Pure water treatment system for producing electrolyte hydrogen water

Abstract

The invention discloses a pure water treatment system for producing electrolyte hydrogen water, which belongs to the technical field of water treatment.The pure water treatment system comprises a water quality pretreatment module and a reverse osmosis module, and further comprises a water inlet pressure adjusting system, a water inlet pressure adjusting system and a water outlet pressure adjusting system, the turbidity, solute concentration, water temperature, PH value, water production speed, concentrated water discharge speed and water inlet pressure of inlet water entering the reverse osmosis module are obtained in real time; the inflow water quality evaluation module obtains an inflow water quality evaluation coefficient; the temperature evaluation module is used for acquiring a temperature damage coefficient; the water quality influence analysis module obtains a water quality influence coefficient; the liquid flow rate matching module is used for acquiring the liquid flow rate matching strength of the water production speed and the concentrated water discharge speed; the water pressure determining module constructs a water pressure adjusting model based on the water inlet pressure and the liquid flow rate matching strength, outputs target water pressure and adjusts the water inlet pressure to the target water pressure; the water production speed and the concentrated water discharge speed can be matched according to the influence of water quality and temperature on the membrane so as to dynamically adjust the water inlet pressure.

Description

Technical Field

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

[0002] In recent years, with the growing 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 is widely used in the field of pure water preparation due to its efficient desalination ability. However, existing pure water treatment devices still face many technical bottlenecks in practical applications.

[0003] Traditional reverse osmosis modules usually rely on fixed parameters for operation and lack a dynamic assessment and control mechanism for influent water quality. For example, changes in influent turbidity, solute concentration and other indicators can easily lead to membrane fouling and scaling, seriously affecting membrane flux and service life. In addition, the impact of water temperature fluctuations on membrane material performance is often overlooked. Excessively high temperatures may cause membrane material expansion or a decrease in desalination rate, while sudden temperature changes can instantly destroy membrane flux stability. In the prior art, although some devices have introduced pretreatment units (such as multi-media filters, activated carbon adsorption, etc.), they lack comprehensive evaluation based on real-time water quality data, making it difficult to adjust pretreatment strategies in a timely manner, resulting in the membrane system being in non-optimal conditions for a long time.

[0004] On the other hand, water inlet pressure regulation mostly relies on empirical formulas or static threshold control, which cannot adapt to dynamic interference factors such as pH value and pressure fluctuations. The matching problem between water production rate and concentrated water discharge rate has not been effectively solved, and the system efficiency is often reduced or energy consumption is increased due to flow rate mismatch. Some technologies try to adjust 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, affecting system stability. Summary of the invention

[0005] In view of the deficiencies in 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 objectives, the present invention is implemented 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, 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; Influent water quality assessment module, which builds an influent water quality assessment model based on influent turbidity and solute concentration to obtain influent water quality assessment coefficient; Temperature evaluation module, which builds a temperature damage model based on water temperature and temperature fluctuation values ​​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.

[0007] On the basis of the above technical solution, the present invention also provides the following optional technical solution: Further technical solution: The steps of constructing 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: , represents the water quality evaluation coefficient, represents the turbidity index, represents the solute concentration index, represents the weight of turbidity index and solute concentration index and ; The obtained water quality evaluation coefficient is compared with the preset water quality coefficient threshold. If the water quality evaluation coefficient is within the water quality 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.

[0008] Further technical solution: The role of is to quantify the direct effect of turbidity on membrane fouling. The role of is to quantify the dominant effect of dissolved salts on membrane fouling and osmotic pressure.

[0009] Further technical solution: The specific steps of constructing a temperature damage model based on water temperature and temperature fluctuation value to obtain the temperature damage coefficient are: 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: , represents the temperature damage coefficient, Indicates the current temperature. Indicates the maximum allowable temperature, The temperature fluctuation value is equal to the difference between the current temperature value and the average temperature value ( ), represents the temperature level weight, represents the temperature fluctuation weight, 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.

[0010] Further technical solutions: The effect is that the temperature may cause the membrane material to expand or the desalination rate to decrease. The role of is to capture the instantaneous effect of temperature mutation on membrane flux. The role of is to determine the exponential function The corresponding sensitivity to temperature fluctuations.

[0011] Further technical solution: The water quality impact model is expressed as: , represents the water quality impact coefficient, represents the water quality evaluation coefficient, Indicates the temperature evaluation coefficient.

[0012] Further technical solution: The specific steps for obtaining the liquid flow rate matching strength are: Obtain pH influencing factor and water inlet pressure fluctuation factor based on current pH value and water inlet pressure fluctuation; The pH value influencing factor, water inlet pressure fluctuation factor, water production rate, concentrated water discharge rate and water quality influencing factor are introduced into the constructed liquid matching model to output the liquid matching strength. The liquid matching model is expressed as: Indicates the liquid matching strength, Indicates the current water production rate. Indicates the current concentrated water discharge speed. Indicates the pH value influencing factor, represents the pressure fluctuation influence factor, represents the water quality influencing factor, It represents the covariance term between the water production rate and the concentrate discharge rate.

[0013] Further technical solution: The specific steps of adjusting the water inlet 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: Indicates the target water pressure, Indicates the current water inlet pressure. represents the proportionality coefficient, Represents the mean of the upper and lower intensity threshold values, Indicates the liquid flow rate matching strength.

[0014] Further technical solution: 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 fluctuations Negative impact on system stability, Indicates the current water inlet pressure. Indicates the mean of the allowable pressure range.

[0015] Further technical solution: 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.

[0016] 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: 1. The present application provides a pure water treatment system for producing electrolyte hydrogen water, which can dynamically collect water quality parameters and construct a multi-dimensional evaluation model to adjust the water inlet pressure and pretreatment strategy in real time. It can match the water production rate and the concentrate discharge rate according to the influence of water quality parameters on the membrane and then dynamically adjust the water inlet pressure. It effectively solves the problems of membrane pollution, low water production efficiency and high energy consumption caused by fixed parameters of traditional reverse osmosis modules, and has the advantages of improving system stability, extending membrane service life and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The figure is a schematic diagram of the working process of the water inlet pressure regulating system of the present invention.

[0018] Figure 2 It is a three-dimensional surface diagram of the water quality assessment model in an embodiment of the present invention.

[0019] Figure 3It is a temperature damage model curve diagram in an embodiment of the present invention.

[0020] Figure 4 It is a three-dimensional surface diagram of the water quality impact model in the embodiment of the present invention.

[0021] Figure 5 It is a three-dimensional surface diagram of the liquid matching model in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0023] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0024] See also Figure 1 , provided in one embodiment of the present invention, is a pure water treatment system for producing electrolyte hydrogen water, comprising a water quality pretreatment module and a reverse osmosis module, and also comprising: 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; Influent water quality assessment module, which builds an influent water quality assessment model based on influent turbidity and solute concentration to obtain influent water quality assessment coefficient; Temperature evaluation module, which builds a temperature damage model based on water temperature and temperature fluctuation values ​​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.

[0025] Preferably, the steps of constructing an influent water quality assessment model based on influent turbidity and solute concentration to obtain an 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: , Represents the water quality evaluation coefficient and the , represents the turbidity index, represents the solute concentration index, represents the weight of turbidity index and solute concentration index and , The role of turbidity is to quantify the direct impact of turbidity on membrane fouling (such as suspended matter blocking membrane pores). The role of is to quantify the dominant effect of dissolved salts on membrane scaling and osmotic pressure. In this example, , , The three-dimensional surface diagram of the water quality assessment model under this condition is as follows Figure 2 As shown (low risk in blue to high risk in red); The obtained water quality evaluation coefficient is compared with the preset water quality coefficient threshold. If the water quality evaluation coefficient is within the water quality coefficient threshold, the raw water quality entering the reverse osmosis module is adjusted (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.

[0026] Specifically, when raw water enters the reverse osmosis module, turbidity and solute concentration data are collected in real time and normalized and converted into dimensionless indices. Through the weighted calculation model, the turbidity index and solute concentration index are combined into a single evaluation coefficient according to the preset weight. This coefficient dynamically reflects the comprehensive threat level 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 increases abnormally and causes When the value increases, the system will trigger the replacement of ion exchange resins first; when the turbidity index rises due to the increase of suspended matter, the multi-media filter backwashing procedure will be started. Through real-time evaluation and timely intervention, pollutants can be effectively prevented from accumulating on the membrane surface to form an irreversible pollution layer. Compared with the existing technology, the traditional method only judges whether a single indicator exceeds the standard through a fixed threshold, and cannot quantify the comprehensive impact of complex pollution. For example, the existing technology may monitor whether the turbidity exceeds 5NTU or whether the TDS exceeds 500ppm separately, but ignores the synergistic effect produced when the two are superimposed. This solution establishes a dynamic evaluation model, which not only considers the real-time changes of the two indicators, but also accurately reflects the differences in the impact of different pollutants on membrane performance through weight allocation. When the turbidity is normal but the solute concentration is critical, the existing technology may misjudge it as a safe state, while this solution can identify potential scaling risks in advance and initiate preventive measures through the weight amplification effect of the solute concentration index β. Through the above technical solution, this application realizes the dynamic evaluation and timely regulation of influent water quality, and solves the problem of lagging membrane pollution control caused by the lack of comprehensive water quality evaluation in traditional reverse osmosis modules. Through normalization processing and weight distribution mechanism, the synergistic pollution effect of suspended particles and dissolved salts can be accurately quantified; through dynamic comparison of preset thresholds, it is ensured that the pretreatment system adjustment is completed before the pollutant concentration reaches the critical value; through and The complementary constraints balance the prevention and control priorities of physical pollution and chemical scaling, avoiding the decrease in system stability caused by single indicator regulation. Preferably, the specific steps of constructing a temperature damage model based on the water temperature and the temperature fluctuation value to obtain the temperature damage coefficient are: 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: , represents the temperature damage coefficient, Indicates the current temperature. Indicates the maximum allowable temperature, The temperature fluctuation value is equal to the difference between the current temperature value and the average temperature value ( ), represents the temperature level weight, represents the temperature fluctuation weight, =1, represents the attenuation coefficient, The effect is that the temperature may cause the membrane material to expand or the desalination rate to decrease. The role of is to capture the instantaneous effect of temperature mutation on membrane flux. The role of is to determine the exponential function The corresponding sensitivity to temperature fluctuations, in this embodiment, =0.7, , , , Under this condition, the temperature damage model curve is as follows: Figure 3 As shown; 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.

[0027] Among them, the current water temperature refers to the real-time temperature data of the water inlet of the reverse osmosis module, which can be collected by a temperature sensor and transmitted to the data acquisition module to characterize the instantaneous temperature level of the environment in which 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 set by the technical parameters provided by the membrane material supplier to determine 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 achieved by calculating the temperature mean of several previous cycles using a sliding average algorithm to quantify the severity of temperature changes. The temperature level weight and temperature fluctuation weight refer to the proportional coefficients assigned to the absolute value and fluctuation value of the temperature respectively, which can be achieved by using preset parameters with a numerical range of 0.5-0.8 to adjust the contribution of the temperature absolute value exceeding the standard and the temperature mutation to the membrane damage. The attenuation coefficient refers to the adjustment factor of the exponential function, which can be achieved by using preset parameters of 0.1-0.3 to control the nonlinear influence of temperature fluctuation on the damage coefficient.

[0028] 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 absolute value of high temperature, the temperature fluctuation weight is set to 0.3 to strengthen the instantaneous impact of temperature mutation, and 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 absolute value of the temperature 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), the temperature damage coefficient is calculated by substituting it into the model. When the coefficient exceeds the preset threshold, the cooling device is triggered to cool the inlet water, and the heater power is adjusted to suppress subsequent temperature fluctuations.

[0029] Compared with the existing technology, the traditional method only triggers temperature adjustment through the temperature absolute value threshold, and cannot identify the cumulative damage and instantaneous impact of temperature fluctuations on membrane materials. For example, in the case of constant high temperature but no fluctuation, the existing technology may misjudge it as a safe state, while this solution identifies the risk of material performance degradation caused by stable high temperature through the temperature fluctuation term. When encountering periodic temperature mutations, the existing technology cannot distinguish between short-term fluctuations and long-term trends, while this solution separates the real abnormal temperature fluctuations through the sliding average algorithm.

[0030] Through the above technical solution, the present application can dynamically identify the dual risks of exceeding the absolute temperature 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 impact of the temperature fluctuation term through an exponential function, triggers temperature stabilization measures in advance, and avoids membrane damage caused by regulation lag in traditional methods. At the same time, the weight distribution mechanism is used to distinguish the degree of harm of long-term high temperature and short-term mutation, and optimize the response strategy of the temperature regulation system.

[0031] The present application further proposes to quantitatively control temperature-related risks by jointly acting on the temperature level weight, temperature fluctuation weight and attenuation coefficient in the temperature damage model, wherein the temperature level weight is used to evaluate the thermal damage risk of water temperature to membrane materials, the temperature fluctuation weight is used to monitor the impact effect of temperature mutation on membrane flux, and the attenuation coefficient is used to adjust the response gradient of the model to temperature fluctuations.

[0032] The temperature level weight refers to the degree to which the water temperature deviates from the maximum allowable temperature. Specifically, the normalized temperature ratio can be used as the calculation basis to convert the difference between the actual temperature and the safety threshold into a risk index for membrane material damage. This weight can prevent the membrane material from expanding or desalination performance attenuation due to continuous high temperature by quantifying the risk contribution of the absolute value of the temperature.

[0033] The temperature fluctuation weight refers to the evaluation parameter of the instantaneous temperature change amplitude. 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 membrane flux. This weight can identify the mutation event that causes a sudden drop in membrane flux by dynamically tracking the temperature fluctuation trajectory.

[0034] The attenuation coefficient refers to the adjustment factor of the exponential function's sensitivity to temperature fluctuations. Specifically, the preset exponential basis adjustment parameter can be used to control the degree to which the model amplifies or suppresses temperature fluctuations. This coefficient can both strengthen the hazard signal of significant temperature fluctuations and filter out the noise interference of small fluctuations by adjusting the curvature characteristics of the exponential term.

[0035] Specifically, the temperature damage model uses the temperature level weight to calculate the ratio of the real-time temperature to the maximum allowable temperature, and establishes a quantitative relationship between the thermal damage risk of the membrane material and the absolute value of the temperature. When the water temperature approaches or exceeds the safety threshold, the weight triggers the membrane protection mechanism. The temperature fluctuation weight calculates the difference between the current temperature and the average temperature during the operation cycle to establish a correlation model between the amplitude of temperature mutation and membrane flux fluctuation. 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 it is set to 0.9, the model output value of small temperature changes can be moderately reduced, while when it is set to 1.1, the risk warning of severe temperature fluctuations can be strengthened. The synergistic effect of these three enables the model to not only evaluate the membrane performance degradation caused by long-term high temperature, but also capture the flux oscillation caused by short-term temperature mutations.

[0036] Compared with existing technologies, existing solutions usually only monitor whether the temperature exceeds the threshold, cannot distinguish the difference between the absolute temperature risk and the dynamic fluctuation risk, and lack multi-dimensional evaluation of temperature mutation events. This solution introduces independent parameters for temperature level weight and temperature fluctuation weight to achieve hierarchical quantification of static temperature level and dynamic temperature fluctuation, and uses the attenuation coefficient to adjust the model response characteristics, so that the temperature damage assessment has both sensitivity and anti-interference ability.

[0037] Through the above technical solution, this application effectively alleviates the problems of membrane material expansion and reduced desalination rate caused by high temperature environment, and triggers the protection mechanism by calculating in real time the degree of temperature deviation from the safety threshold. At the same time, the model's ability to quickly identify temperature mutation events can reduce the instantaneous fluctuation amplitude of membrane flux, and the parameterized design of the attenuation coefficient enables the system to dynamically adjust the temperature sensitivity according to different working conditions to avoid misjudgment caused by environmental noise. This solution achieves precise prevention and control of temperature-related damage to reverse osmosis membranes through a hierarchical and multi-dimensional temperature risk assessment mechanism.

[0038] Preferably, the water quality impact model is expressed as: , represents the water quality impact coefficient, represents the water quality evaluation coefficient, represents the temperature evaluation coefficient. Based on the temperature damage coefficient output by the temperature damage model and the water quality evaluation coefficient output by the water quality evaluation model, the three-dimensional surface diagram of the water quality impact model is as follows: Figure 4 As shown (low risk in blue to high risk in red).

[0039] The present application further proposes a water quality impact model represented by a water quality impact coefficient equal to the superimposed impact of a water quality evaluation coefficient and a temperature evaluation coefficient, wherein the water quality impact coefficient is used to quantitatively evaluate the synergistic impact of dynamic changes in influent water quality and temperature fluctuations.

[0040] Specifically, the water quality evaluation coefficient reflects the risk of suspended matter clogging and the tendency of dissolved salt scaling through normalized turbidity and solute concentration data, respectively, and the temperature evaluation coefficient amplifies the influence of temperature fluctuations on the thermal expansion of membrane materials through an exponential function. The two coefficients are geometrically superimposed and corrected for synergistic effects to form a water quality influence coefficient, so that when high turbidity and high temperature fluctuations exist at the same time, a significantly increased comprehensive influence value is produced, and when a single indicator is abnormal, the synergistic effect can still maintain a linear transfer of the influence degree through geometric superposition correction. The calculation results of the model are passed to the liquid flow rate matching module as the input parameter for the dynamic adjustment of the water production rate and the concentrate discharge rate, ensuring that the synergistic negative effects of water quality deterioration and temperature anomalies are compensated for during the pressure regulation process.

[0041] Compared with the existing technology, the existing reverse osmosis modules usually use independent parameter threshold control, such as setting a separate turbidity over-limit alarm or temperature over-limit protection, but it is impossible to quantify the comprehensive damage to membrane performance caused by the coupling of multiple factors. However, this solution establishes a mathematical model of geometric superposition correction synergy effect, so that water quality parameters and temperature parameters produce nonlinear interactions at the algorithm level, which can accurately reflect the superposition effect of high turbidity and temperature mutation, and avoid the misjudgment of a single parameter reaching the standard but having a comprehensive impact exceeding the limit.

[0042] Through the above technical solution, the present application can quantify the synergistic effect strength of influent water quality fluctuation and temperature change in real time, provide accurate multi-factor impact assessment data for the reverse osmosis module, enable the influent pressure regulation process to perform compensation control for complex abnormal working conditions, and effectively prevent the membrane flux drop or desalination rate attenuation caused by multi-parameter dynamic coupling. Preferably, a liquid matching model is constructed 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 compare it with a preset strength threshold. If the liquid flow rate matching strength is not within the matching strength threshold, the specific steps of forming the judgment information are as follows: According to the current pH value and the inlet pressure fluctuation, the pH influencing factor and the inlet pressure fluctuation factor are obtained. 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 fluctuations Negative impact on system stability, is the current water inlet pressure, Indicates the mean of the allowable range of pressure; The pH value influencing factor, water inlet pressure fluctuation factor, water production rate, concentrated water discharge rate and water quality influencing factor are introduced into the constructed liquid matching model to output the liquid matching strength. The liquid matching model is expressed as: Indicates the liquid matching strength and the , Indicates the current water production rate. Indicates the current concentrated water discharge speed. Indicates the pH value influencing factor, represents the pressure fluctuation influence factor, represents the water quality influencing factor, The covariance term representing the water production rate and the brine discharge rate (its function is to measure the degree of synchronization between the water production rate and the brine discharge rate based on the deformation of the Pearson correlation coefficient. The significance of taking the absolute value of the numerator is to only focus on the fluctuation synchronization. The denominator is the product of the standard deviation to map the result to the interval of 0-1, indicating the matching strength). Under the conditions of the above-mentioned water quality assessment model and water quality impact model, the three-dimensional surface diagram of the liquid matching model is as follows: Figure 5 As shown (blue low match to red high match); The liquid flow rate matching strength is compared with a preset strength threshold, and if the liquid flow rate matching strength is not within the matching strength threshold, judgment information is formed.

[0043] The pH influencing factor refers to a parameter that quantifies the degree of pH deviation from neutrality. Specifically, it can be achieved by normalizing the difference between the absolute value of the pH value and the preset neutral value, which is used to inhibit the reduction of membrane flux in acidic or alkaline environments.

[0044] Among them, the pressure fluctuation influencing factor refers to the parameter that characterizes the instability of the inlet water pressure and is used to evaluate the interference intensity of pressure fluctuation on the membrane separation process.

[0045] The covariance term of the water production rate and the concentrate discharge rate refers to the mathematical representation of the dynamic equilibrium relationship between the two. It can be obtained by calculating the covariance of the real-time water production rate and the concentrate discharge rate, and is used to capture the synchronization difference of the flow rate changes between the two.

[0046] Specifically, the pH sensor collects the pH value data of the inlet water in real time, generates the pH value influencing factor after normalization, and the pressure sensor synchronously monitors the inlet water pressure fluctuation and calculates the pressure fluctuation influencing factor. The water quality influencing factor output by the water quality monitoring module is input into the liquid matching model together with the real-time water production rate and the concentrate discharge rate. In the model, the pH value influencing factor and the pressure fluctuation influencing factor are used as inhibition items to punish the working conditions that deviate from the neutral environment and the pressure instability respectively; the water quality influencing factor is used as an adjustment item to dynamically correct the reference flow rate ratio of the produced water and the concentrate; the covariance term of the water production rate and the concentrate discharge rate is used to characterize the degree of coordination between the flow rate changes of the two. When the liquid matching strength exceeds the preset threshold, the system automatically triggers the water pressure regulation mechanism, and dynamically adjusts the inlet water pressure to restore the water production rate and the concentrate discharge rate to a balanced state.

[0047] Compared with the existing technology, the traditional method only relies on a single parameter static threshold to control flow rate matching, ignoring the dynamic coupling effect of pH value changes and pressure fluctuations. For example, the pressure regulation in the existing technology only considers the current water production, and does not include the membrane flux attenuation caused by pH value deviation into the calculation, resulting in regulation lag. However, this solution establishes a multi-factor collaborative model to nonlinearly associate the pH value deviation degree, pressure fluctuation amplitude and water quality parameters, thereby achieving accurate quantification of the dynamic balance between water production rate and concentrate discharge rate, effectively solving the problem that the static control method cannot adapt to complex working conditions.

[0048] Through the above technical scheme, the present application can sense in real time the interference of pH value deviation and pressure fluctuation on flow rate matching, and dynamically correct the water inlet pressure parameters so that the water production rate and the concentrate discharge rate can still maintain the best matching state in an acidic or alkaline environment, thereby avoiding the aggravation of membrane pollution and abnormal increase in energy consumption due to flow rate mismatch, and at the same time enhancing the system's adaptive ability to cope with fluctuations in inlet water quality.

[0049] Preferably, the specific steps of 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: Indicates the target water pressure, Indicates the current water inlet pressure. It represents the proportionality factor (the proportionality factor that controls the adjustment range of the inlet pressure. Its function is to avoid the mechanical impact of sudden pressure changes on the membrane. Too large will cause oscillation). Represents the mean of the upper and lower intensity threshold values, Indicates the liquid flow rate matching strength.

[0050] The current inlet water pressure refers to the real-time pressure value at the inlet of the reverse osmosis membrane assembly, which can be collected in real time by a pressure sensor and used as an adjustment reference to ensure the continuity of the adjustment process.

[0051] The proportionality coefficient refers to a control parameter of the pressure adjustment range, and specifically can be a constant in a preset range, such as 0.5 to 1.5, to balance the adjustment response speed and system stability.

[0052] The mean value of the intensity threshold refers to the middle value of the standard range of the matching intensity between the water production rate and the concentrate discharge rate, which can be obtained through statistics of historical operation data as a reference for judging whether the matching status deviates from the normal range.

[0053] Among them, the liquid flow rate matching intensity refers to the dynamic coordination degree between the produced water and concentrated water discharge rates calculated by the mathematical model. Specifically, the covariance algorithm can be used to quantify the flow rate correlation between the two to reflect the real-time status of the system operation efficiency.

[0054] Specifically, when the water pressure determination module receives the judgment information that the liquid flow rate matching strength deviates from the strength threshold mean, the real-time collected water inlet pressure and matching strength data are input into the adjustment model. Calculate target water pressure: Current inlet water pressure As a base value, match strength difference Reflects the degree of deviation between the actual operating status and the standard range, the proportionality coefficient Controls the pressure adjustment range. For example, when the liquid flow rate matches the intensity Below average When, the difference is a positive value, the target water pressure Based on the current pressure By proportionality factor Increase, thereby increasing the water production rate to restore flow rate matching. This model converts the dynamic deviation of matching strength into pressure adjustment to achieve closed-loop control of water inlet pressure and avoid regulation lag caused by relying on fixed thresholds.

[0055] Compared with the existing technology, the traditional method uses static pressure threshold or empirical formula adjustment, which cannot respond to the membrane flux fluctuation caused by pH value change and the matching strength deviation caused by pressure disturbance. This solution establishes a real-time mathematical model of matching strength and pressure adjustment, quantifies the flow rate coordination state into a calculable parameter, and forms a dynamic corresponding relationship between the pressure adjustment amount and the actual operation deviation of the system. For example, when the inlet pressure fluctuates suddenly, the matching strength The real-time changes will directly affect the adjustment formula The existing technology needs to wait until the pressure fluctuation exceeds a fixed threshold before triggering the adjustment, which results in obvious response delay.

[0056] Through the above technical solution, the present application can automatically calculate the optimal water inlet pressure according to the real-time matching status of the water production and concentrated water discharge speed, effectively eliminating the flow rate mismatch problem caused by pH value mutation or pressure disturbance. By dynamically adjusting the pressure parameters, the reverse osmosis module can maintain the balance between water production efficiency and energy consumption under complex working conditions, avoid damage to the membrane components caused by pressure overshoot, and significantly improve the system operation stability.

[0057] 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, the activated carbon filter, the multi-media filter and the precision filter in the water quality pretreatment module.

[0058] Among them, the resin filter refers to a filtration unit constructed with ion exchange resin materials, which can be specifically implemented with sulfonic acid cation exchange resins, and is used to selectively adsorb calcium and magnesium ions in raw water to reduce solute concentrations. The activated carbon filter refers to an adsorption device filled with granular activated carbon, which can be specifically implemented with coconut shell-based activated carbon, and intercepts organic pollutants and residual chlorine substances through physical adsorption. The multi-media filter refers to a deep filtration layer composed of quartz sand and anthracite of different particle sizes, which can be specifically implemented with graded filter materials with a particle size gradient of 1.6-0.8mm, and is used to intercept suspended particles and reduce turbidity. The precision filter refers to a terminal filtration device equipped with a microporous filter membrane, which can be specifically implemented with a 5μm pore size polypropylene folded filter element, which is used to intercept colloidal substances to ensure the cleanliness of the incoming water.

[0059] Specifically, when real-time monitoring shows that the solute concentration exceeds the standard, the ion exchange resin filter is replaced to improve the removal rate of calcium and magnesium ions. If an abnormal increase in turbidity is detected, the coarse filter 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 exceeds the threshold, the failed carbon layer in the activated carbon filter is replaced with a fresh adsorption medium. In the case of fluctuations in the colloidal silica content, the filter element accuracy 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 with a quick-release buckle.

[0060] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0061] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that 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; Influent water quality assessment module, which builds an influent water quality assessment model based on influent turbidity and solute concentration to obtain influent water quality assessment coefficient; Temperature evaluation module, which builds a temperature damage model based on water temperature and temperature fluctuation values ​​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: Represents the water quality evaluation coefficient and the , represents the turbidity index, represents the solute concentration index, represents the weight of turbidity index and solute concentration index and ; The obtained water quality evaluation coefficient is compared with the preset water quality coefficient threshold. If the water quality evaluation coefficient is within the water quality 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: Said The role of is to quantify the direct effect of turbidity on membrane fouling. The role of is to quantify the dominant effect of dissolved salts on membrane fouling 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: represents the temperature damage coefficient, Indicates the current temperature. Indicates the maximum allowable temperature, The temperature fluctuation value is equal to the difference between the current temperature value and the average temperature value. represents the temperature level weight, represents the temperature fluctuation weight, 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 effect is that the temperature may cause the membrane material to expand or the desalination rate to decrease. The role of is to capture the instantaneous effect of temperature mutation on membrane flux. The role of is to determine the exponential function 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: represents the water quality impact coefficient, represents the water quality evaluation coefficient, Indicates the temperature evaluation 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 influencing factor and water inlet pressure fluctuation factor based on current pH value and water inlet pressure fluctuation; The pH value influencing factor, water inlet pressure fluctuation factor, water production rate, concentrated water discharge rate and water quality influencing factor are introduced into the constructed liquid matching model to output the liquid matching strength. The liquid matching model is expressed as: Indicates the liquid matching strength and , Indicates the current water production rate. Indicates the current concentrated water discharge speed. Indicates the pH value influencing factor, represents the pressure fluctuation influence factor, represents the water quality influencing factor, 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: Indicates the target water pressure, Indicates the current water inlet pressure. represents the proportionality coefficient, Represents the mean of the upper and lower intensity threshold values, 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 fluctuations Negative impact on system stability, 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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