefficient;

[0050] A water quality impact analysis module that constructs a water quality impact model based on the influent water quality evaluation coefficient and the temperature damage coefficient to obtain a water quality impact coefficient;

[0051] A liquid flow rate matching module that constructs a liquid matching model to obtain the liquid flow rate matching intensity of the water production rate and the concentrated water discharge rate under the current pH value, influent water pressure fluctuation, and water quality impact coefficient, and compares it with a preset intensity threshold. If the liquid flow rate matching intensity is not within the matching intensity threshold, judgment information is formed;

[0052] A water pressure determination module that constructs a water pressure adjustment model based on the current influent water pressure and the liquid flow rate matching intensity, outputs a target water pressure, and adjusts the influent water pressure to the target water pressure.

[0053] Preferably, the steps of constructing an influent water quality evaluation model based on influent turbidity and solute concentration to obtain an influent water quality evaluation coefficient are as follows:

[0054] Normalize the turbidity and solute concentration by dividing the turbidity and solute concentration by their maximum allowable values respectively to obtain a turbidity index and a solute concentration index;

[0055] Import the turbidity index and the solute concentration index into the constructed water quality evaluation model to output a water quality evaluation coefficient. The water quality evaluation model is expressed as: k w =αT i +βC i ,k w represents the water quality evaluation coefficient and the k w ∈[0, 1], T i represents the turbidity index, C i represents the solute concentration index, α and β represent the weights of the turbidity index and the solute concentration index respectively, and α + β = 1. The role of α is to quantify the direct impact of turbidity on membrane fouling (such as suspended solids blocking membrane pores), and the role of β is to quantify the dominant impact of dissolved salts on membrane scaling and osmotic pressure. In this embodiment, α = 0.6, β = 0.4, and the k w =0.6T i +0.4C i , and the three-dimensional surface diagram of the water quality evaluation model under this condition is as shown in Figure 2 (from blue for low risk to red for high risk);

[0056] Compare the obtained water quality evaluation coefficient with the preset water quality evaluation coefficient threshold. If the water quality evaluation coefficient is not within the water quality evaluation coefficient threshold, adjust the raw water quality entering the reverse osmosis module (including replacing one or more of the resin filter, activated carbon filter, multi-media filter, and precision filter in the raw water pretreatment stage) until the water quality evaluation coefficient is within the water quality evaluation coefficient threshold.

[0057] Specifically, when the raw water enters the reverse osmosis module, the turbidity and solute concentration data are collected in real time and normalized to convert them into dimensionless indices. Through a weighted calculation model, the turbidity index and solute concentration index are fused into a single evaluation coefficient according to the preset weights. This coefficient dynamically reflects the comprehensive threat degree of the influent water quality to the membrane system. When it exceeds the preset safety threshold, the pretreatment unit adjustment operation is immediately started. For example, when the solute concentration abnormally increases and the β value increases, the system preferentially triggers the ion exchange resin replacement operation; when the turbidity index rises due to an increase in suspended solids, the multi-media filter backwashing program is started. Through real-time evaluation and timely intervention, effectively avoid the accumulation of pollutants on the membrane surface to form an irreversible pollution layer.

[0058] Compared with the prior art, the traditional method only judges whether a single index exceeds the standard through a fixed threshold and cannot quantify the comprehensive impact of compound pollution. For example, the prior art may separately monitor whether the turbidity exceeds 5 NTU or whether the TDS exceeds 500 ppm, but ignores the synergistic effect generated when the two are superimposed. This solution not only considers the real-time changes of the two indicators by establishing a dynamic evaluation model, but also accurately reflects the impact differences of different pollutants on the membrane performance through weight allocation. When the turbidity is normal but the solute concentration is critical, the prior art may misjudge it as a safe state, while this solution can identify potential scaling risks in advance and start preventive measures through the weight amplification effect of the solute concentration index β.

[0059] Through the above technical solutions, the present application realizes the dynamic evaluation and timely regulation of the influent water quality, and solves the problem of lagging membrane pollution control caused by the lack of comprehensive water quality evaluation in the traditional reverse osmosis module. Through the normalization process and weight allocation mechanism, accurately quantify the synergistic pollution effect of suspended particles and dissolved salts; through the dynamic comparison of the preset threshold, ensure that the pretreatment system adjustment is completed before the pollutant concentration reaches the critical value; through the complementary constraints of α and β, balance the prevention and control priorities of physical pollution and chemical scaling, and avoid the decline of system stability caused by the regulation of a single index.

[0060] Preferably, the specific steps for constructing a temperature damage model based on the water temperature and temperature fluctuation value to obtain the temperature damage coefficient are as follows:

[0061] Import the current water temperature and temperature fluctuation value into the constructed temperature damage model to output the temperature damage coefficient, and the temperature damage model is expressed as: kT represents the temperature damage coefficient, T represents the current temperature, T max represents the maximum allowable temperature, and ΔT is the temperature fluctuation value equal to the difference between the current temperature value and the average temperature value (ΔT = |T - T avg |), γ represents the temperature level weight, δ represents the temperature fluctuation weight, γ + δ = 1, μ represents the attenuation coefficient. The role of γ is the risk of the membrane material expanding or the desalination rate decreasing due to temperature. The role of δ is to capture the instantaneous impact of temperature mutation on the membrane flux. The role of μ is to determine the exponential function 1 - e -μΔT 's corresponding sensitivity to temperature fluctuation. In this embodiment, γ = 0.7, δ = 0.3, μ = 0.2, T max = 40°C, T avg = 30°C. Under this condition, the temperature damage model curve model is as Figure 3 shown;

[0062] Compare the obtained temperature damage coefficient with the preset temperature damage coefficient threshold. If the temperature damage coefficient is not within the temperature damage coefficient threshold, then start the temperature regulation system in the pure water treatment device to adjust the inlet water temperature of the reverse osmosis module, so as to make the temperature damage coefficient within the temperature damage coefficient threshold.

[0063] Among them, the current water temperature refers to the real-time temperature data at the inlet of the reverse osmosis module, which can be specifically collected by a temperature sensor and transmitted to the data acquisition module to be used to characterize the instantaneous temperature level of the environment where the membrane material is located. The maximum allowable temperature refers to the critical temperature value that the reverse osmosis membrane material can withstand, which can be specifically set according to the technical parameters provided by the membrane material supplier and is used to judge the absolute threshold of high temperature risk. The temperature fluctuation value refers to the difference between the current temperature and the average temperature value, which can be specifically calculated by using a moving average algorithm to calculate the temperature average value of the previous several cycles and is used to quantify the severity of temperature change. The temperature level weight and the temperature fluctuation weight refer to the proportionality coefficients assigned to the absolute value of temperature and the fluctuation value respectively, which can be specifically implemented by using preset parameters with a numerical range of 0.5 - 0.8 and are used to adjust the contribution degrees of the absolute value of temperature exceeding the standard and temperature mutation to membrane damage. The attenuation coefficient refers to the adjustment factor of the exponential function, which can be specifically implemented by using preset parameters of 0.1 - 0.3 and is used to control the non-linear influence degree of temperature fluctuation on the damage coefficient.

[0064] Specifically, when the temperature sensor detects the inlet water temperature, the average temperature of the previous two hours is calculated by the sliding window method, and the difference between the current temperature and the average temperature is used as the temperature fluctuation value. For example, when the temperature level weight is set to 0.7 to amplify the harmfulness of the high-temperature absolute value, and the temperature fluctuation weight is set to 0.3 to strengthen the instantaneous impact of temperature mutation, the attenuation coefficient is taken as 0.2 to balance the exponential growth effect of temperature fluctuation on the damage coefficient. When the current temperature is detected to be 35 °C and the maximum allowable temperature is 40 °C, the temperature absolute value term is calculated as 35 / 40 = 0.875. If the temperature fluctuation value reaches 5 °C at this time (the current temperature is 5 °C higher than the average temperature), substituting it into the model to calculate the temperature damage coefficient. When this coefficient exceeds the preset threshold, the cooling device is triggered to cool the inlet water, and at the same time, the heater power is adjusted to suppress subsequent temperature fluctuations.

[0065] Compared with the prior art, the traditional method only triggers temperature regulation through the temperature absolute value threshold and cannot identify the cumulative damage and instantaneous impact of temperature fluctuations on the membrane material. For example, in the case of constant high temperature but no fluctuations, the prior art may misjudge it as a safe state, while this solution identifies the risk of material performance decline caused by stable high temperature through the temperature fluctuation term. When encountering periodic temperature mutations, the prior art cannot distinguish short-term fluctuations from long-term trends, while this solution separates the true abnormal temperature fluctuations through the sliding average algorithm.

[0066] Through the above technical solution, this application can dynamically identify the dual risks of excessive temperature absolute value and temperature mutation, start temperature regulation before the membrane material expands or the desalination rate decreases, and prevent the instantaneous collapse of the membrane flux caused by temperature fluctuations. For example, when the inlet water temperature fluctuates violently in a short period of time, the model quickly amplifies the influence of the temperature fluctuation term through the exponential function, triggering temperature stabilization measures in advance to avoid membrane damage caused by the adjustment lag of the traditional method. At the same time, the weight distribution mechanism is used to distinguish the harm degrees of long-term high temperature and short-term mutation, and optimize the response strategy of the temperature regulation system.

[0067] This application further proposes to jointly control the quantification of temperature-related risks through the temperature level weight, temperature fluctuation weight, and attenuation coefficient in the temperature damage model. Among them, the temperature level weight is used to evaluate the thermal damage risk of water temperature to the membrane material, the temperature fluctuation weight is used to monitor the impact effect of temperature mutation on the membrane flux, and the attenuation coefficient is used to adjust the response gradient of the model to temperature fluctuations.

[0068] Among them, the temperature level weight refers to the measure of the degree to which the water temperature deviates from the maximum allowable temperature. Specifically, the normalized temperature ratio can be used as the calculation benchmark to convert the difference between the actual temperature and the safety threshold into the risk index of membrane material damage. By quantifying the risk contribution of the temperature absolute value, this weight can prevent the membrane material from expanding or the desalination performance from decaying due to continuous high temperature.

[0069] Among them, the temperature fluctuation weight is an evaluation parameter for the instantaneous change amplitude of temperature. Specifically, the difference between the current temperature and the average temperature can be used as the input variable to capture the instantaneous interference of temperature mutation on the membrane flux. This weight can identify mutation events that cause a sudden drop in membrane flux by dynamically tracking the temperature fluctuation trajectory.

[0070] Among them, the attenuation coefficient is a regulation factor for the sensitivity of the exponential function to temperature fluctuations. Specifically, a preset exponential base adjustment parameter can be used to control the amplification or suppression degree of the model to temperature fluctuations. By adjusting the curvature characteristics of the exponential term, this coefficient can not only strengthen the hazard signal of significant temperature fluctuations but also filter out the noise interference of minor fluctuations.

[0071] Specifically, the temperature damage model performs a ratio operation on the real-time temperature and the maximum allowable temperature through the temperature level weight to establish a quantitative relationship between the thermal damage risk of the membrane material and the absolute value of temperature. When the water temperature approaches or exceeds the safety threshold, this weight triggers the membrane protection mechanism. The temperature fluctuation weight establishes an association model between the temperature mutation amplitude and the membrane flux fluctuation by calculating the difference between the current temperature and the average temperature within the operation cycle. When the temperature difference exceeds the set range, the temperature compensation program is started. The attenuation coefficient changes the response sensitivity of the temperature fluctuation term by adjusting the base parameter of the exponential function. For example, when set to 0.9, it can moderately reduce the model output value of minor temperature changes, while when set to 1.1, it can strengthen the risk warning of severe temperature fluctuations. The synergistic effect of these three enables the model to not only evaluate the degradation of membrane performance caused by long-term high temperature but also capture the flux oscillation caused by short-term temperature mutation.

[0072] Compared with the prior art, existing solutions usually only monitor whether the temperature exceeds the threshold, unable to distinguish the difference between the absolute temperature risk and the dynamic fluctuation risk, and lacking a multi-dimensional assessment of temperature mutation events. This solution realizes the hierarchical quantification of static temperature level and dynamic temperature fluctuation by introducing independent parameters of temperature level weight and temperature fluctuation weight. At the same time, the attenuation coefficient is used to adjust the model response characteristics, making the temperature damage assessment have both sensitivity and anti-interference ability.

[0073] Through the above technical solution, this application effectively alleviates the problems of membrane material expansion and desalination rate decline caused by high-temperature environment, and triggers the protection mechanism by calculating the degree of temperature deviation from the safety threshold in real time. At the same time, the model's rapid identification ability for temperature mutation events can reduce the instantaneous fluctuation amplitude of membrane flux, and the parametric design of the attenuation coefficient enables the system to dynamically adjust the temperature sensitivity according to different working conditions, avoiding misjudgment caused by environmental noise. This solution realizes the precise prevention and control of temperature-related damage to reverse osmosis membranes through a hierarchical and multi-dimensional temperature risk assessment mechanism.

[0074] Preferably, the water quality impact model is expressed as: kim Denote the water quality impact coefficient as k w Denote the water quality evaluation coefficient as k T Denote the temperature damage coefficient. Based on the temperature damage coefficient output by the above temperature damage model and the water quality evaluation coefficient output by the water quality assessment model, the three-dimensional surface diagram of the water quality impact model is as Figure 4 shown (from blue low risk to red high risk).

[0075] This application further proposes that the water quality impact model is expressed as the water quality impact coefficient being equal to the superposition effect of the water quality evaluation coefficient and the temperature evaluation coefficient, where the water quality impact coefficient is used to quantitatively evaluate the combined effect of the dynamic change of the influent water quality and the temperature fluctuation.

[0076] Specifically, the water quality evaluation coefficient reflects the risk of suspension blockage and the scaling tendency of dissolved salts through the turbidity and solute concentration data after normalization processing, and the temperature evaluation coefficient amplifies the influence degree of temperature fluctuation on the thermal expansion of the membrane material through an exponential function. The two coefficients are geometrically superimposed and corrected for the synergistic effect to form the water quality impact coefficient, so that a significantly increased comprehensive influence value is generated when high turbidity and high temperature fluctuation exist simultaneously, and the linear transmission of the influence degree can still be maintained through the geometric superposition and correction of the synergistic effect when a single index is abnormal. The operation result of this model is transmitted to the liquid flow rate matching module as the input parameter for the dynamic adjustment of the water production rate and the concentrated water discharge rate, ensuring that the negative synergistic effects caused by water quality deterioration and temperature abnormality are compensated simultaneously during the pressure adjustment process.

[0077] Compared with the prior art, existing reverse osmosis modules usually adopt independent parameter threshold control. For example, a turbidity over-standard alarm or a high temperature protection is set separately, but the combined damage of multiple factors on the membrane performance cannot be quantified. However, in this solution, by establishing a mathematical model of geometric superposition and correction of the synergistic effect, the water quality parameter and the temperature parameter have a non-linear interaction at the algorithm level, which can accurately reflect the superposition effect of high turbidity and temperature mutation, and avoid misjudgment situations where a single parameter meets the standard but the comprehensive influence exceeds the limit.

[0078] Through the above technical solution, this application can quantitatively measure the intensity of the combined effect of the influent water quality fluctuation and the temperature change in real time, provide accurate multi-factor influence evaluation data for the reverse osmosis module, enable the influent pressure adjustment process to perform compensation control for complex abnormal working conditions, and effectively prevent problems such as sudden drop in membrane flux or attenuation of desalination rate caused by dynamic coupling of multiple parameters

[0079] Preferably, the specific steps for constructing a liquid matching model to obtain the liquid flow rate matching intensity of the water production rate and the concentrated water discharge rate under the current pH value, influent pressure fluctuation, and water quality impact coefficient and comparing it with a preset intensity threshold, and forming a judgment message if the liquid flow rate matching intensity is not within the matching intensity threshold are as follows:

[0080] Obtain the pH value influence factor and the influent water pressure fluctuation factor based on the current pH value and the influent water pressure fluctuation. The pH value influence factor aims to quantify the degree of deviation of the pH value from neutrality and suppress the matching coefficient in acidic or alkaline environments. The influent water pressure fluctuation factor aims to quantify the negative impact of the influent water pressure fluctuation ΔP = |P c - P avg | on the system stability, where P c is the current influent water pressure and P avg represents the mean value of the pressure allowable range;

[0081] Import the pH value influence factor, the influent water pressure fluctuation factor, the water production rate, the concentrated water discharge rate, and the water quality influence coefficient into the constructed liquid matching model to output the liquid flow rate matching intensity. The liquid matching model is expressed as:

[0082]

[0083] R m represents the liquid flow rate matching intensity and the R m ∈[0, 1], Q p represents the current water production rate, Q c represents the current concentrated water discharge rate, pH pun represents the pH value influence factor, P pun represents the influent water pressure fluctuation factor, k im represents the water quality influence coefficient, represents the covariance term of the water production rate and the concentrated water discharge rate (its function is to measure the synchronization degree of the water production rate and the concentrated water discharge rate based on the deformation of the Pearson correlation coefficient. The meaning of taking the absolute value of the numerator is to only focus on the fluctuation synchronization, and the denominator is the product of the standard deviations to map the result to the 0 - 1 interval to represent the matching intensity). Under the conditions of the above water quality assessment model and water quality influence model, the three-dimensional surface diagram of the liquid matching model is as Figure 5 shown (from blue low matching to red high matching);

[0084] Compare the liquid flow rate matching intensity with the preset intensity threshold. If the liquid flow rate matching intensity is not within the matching intensity threshold, judgment information is formed.

[0085] Among them, the pH value influence factor refers to the parameter that quantifies the degree of deviation of the pH value from neutrality. Specifically, it can be achieved by normalizing the difference between the absolute value of the pH value and the preset neutral value, and is used to suppress the reduction of the membrane flux in acidic or alkaline environments.

[0086] Among them, the influent water pressure fluctuation factor refers to the parameter that characterizes the instability of the influent water pressure and is used to evaluate the interference intensity of the pressure fluctuation on the membrane separation process.

[0087] Among them, the covariance term of the water production rate and the concentrated water discharge rate refers to the mathematical representation of their dynamic balance relationship, which can be specifically obtained by calculating the covariance of the real-time water production rate and the concentrated water discharge rate, and is used to capture the synchronous difference in the flow rate changes of the two.

[0088] Specifically, the pH sensor collects the pH data of the influent water in real time, generates a pH influence factor after normalization processing, and the pressure sensor synchronously monitors the influent water pressure fluctuation and calculates the influent water pressure fluctuation factor. The water quality influence coefficient output by the water quality monitoring module, together with the real-time water production rate and the concentrated water discharge rate, is input into the liquid matching model. In the model, the pH influence factor and the influent water pressure fluctuation factor are used as suppression terms to respectively penalize the working conditions deviating from the neutral environment and unstable pressure; the water quality influence coefficient is used as an adjustment term to dynamically correct the reference flow rate ratio of the produced water and the concentrated water; and the covariance term of the water production rate and the concentrated water discharge rate is used to characterize the degree of coordination of the flow rate changes of the two. When the liquid flow rate matching intensity exceeds the preset threshold, the system automatically triggers the water pressure adjustment mechanism to make the water production rate and the concentrated water discharge rate reach a new balance state by dynamically adjusting the influent water pressure.

[0089] Compared with the prior art, the traditional method only relies on a single parameter static threshold to control the flow rate matching, ignoring the dynamic coupling effect of pH value change and pressure fluctuation. For example, in the prior art, the pressure adjustment only considers the current water production volume and does not incorporate the membrane flux decay caused by the deviation of the pH value into the calculation, resulting in a lag in adjustment. However, this solution realizes the precise quantification of the dynamic balance between the water production rate and the concentrated water discharge rate by establishing a multi-factor collaborative model, which non-linearly correlates the degree of pH deviation, the amplitude of pressure fluctuation and water quality parameters, and effectively solves the problem that the static control method cannot adapt to complex working conditions.

[0090] Through the above technical solution, this application can real-time sense the interference of pH deviation and pressure fluctuation on the flow rate matching, dynamically correct the influent water pressure parameter, make the water production rate and the concentrated water discharge rate still maintain the best matching state in acidic or alkaline environments, avoid the aggravation of membrane pollution and abnormal increase in energy consumption caused by flow rate mismatch, and at the same time enhance the adaptive ability of the system to cope with the fluctuation of influent water quality.

[0091] Preferably, the specific steps for adjusting the influent water pressure to the target water pressure are as follows:

[0092] The water pressure determination module receives the judgment information formed by the liquid flow rate matching module, imports the current influent water pressure and the liquid flow rate matching intensity into the constructed influent water pressure adjustment model, and outputs the target water pressure. The influent water pressure adjustment model is expressed as:

[0093] P t =p c (1 + k p (R avg -Rm ))

[0094] P t represents the target water pressure, p c represents the current inlet water pressure, k p represents the proportionality coefficient (a proportional factor that controls the adjustment range of the inlet pressure, and its function is to avoid mechanical impact on the membrane caused by pressure mutation. If k p is too large, it will cause oscillation), R avg represents the mean value of the upper limit and the lower limit of the intensity threshold, R m represents the matching intensity of the liquid flow rate.

[0095] Among them, the current inlet water pressure refers to the real-time pressure value at the inlet of the reverse osmosis membrane module, and specifically, it can be collected in real time by a pressure sensor as an adjustment reference to ensure the continuity of the adjustment process.

[0096] Among them, the proportionality coefficient refers to the control parameter of the pressure adjustment range, and specifically, a preset range value such as a constant between 0.5 and 1.5 can be used to balance the adjustment response speed and system stability.

[0097] Among them, the mean value of the intensity threshold refers to the intermediate value of the standard range of the matching intensity of the water production rate and the concentrated water discharge rate, and specifically, it can be obtained through statistical analysis of historical operation data as a reference benchmark for judging whether the matching state deviates from the normal range.

[0098] Among them, the matching intensity of the liquid flow rate refers to the dynamic coordination degree of the water production and the concentrated water discharge rate calculated by a mathematical model. Specifically, the covariance algorithm can be used to quantify the flow rate correlation between the two to reflect the real-time state of the system operation efficiency.

[0099] Specifically, when the water pressure determination module receives the judgment information that the matching intensity of the liquid flow rate deviates from the mean value of the intensity threshold, it inputs the inlet pressure and the matching intensity data collected in real time into the adjustment model. Through the mathematical formula P t = p c (1 + k p (R avg - R m )) to calculate the target water pressure: the current inlet water pressure p c as the base value, the matching intensity difference (R avg - R m ) reflects the deviation degree of the actual operation state from the standard range, and the proportionality coefficient k p controls the pressure adjustment range. For example, when the matching intensity of the liquid flow rate R m is lower than the mean value R avg , the difference (R avg - R m ) is positive, and the target water pressure P t will be based on the current pressure pc According to the proportionality coefficient k p increases, thereby improving the water production rate to restore the flow rate matching. This model realizes the closed-loop control of the inlet pressure by converting the dynamic deviation of the matching strength into the pressure adjustment amount, avoiding the adjustment lag caused by relying on a fixed threshold.

[0100] Compared with the prior art, the traditional method uses a static pressure threshold or an empirical formula for adjustment, and cannot respond to the membrane flux fluctuation caused by the pH value change and the matching strength deviation caused by the pressure disturbance. This solution establishes a real-time mathematical model between the matching strength and the pressure adjustment amount, quantifies the flow rate coordination state into a computable parameter, and makes the pressure adjustment amount form a dynamic correspondence with the actual operation deviation of the system. For example, when the inlet pressure suddenly fluctuates, the real-time change of the matching strength R m will directly act on the (Ra vg- R m ) term in the adjustment formula to achieve millisecond-level pressure compensation, while the prior art needs to wait until the pressure fluctuation exceeds the fixed threshold before triggering the adjustment, resulting in an obvious response delay.

[0101] Through the above technical solution, this application can automatically calculate the optimal inlet pressure according to the real-time matching state of the water production and the concentrated water discharge speed, effectively eliminating the flow rate mismatch problem caused by sudden pH value changes or pressure disturbances. By dynamically adjusting the pressure parameters, the reverse osmosis module maintains the balance between water production efficiency and energy consumption under complex working conditions, avoids damage to the membrane components caused by pressure overshoot, and significantly improves the operation stability of the system.

[0102] Preferably, the operation of adjusting the quality of the raw water entering the reverse osmosis module includes replacing one or more of the resin filter, activated carbon filter, multi-media filter and precision filter in the water quality pretreatment module.

[0103] Among them, the resin filter refers to a filtering unit constructed of ion exchange resin materials, which can be specifically realized by using sulfonic acid type cation exchange resin, and is used for selectively adsorbing calcium and magnesium ions in the raw water to reduce the solute concentration. The activated carbon filter refers to an adsorption device filled with granular activated carbon, which can be specifically realized by using coconut shell-based activated carbon, and intercepts organic pollutants and residual chlorine substances through physical adsorption. The multi-media filter refers to a deep filtering layer composed of quartz sand and anthracite with different particle sizes, which can be specifically realized by using a graded filter material with a particle size gradient of 1.6 - 0.8 mm, and is used for intercepting suspended particles to reduce turbidity. The precision filter refers to a terminal filtering device equipped with a microporous filter membrane, which can be specifically realized by using a 5μm pore diameter polypropylene folded filter element, and is used for intercepting colloid substances to ensure the cleanliness of the inlet water.

[0104] Specifically, when the solute concentration is detected to exceed the standard in real time, the ion exchange resin filter is replaced to improve the removal rate of calcium and magnesium ions. If the turbidity is detected to increase abnormally, the coarse filtration layer in the multi-media filter is replaced with a higher-density anthracite layer to enhance the pollution interception capacity. When the organic pollutant index breaks through the threshold, the ineffective carbon layer in the activated carbon filter is replaced with a fresh adsorption medium. For the case of fluctuating colloidal silicon content, the filter element precision of the precision filter is switched from 5μm to 1μm, and the transmembrane pressure difference is maintained below 0.05MPa. This dynamic adjustment mechanism is achieved through the modular design of the water quality pretreatment module, and each filter is connected by quick-release fasteners.

[0105] It should be noted that in this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusively, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0106] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A pure water treatment system for producing electrolyte hydrogen water, characterized in that: It includes water pretreatment module and reverse osmosis module, and also includes: The inlet water pressure regulating system regulates the inlet water pressure of the reverse osmosis module, including: The data acquisition module acquires the turbidity, solute concentration, water temperature, pH value, current water production rate, current concentrated water discharge rate and current water inlet pressure of the water entering the reverse osmosis module in real time; The inlet water quality assessment module builds an inlet water quality assessment model based on the inlet water turbidity and solute concentration to obtain the inlet water quality assessment coefficient; the temperature assessment module builds a temperature damage model based on the water temperature and temperature fluctuation value to obtain the temperature damage coefficient; The water quality impact analysis module builds a water quality impact model based on the inlet water quality evaluation coefficient and temperature damage coefficient to obtain the water quality impact coefficient; The liquid flow rate matching module builds a liquid matching model to obtain the liquid flow rate matching strength of the water production rate and the concentrated water discharge rate under the current pH value, water inlet pressure fluctuation and water quality influence coefficient, and compares it with the preset strength threshold. If the liquid flow rate matching strength is not within the matching strength threshold, a judgment information is formed; The water pressure determination module constructs a water pressure regulation model based on the current water inlet pressure and liquid flow rate matching strength to output the target water pressure and adjust the water inlet pressure to the target water pressure.

2. The pure water treatment system for producing electrolyte hydrogen water according to claim 1, characterized in that: The steps to construct an influent water quality assessment model based on influent turbidity and solute concentration to obtain the influent water quality assessment coefficient are as follows: The turbidity and solute concentration are normalized, and the turbidity and solute concentration are divided by their maximum allowable values ​​respectively to obtain the turbidity index and solute concentration index; The turbidity index and the solute concentration index are introduced into the constructed water quality assessment model to output the water quality assessment coefficient. The water quality assessment model is expressed as: k w =αT i +βC i k w represents the water quality evaluation coefficient and the k w ∈[0, 1], T i Indicates turbidity index, C i represents the solute concentration index, α and β represent the weights of the turbidity index and the solute concentration index, and α+β=1; The obtained water quality evaluation coefficient is compared with the preset water quality evaluation coefficient threshold. If the water quality evaluation coefficient is not within the water quality evaluation coefficient threshold, the raw water quality entering the reverse osmosis module is adjusted until the water quality evaluation coefficient is within the water quality evaluation coefficient threshold.

3. The pure water treatment system for producing electrolyte hydrogen water according to claim 2, characterized in that: The role of α is to quantify the direct effect of turbidity on membrane fouling, and the role of β is to quantify the dominant effect of dissolved salts on membrane scaling and osmotic pressure.

4. The pure water treatment system for producing electrolyte hydrogen water according to claim 1, characterized in that: The specific steps for constructing a temperature damage model based on water temperature and temperature fluctuation values ​​to obtain the temperature damage coefficient are as follows: The current water temperature and temperature fluctuation value are imported into the constructed temperature damage model to output the temperature damage coefficient. The temperature damage model is expressed as: k T represents the temperature damage coefficient, T represents the current temperature, T max Indicates the maximum allowable temperature, ΔT=|TT avg | is the temperature fluctuation value, which is equal to the difference between the current temperature value and the average temperature value, γ represents the temperature level weight, δ represents the temperature fluctuation weight, and μ represents the attenuation coefficient; The obtained temperature damage coefficient is compared with the preset temperature damage coefficient threshold. If the temperature damage coefficient is not within the temperature damage coefficient threshold, the temperature control system in the pure water treatment device is started to adjust the inlet water temperature of the reverse osmosis module to make the temperature damage coefficient within the temperature damage coefficient threshold.

5. The pure water treatment system for producing electrolyte hydrogen water according to claim 4, characterized in that: The role of γ is to deal with the risk of membrane material expansion or desalination rate reduction caused by temperature, the role of δ is to capture the instantaneous effect of temperature mutation on membrane flux, and the role of μ is to determine the exponential function 1-e -μΔT The corresponding sensitivity to temperature fluctuations.

6. The pure water treatment system for producing electrolyte hydrogen water according to claim 1, characterized in that: The water quality impact model is expressed as: k im represents the water quality influence coefficient, k w Represents the water quality evaluation coefficient, k T Represents the temperature damage coefficient.

7. The pure water treatment system for producing electrolyte hydrogen water according to claim 1, characterized in that: The specific steps to obtain the liquid flow rate matching strength are: Obtain pH value influencing factor and inlet pressure fluctuation factor based on current pH value and inlet pressure fluctuation; The pH value influencing factor, water inlet pressure fluctuation factor, water production rate, concentrated water discharge rate and water quality influence coefficient are introduced into the constructed liquid matching model to output the liquid flow rate matching strength. The liquid matching model is expressed as: R m Indicates the liquid flow rate matching strength and R m ∈[0, 1], Q p Indicates the current water production rate, Q c Indicates the current concentrated water discharge rate, pH pun Indicates pH influence factor, P pun represents the water inlet pressure fluctuation factor, k im represents the water quality impact coefficient, It represents the covariance term between the water production rate and the concentrate discharge rate.

8. The pure water treatment system for producing electrolyte hydrogen water according to claim 1, characterized in that: The specific steps for adjusting the inlet water pressure to the target water pressure are: The water pressure determination module receives the judgment information formed by the liquid flow rate matching module, imports the current inlet water pressure and the liquid flow rate matching strength into the constructed inlet water pressure regulation model, and outputs the target water pressure. The inlet water pressure regulation model is expressed as: P t =p c (1+k p (R avg -R m )) P t represents the target water pressure, p c Indicates the current inlet water pressure, k p Represents the proportionality coefficient, R avg Represents the mean of the upper and lower limits of the intensity threshold, R m Indicates the liquid flow rate matching strength.

9. The pure water treatment system for producing electrolyte hydrogen water according to claim 7, characterized in that: The pH value influencing factor The purpose is to quantify the degree of pH deviation from neutrality, suppress the matching coefficient in acidic or alkaline environment, and the water inlet pressure fluctuation factor The purpose is to quantify the inlet pressure fluctuation ΔP = |P c -P avg |Negative impact on system stability, P avg Indicates the mean of the allowable pressure range.

10. The pure water treatment system for producing electrolyte hydrogen water according to any one of claims 1 to 9, characterized in that: The operation of adjusting the quality of raw water entering the reverse osmosis module includes replacing one or more of the resin filter, activated carbon filter, multi-media filter and precision filter in the water quality pretreatment module.

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