Online intelligent cleaning control method and system for reverse osmosis device

Abstract

The invention discloses an online intelligent cleaning control method and system for a reverse osmosis device, and the method comprises the steps: obtaining and evaluating the water inlet working condition data of the reverse osmosis device, and obtaining a water inlet state evaluation value; acquiring and evaluating water quality index data influencing scaling of the reverse osmosis device in the circulating water to obtain a water quality state evaluation value; comprehensively determining a scaling degree value of the reverse osmosis device based on the water inlet state evaluation value and the water quality state evaluation value, and determining a cleaning working condition of the cleaning device according to the scaling degree value; after running for a period of time according to the cleaning working condition, re-determining the scaling degree value of the reverse osmosis device, and determining a working condition correction coefficient based on the difference between the two scaling degree values; and correcting the cleaning working condition of the cleaning device according to the working condition correction coefficient, and then controlling the cleaning device to clean the reverse osmosis device. According to the invention, scaling and pollution blockage of the reverse osmosis device can be found and controlled in time, the operation efficiency and the water quality stability are improved, the maintenance cost is reduced, and the fault risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of reverse osmosis device cleaning, and in particular to an online intelligent cleaning control method and system for a reverse osmosis device. Background Art

[0002] Reverse osmosis devices are commonly used treatment systems in the desalted water preparation process and water reuse and concentration process. With the continuous tightening of environmental protection policies in various regions, the utilization rate of urban water by various power generation companies has continued to increase, and there are more and more cases of reverse osmosis for urban water treatment. In the reuse of urban water, due to the complexity of urban water quality, reverse osmosis is often blocked by scale. The scale is usually a composite scale of organic and inorganic substances, and the cleaning process is also more difficult. At the same time, with the popularization of zero wastewater discharge requirements, reverse osmosis devices have also begun to be widely used for deep concentration and reduction of circulating water. Reverse osmosis devices will also be blocked more frequently, and the composition of the scale in the blockage also varies greatly.

[0003] Therefore, when the reverse osmosis device is used to treat urban recycled water and circulating water, there are usually problems such as frequent RO fouling and frequent cleaning. If an offline cleaning method is used, it will not only be time-consuming and labor-intensive, affecting the normal operation process, but also have poor cleaning effects, resulting in a significant shortening of the water production cycle. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an online intelligent cleaning control method and system for a reverse osmosis device, comprising: Acquire the water inlet condition data of the reverse osmosis device, analyze and evaluate the water inlet condition data, and obtain the water inlet state evaluation value of the reverse osmosis device; Obtain water quality index data in circulating water that affects scaling of reverse osmosis devices, analyze and evaluate the water quality index data, and obtain a water quality status evaluation value of circulating water; Comprehensively determine the scaling degree value of the reverse osmosis device based on the water inlet state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, and determine the cleaning working conditions of the cleaning device according to the scaling degree value; Re-determine the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determine the working condition correction coefficient based on the difference between the scaling degree values ​​before and after; The cleaning working conditions of the cleaning device are corrected according to the working condition correction coefficient, and the cleaning device is controlled to clean the reverse osmosis device according to the corrected working conditions.

[0005] Furthermore, the acquisition of the water inlet condition data of the reverse osmosis device, and the analysis and evaluation of the water inlet condition data to obtain the water inlet state evaluation value of the reverse osmosis device include: Obtaining water inlet condition data of the reverse osmosis device within a preset time, the water inlet condition data including water inlet pressure data and water inlet flow data; Determine the data value of each data in the water inlet pressure data and the water inlet flow data respectively, and calculate the average value according to the data value of each data in the water inlet pressure data and the water inlet flow data respectively, to obtain the average water inlet pressure value and the average water inlet flow value respectively; The average water inlet pressure value and the average water inlet flow value are evaluated and valued respectively, and the average water inlet pressure evaluation value and the average water inlet flow evaluation value are obtained respectively; The maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data are obtained respectively, and the range values ​​are calculated according to the maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data respectively, so as to obtain the water inlet pressure range value and the water inlet flow range value respectively; The water inlet pressure extreme difference value and the water inlet flow extreme difference value are evaluated and valued respectively, and the water inlet pressure extreme difference evaluation value and the water inlet flow extreme difference evaluation value are obtained respectively; The water inlet state evaluation value of the reverse osmosis device is determined according to the average water inlet pressure evaluation value, the average water inlet flow evaluation value, the water inlet pressure extreme difference evaluation value, and the water inlet flow extreme difference evaluation value, wherein the calculation formula of the water inlet state evaluation value of the reverse osmosis device is: X=a*(P+M)+b*(Q+N), Among them, X is the water inlet state evaluation value of the reverse osmosis device, a is the first conversion coefficient, P is the average water inlet pressure evaluation value, M is the average water inlet flow evaluation value, b is the second conversion coefficient, Q is the water inlet pressure extreme difference evaluation value, and N is the water inlet flow extreme difference evaluation value.

[0006] Furthermore, the water quality index data in the circulating water that affects the scaling of the reverse osmosis device is obtained, and the water quality index data is analyzed and evaluated to obtain the water quality status evaluation value of the circulating water, including: Take the water quality index data that affects the scaling of the reverse osmosis device in the circulating water, which includes the calcium content data, iron content data, silicon content data and phosphorus content data; Determine the data value of each of the calcium content data, the iron content data, the silicon content data, and the phosphorus content data, respectively, and calculate the average value according to the data value of each of the calcium content data, the iron content data, the silicon content data, and the phosphorus content data, respectively, to obtain the average calcium content value, the average iron content value, the average silicon content value, and the average phosphorus content value; Obtaining a preset standard average calcium content value, a standard average iron content value, a standard average silicon content value, and a standard average phosphorus content value, and respectively calculating the differences between the standard average calcium content value, the standard average iron content value, the standard average silicon content value, and the standard average phosphorus content value and the average calcium content value, the average iron content value, the average silicon content value, and the average phosphorus content value, to obtain a calcium content difference value, an iron content difference value, a silicon content difference value, and a phosphorus content difference value, respectively; The calcium content difference value, the iron content difference value, the silicon content difference value and the phosphorus content difference value are evaluated and valued respectively, and the average calcium content evaluation value, the average iron content evaluation value, the average silicon content evaluation value and the average phosphorus content evaluation value are obtained respectively; The water quality status assessment value of the circulating water is calculated based on the average calcium content assessment value, the average iron content assessment value, the average silicon content assessment value and the average phosphorus content assessment value, wherein the calculation formula for the water quality status assessment value of the circulating water is: Y=(T+U+V+O) / 4, Among them, Y is the water quality status assessment value of circulating water, T is the average calcium content assessment value, U is the average iron content assessment value, V is the average silicon content assessment value, and O is the average phosphorus content assessment value.

[0007] Furthermore, the scaling degree value of the reverse osmosis device is comprehensively determined based on the water inlet state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, including: Obtaining an inlet water status evaluation value of the reverse osmosis device and a water quality status evaluation value of the circulating water, and determining preset weights corresponding to the inlet water status evaluation value and the water quality status evaluation value; The scaling degree value of the reverse osmosis device is calculated according to the influent state evaluation value, the water quality state evaluation value and the corresponding preset weights, wherein the calculation formula of the scaling degree value of the reverse osmosis device is: S=α*X+β*Y, Wherein, S is the scaling degree value of the reverse osmosis device, α is the preset weight of the water inlet state evaluation value of the reverse osmosis device, X is the water inlet state evaluation value of the reverse osmosis device, β is the preset weight of the water quality state evaluation value of the circulating water, and Y is the water quality state evaluation value of the circulating water.

[0008] Furthermore, the step of determining the cleaning working conditions of the cleaning device according to the scaling degree value includes: Obtaining the scaling degree value △G and the preset scaling degree preset value G0, and determining the preset preset difference g1, preset difference g2, third preset difference g3 and fourth preset difference g4, and g1<g2<g3<g4; presetting a preset working condition matrix A1 (a1, b1), a preset working condition matrix A2 (a2, b2), a third preset working condition matrix A3 (a3, b3) and a fourth preset working condition matrix A4 (a4, b4), wherein a1-a4 are sequentially to the fourth preset dosage, and a1<a2<a3<a4, b1-b4 are sequentially to the fourth preset cleaning temperature, and b1<b2<b3<b4; According to the difference between the scaling degree value △G and the preset scaling degree preset value G0, a preset working condition matrix Ai is selected as the working condition of the cleaning device; When △G-G0≤g1, the preset working condition matrix A1 is selected as the working condition of the cleaning device; When g1<△G-G0≤g2, the preset working condition matrix A2 is selected as the working condition of the cleaning device; When g2<△G-G0≤g3, the third preset working condition matrix A3 is selected as the working condition of the cleaning device; When g3<ΔG-G0≤g4, the fourth preset working condition matrix A4 is selected as the working condition of the cleaning device.

[0009] Further, the scaling degree value of the reverse osmosis device is re-determined after running for a period of time according to the cleaning working condition, and the working condition correction coefficient is determined based on the difference between the scaling degree values ​​before and after, including: After the cleaning device has been running for a period of time according to the cleaning working conditions, the scaling degree value of the reverse osmosis device is re-determined; Obtaining the last scaling degree value and the re-determined scaling degree value, calculating the difference between the last scaling degree value and the re-determined scaling degree value, and obtaining the scaling degree difference value; Presetting a corresponding relationship between a working condition correction coefficient and a scaling degree difference value interval, wherein the corresponding relationship between a working condition correction coefficient and a scaling degree difference value interval is associated with a corresponding working condition correction coefficient for each scaling degree difference value interval; The scaling degree difference value is obtained, and based on the mapping relationship between the scaling degree difference value interval to which the scaling degree difference value belongs within the difference coefficient-scaling degree difference value interval correspondence relationship, the working condition correction coefficient corresponding to the scaling degree difference value interval is selected as the working condition correction coefficient of the cleaning device.

[0010] Furthermore, the cleaning working condition of the cleaning device is corrected according to the working condition correction coefficient, and the cleaning device is controlled to clean the reverse osmosis device according to the corrected working condition, including: Obtain the working condition correction coefficient mi selected by the cleaning device, and correct the cleaning working condition matrix Ai (ai, bi) of the cleaning device according to the working condition correction coefficient mi. The corrected cleaning working condition matrix is ​​Ai (ai*mi, bi*mi); The corrected cleaning working condition matrix is ​​used as the working condition of the cleaning device, and the cleaning device is controlled according to the working condition to clean the reverse osmosis device.

[0011] The present invention also provides an online intelligent cleaning control system for a reverse osmosis device, comprising: The first acquisition module is used to acquire the water inlet condition data of the reverse osmosis device, and analyze and evaluate the water inlet condition data to obtain the water inlet state evaluation value of the reverse osmosis device; The second acquisition module is used to obtain water quality index data in the circulating water that affects the scaling of the reverse osmosis device, and analyze and evaluate the water quality index data to obtain a water quality status evaluation value of the circulating water; An analysis module, for comprehensively determining a scaling degree value of the reverse osmosis device based on an evaluation value of an inlet water state of the reverse osmosis device and an evaluation value of a water quality state of circulating water, and determining a cleaning working condition of a cleaning device according to the scaling degree value; A determination module, used to re-determine the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determine the working condition correction coefficient based on the difference between the two scaling degree values ​​before and after; The correction module is used to correct the cleaning working conditions of the cleaning device according to the working condition correction coefficient, and control the cleaning device to clean the reverse osmosis device according to the corrected working conditions.

[0012] Compared with the prior art, the online intelligent cleaning control method and system of a reverse osmosis device according to the embodiment of the present invention has the following beneficial effects: The present invention realizes effective integration and management of multi-source data by integrating the inlet working condition data of the reverse osmosis device and the water quality index data of the circulating water, and accurately grasps the operating status and scaling risk of the reverse osmosis device through data analysis and evaluation, providing a basis for subsequent decision-making; Based on the analysis and evaluation of water quality index data, the present invention can accurately evaluate the water quality of circulating water, timely discover factors that may cause scaling problems, and predict the scaling risk of the reverse osmosis device in combination with the water inlet condition data, formulate preventive measures in advance, and ensure the stable operation of the system. The present invention compares the scaling degree values ​​before and after cleaning to evaluate the cleaning effect, ensure that the scaling problem is effectively controlled, and optimize the cleaning working conditions according to the working condition correction coefficient, improve the cleaning efficiency, and reduce the cleaning cost and time; Based on data analysis and evaluation results, the present invention realizes comprehensive evaluation of the scaling degree value of the reverse osmosis device and intelligent decision support for cleaning working conditions, and based on the adjustment of the correction coefficient, realizes intelligent optimization of the cleaning working conditions, thereby improving the operating efficiency and reliability of the system; The present invention can perform online intelligent cleaning of the reverse osmosis device through data-driven automatic control, thereby improving stability and reliability, reducing the need for human intervention, and reducing operational risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 1 is a schematic diagram of the flow structure of an online intelligent cleaning control method for a reverse osmosis device according to an embodiment of the present invention; Figure 2 It is a schematic diagram of the composition of an online intelligent cleaning control system for a reverse osmosis device in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0015] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0016] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying a relative degree of importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0017] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technical personnel in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0018] like Figure 1 As shown, in an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, including: S100: obtaining water inlet condition data of the reverse osmosis device, and analyzing and evaluating the water inlet condition data to obtain a water inlet state evaluation value of the reverse osmosis device; S200: obtaining water quality index data in the circulating water that affects the scaling of the reverse osmosis device, and analyzing and evaluating the water quality index data to obtain a water quality state evaluation value of the circulating water; S300: comprehensively determining the scaling degree value of the reverse osmosis device based on the water inlet state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, and determining the cleaning working conditions of the cleaning device according to the scaling degree value; S400: re-determining the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determining the working condition correction coefficient based on the difference between the scaling degree values ​​before and after; S500: correcting the cleaning working conditions of the cleaning device according to the working condition correction coefficient, and controlling the cleaning device to clean the reverse osmosis device according to the corrected working conditions.

[0019] Furthermore, the present invention realizes effective integration and management of multi-source data by integrating the inlet working condition data of the reverse osmosis device and the water quality index data of the circulating water, and accurately grasps the operating status and scaling risk of the reverse osmosis device through analysis and evaluation of the data, providing a basis for subsequent decision-making; based on the analysis and evaluation of the water quality index data, the present invention realizes accurate evaluation of the water quality status of the circulating water, timely discovers factors that may cause scaling problems, and predicts the scaling risk of the reverse osmosis device in combination with the inlet working condition data, formulates preventive measures in advance, and ensures the stable operation of the system; the present invention evaluates the cleaning effect by comparing the scaling degree values ​​before and after cleaning, ensures that the scaling problem is effectively controlled, and optimizes the cleaning working conditions according to the working condition correction coefficient, improves the cleaning efficiency, and reduces the cleaning cost and time; based on the data analysis and evaluation results, the present invention realizes the comprehensive evaluation of the scaling degree value of the reverse osmosis device and the intelligent decision support of the cleaning working conditions, and based on the adjustment of the correction coefficient, realizes the intelligent optimization of the cleaning working conditions, and improves the operating efficiency and reliability of the system; the present invention can perform online intelligent cleaning of the reverse osmosis device through data-driven automatic control, improves stability and reliability, reduces the need for human intervention, and reduces operating risks.

[0020] In an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, wherein the water inlet condition data of the reverse osmosis device is obtained, and the water inlet condition data is analyzed and evaluated to obtain a water inlet state evaluation value of the reverse osmosis device, including: obtaining the water inlet condition data of the reverse osmosis device within a preset time, the water inlet condition data including water inlet pressure data and water inlet flow data; respectively determining the data value of each data in the water inlet pressure data and the water inlet flow data, and calculating the average value according to the data value of each data in the water inlet pressure data and the water inlet flow data, respectively obtaining an average water inlet pressure value and an average water inlet flow value; respectively evaluating and taking the average water inlet pressure value and the average water inlet flow value ... The average water inlet pressure evaluation value and the average water inlet flow evaluation value are obtained; the maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data are obtained respectively, and the range values ​​are calculated according to the maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data, respectively, to obtain the water inlet pressure range value and the water inlet flow range value; the water inlet pressure range value and the water inlet flow range value are evaluated and valued respectively, to obtain the water inlet pressure range value and the water inlet flow range value; the water inlet state evaluation value of the reverse osmosis device is determined according to the average water inlet pressure evaluation value and the average water inlet flow evaluation value as well as the water inlet pressure range value and the water inlet flow range value, wherein the calculation formula of the water inlet state evaluation value of the reverse osmosis device is: X=a*(P+M)+b*(Q+N), Among them, X is the water inlet state evaluation value of the reverse osmosis device, a is the first conversion coefficient, P is the average water inlet pressure evaluation value, M is the average water inlet flow evaluation value, b is the second conversion coefficient, Q is the water inlet pressure extreme difference evaluation value, and N is the water inlet flow extreme difference evaluation value.

[0021] Specifically, the water inlet condition data of the reverse osmosis device within a preset time is obtained, including the water inlet pressure data and the water inlet flow data, and each data in the water inlet pressure data and the water inlet flow data is extracted and processed to obtain the specific value of each data; the average values ​​of the water inlet pressure data and the water inlet flow data are respectively calculated to obtain the average water inlet pressure value and the average water inlet flow value; the maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data are respectively obtained, and the water inlet pressure extreme value and the water inlet flow extreme value are calculated; the average water inlet pressure value, the average water inlet flow value, the water inlet pressure extreme value and the water inlet flow extreme value are evaluated and valued to determine their specific values ​​within the evaluation range; according to the given calculation formula, the water inlet state evaluation value of the reverse osmosis device is calculated using the average water inlet pressure evaluation value, the average water inlet flow evaluation value, the water inlet pressure extreme value and the water inlet flow extreme value. This step realizes a comprehensive analysis of the water inflow of the reverse osmosis device by processing, calculating and evaluating the water inflow condition data, providing a basis for subsequent decision-making; combining the evaluation results of the average value and the extreme value, the water inflow status evaluation value of the reverse osmosis device is determined using the given calculation formula, which comprehensively considers the average level and fluctuation of the water inflow pressure and flow rate; the water inflow status evaluation value obtained by calculation provides an intuitive indicator for operators to help them understand the water inflow of the reverse osmosis device and adjust the operating parameters in time to ensure the normal operation of the system; this process is based on data-driven, and through the analysis and evaluation of the water inflow data, it provides a scientific and objective basis to help operation and maintenance personnel make accurate operation adjustments and decisions, thereby improving the efficiency and stability of the system. Combining the above technical effects, this process helps to realize the comprehensive evaluation and monitoring of the water inflow status of the reverse osmosis device, providing important support and guarantee for the stable operation of the system.

[0022] In an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, wherein water quality index data in circulating water that affects scaling of the reverse osmosis device is obtained, and the water quality index data is analyzed and evaluated to obtain a water quality status evaluation value of the circulating water, including: obtaining water quality index data in circulating water that affects scaling of the reverse osmosis device, the water quality index data including calcium content data, iron content data, silicon content data, and phosphorus content data; respectively determining the data value of each of the calcium content data, the iron content data, the silicon content data, and the phosphorus content data, and calculating the average value according to the data value of each of the calcium content data, the iron content data, the silicon content data, and the phosphorus content data, respectively, to obtain the average calcium content value, the average iron content value, the average silicon content value, and the average phosphorus content value; obtaining a preset standard average calcium content value, a standard average iron content value, a standard average silicon content value, and a standard average phosphorus content value. The standard average calcium content value, the standard average iron content value, the standard average silicon content value and the standard average phosphorus content value are calculated, and the differences between the standard average calcium content value, the standard average iron content value, the standard average silicon content value and the standard average phosphorus content value and the average calcium content value, the average iron content value, the average silicon content value and the average phosphorus content value are calculated respectively to obtain the calcium content difference value, the iron content difference value, the silicon content difference value and the phosphorus content difference value respectively; the calcium content difference value, the iron content difference value, the silicon content difference value and the phosphorus content difference value are evaluated and taken respectively to obtain the average calcium content evaluation value, the average iron content evaluation value, the average silicon content evaluation value and the average phosphorus content evaluation value respectively; the water quality status evaluation value of the circulating water is calculated according to the average calcium content evaluation value, the average iron content evaluation value, the average silicon content evaluation value and the average phosphorus content evaluation value, wherein the calculation formula of the water quality status evaluation value of the circulating water is: Y=(T+U+V+O) / 4, Among them, Y is the water quality status assessment value of circulating water, T is the average calcium content assessment value, U is the average iron content assessment value, V is the average silicon content assessment value, and O is the average phosphorus content assessment value.

[0023] Specifically, the calcium content, iron content, silicon content and phosphorus content data in the circulating water are collected; the collected data are processed to calculate the data value of each indicator, and the average calcium content value, the average iron content value, the average silicon content value and the average phosphorus content value are calculated; a predetermined standard average value is set, including a standard average calcium content value, a standard average iron content value, a standard average silicon content value and a standard average phosphorus content value; the difference between the standard average value and the actual average value is calculated to obtain a calcium content difference value, an iron content difference value, a silicon content difference value and a phosphorus content difference value; each difference value is evaluated to obtain an average calcium content evaluation value, an average iron content evaluation value, an average silicon content evaluation value and an average phosphorus content evaluation value; and the water quality status evaluation value of the circulating water is calculated based on the evaluation value. This step can timely understand the water quality status through the analysis and evaluation of key water quality indicators in the circulating water, which helps to prevent the occurrence of scaling problems in the reverse osmosis device; through the monitoring and evaluation of water quality data, timely adjustment measures can be taken to ensure that the quality of the circulating water meets the requirements, extend the service life of the equipment, and reduce maintenance costs; by establishing an evaluation system, the water quality evaluation process can be standardized, work efficiency and accuracy can be improved, a scientific basis can be provided for engineers and operators, the water treatment process can be optimized, and the stability and reliability of the system can be improved.

[0024] In an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, wherein the scaling degree value of the reverse osmosis device is comprehensively determined based on the inlet water state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, including: obtaining the inlet water state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, and determining the preset weights corresponding to the inlet water state evaluation value and the water quality state evaluation value; calculating the scaling degree value of the reverse osmosis device according to the inlet water state evaluation value and the water quality state evaluation value and the corresponding preset weights, wherein the calculation formula of the scaling degree value of the reverse osmosis device is: S=α*X+β*Y, Wherein, S is the scaling degree value of the reverse osmosis device, α is the preset weight of the water inlet state evaluation value of the reverse osmosis device, X is the water inlet state evaluation value of the reverse osmosis device, β is the preset weight of the water quality state evaluation value of the circulating water, and Y is the water quality state evaluation value of the circulating water.

[0025] Specifically, the water inlet status evaluation value of the reverse osmosis device and the water quality status evaluation value of the circulating water are obtained; the preset weights corresponding to the water inlet status evaluation value and the water quality status evaluation value, namely α and β, are determined. These weights can be set according to the actual situation and needs to measure the influence of different factors on the degree of scaling; the scaling degree value of the reverse osmosis device can be calculated by the formula. This step can quantitatively evaluate the scaling of the reverse osmosis device by calculating the scaling degree value, providing a basis for subsequent cleaning and maintenance; by setting the preset weights of the water inlet status evaluation value and the water quality status evaluation value, the influence of different factors can be adjusted according to the actual situation, so that the scaling degree value is more in line with the actual situation; taking into account the two aspects of the water inlet status and the water quality status, comprehensively evaluating the scaling of the reverse osmosis device helps to fully understand the operating status of the device and adjust the operation in time to ensure the normal operation of the equipment and extend its service life.

[0026] In an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, wherein the cleaning working condition of the cleaning device is determined according to the scaling degree value, including: obtaining the scaling degree value △G and a preset scaling degree preset value G0, and determining a preset preset difference g1, a preset difference g2, a third preset difference g3 and a fourth preset difference g4, and g1<g2<g3<g4; presetting a preset working condition matrix A1 (a1, b1), a preset working condition matrix A2 (a2, b2), a third preset working condition matrix A3 (a3, b3) and a fourth preset working condition matrix A4 (a4, b4), wherein a1-a4 are respectively a to a fourth preset dosage, and a1<a 2<a3<a4, b1-b4 is successively to the fourth preset cleaning temperature, b1<b2<b3<b4; according to the difference between the scaling degree value △G and the preset scaling degree preset value G0, the preset working condition matrix Ai is selected as the working condition of the cleaning device; when △G-G0≤g1, the preset working condition matrix A1 is selected as the working condition of the cleaning device; when g1<△G-G0≤g2, the preset working condition matrix A2 is selected as the working condition of the cleaning device; when g2<△G-G0≤g3, the third preset working condition matrix A3 is selected as the working condition of the cleaning device; when g3<△G-G0≤g4, the fourth preset working condition matrix A4 is selected as the working condition of the cleaning device.

[0027] Specifically, the scaling degree value △G and the preset scaling degree preset value G0 are obtained; preset differences g1, g2, g3, g4 are set, and g1<g2<g3<g4 are ensured. At the same time, preset working condition matrices A1 (a1, b1), A2 (a2, b2), A3 (a3, b3), A4 (a4, b4) are set, where a1-a4 represent the dosage, and b1-b4 represent the cleaning temperature, to ensure that these values ​​are in the set order; according to the difference between the scaling degree value △G and the preset scaling degree preset value G0, an appropriate preset working condition matrix Ai is selected as the working condition of the cleaning device, and an appropriate preset working condition matrix is ​​selected according to the set difference range. This step can realize automatic selection of the working conditions of the cleaning device by setting the preset difference and the working condition matrix, making the cleaning process more intelligent and efficient; according to the difference between the scaling degree value and the preset value, the most suitable working condition matrix is ​​selected to achieve accurate cleaning of the reverse osmosis device and avoid problems caused by excessive or insufficient cleaning; by adjusting the working conditions of the cleaning device according to actual conditions, resources such as water, energy and cleaning agents required in the cleaning process can be effectively saved, thereby improving cleaning efficiency and reducing costs.

[0028] In an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, wherein the scaling degree value of the reverse osmosis device is re-determined after a period of operation according to the cleaning working conditions, and the working condition correction coefficient is determined based on the difference between the two scaling degree values, including: the cleaning device re-determines the scaling degree value of the reverse osmosis device after a period of operation according to the cleaning working conditions; obtains the last scaling degree value and the re-determined scaling degree value, calculates the difference between the last scaling degree value and the re-determined scaling degree value, and obtains the scaling degree difference value; pre-sets a corresponding relationship between the working condition correction coefficient and the scaling degree difference value interval, wherein the corresponding relationship between the working condition correction coefficient and the scaling degree difference value interval is associated with a corresponding working condition correction coefficient for each scaling degree difference value interval; obtains the scaling degree difference value, and based on the mapping relationship between the scaling degree difference value interval to which the scaling degree difference value belongs within the corresponding relationship between the difference coefficient and the scaling degree difference value interval, selects the working condition correction coefficient corresponding to the scaling degree difference value interval as the working condition correction coefficient of the cleaning device.

[0029] Specifically, after the cleaning device has been running for a period of time according to the set working conditions, the scaling degree of the reverse osmosis device is re-evaluated to obtain a new scaling degree value; the previous scaling degree value and the re-determined scaling degree value are obtained, and the difference between them is calculated to obtain a scaling degree difference value, which is used to measure the change in the scaling degree; the correspondence between different scaling degree difference value intervals and working condition correction coefficients is pre-set to ensure that each scaling degree difference value interval has a corresponding working condition correction coefficient, which is used to adjust the working conditions of the cleaning device; according to the interval to which the scaling degree difference value belongs, the corresponding working condition correction coefficient is found in the corresponding relationship between the working condition correction coefficient and the scaling degree difference value interval, which is used as the working condition correction coefficient of the cleaning device, which is used to adjust the working conditions of the cleaning device. This step selects appropriate working condition correction coefficients according to the difference in scaling degree to achieve real-time adjustment of the working conditions of the cleaning device to cope with changes in scaling conditions of the reverse osmosis device. By selecting appropriate working condition correction coefficients according to the actual changes in scaling degree, the working conditions of the cleaning device can be accurately adjusted to ensure the best cleaning effect. By dynamically adjusting the working conditions, excessive cleaning or incomplete cleaning can be avoided, thereby saving resources required during the cleaning process, improving cleaning efficiency, and extending the service life of the equipment.

[0030] In an embodiment of the present application, an online intelligent cleaning control method for a reverse osmosis device is provided, wherein the cleaning working condition of the cleaning device is corrected according to the working condition correction coefficient, and the cleaning device is controlled to clean the reverse osmosis device according to the corrected working condition, including: obtaining the working condition correction coefficient mi selected by the cleaning device, and correcting the cleaning working condition matrix Ai (ai, bi) of the cleaning device according to the working condition correction coefficient mi, the corrected cleaning working condition matrix is ​​Ai (ai*mi, bi*mi); using the corrected cleaning working condition matrix as the working condition of the cleaning device, and controlling the cleaning device to clean the reverse osmosis device according to the working condition.

[0031] Specifically, according to the previous steps, a suitable working condition correction coefficient mi is selected, and the correction coefficient reflects the degree of adjustment required for the cleaning working conditions; according to the selected working condition correction coefficient mi, the cleaning working condition matrix Ai (ai, bi) is corrected, and the corrected cleaning working condition matrix is ​​Ai (ai*mi, bi*mi), that is, the parameters in the original cleaning working condition matrix are adjusted accordingly according to the correction coefficient; the corrected cleaning working condition matrix Ai (ai*mi, bi*mi) is used as the new working condition of the cleaning device, which is used to control the cleaning device to perform cleaning operations on the reverse osmosis device. In this step, by correcting the cleaning working condition matrix according to the working condition correction coefficient mi, the working conditions of the cleaning device can be accurately adjusted to ensure the effectiveness and efficiency of the cleaning process; the cleaning working conditions are dynamically adjusted according to the actual situation, so that the cleaning device can be adjusted in time according to the scaling of the reverse osmosis device, thereby improving the cleaning effect and extending the life of the equipment; the working condition correction coefficient mi is used to automatically adjust the cleaning working conditions, realize the intelligent control of the cleaning device on the reverse osmosis device, reduce manual intervention, and improve the automation of the cleaning process.

[0032] like Figure 2 As shown, in an embodiment of the present application, an online intelligent cleaning control system for a reverse osmosis device is provided, comprising: a first acquisition module, used to acquire water inlet condition data of the reverse osmosis device, and analyze and evaluate the water inlet condition data to obtain a water inlet state evaluation value of the reverse osmosis device; a second acquisition module, used to acquire water quality index data in the circulating water that affects the scaling of the reverse osmosis device, and analyze and evaluate the water quality index data to obtain a water quality state evaluation value of the circulating water; an analysis module, used to comprehensively determine the scaling degree value of the reverse osmosis device based on the water inlet state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, and determine the cleaning working conditions of the cleaning device according to the scaling degree value; a determination module, used to redetermine the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determine the working condition correction coefficient based on the difference between the scaling degree values ​​before and after; a correction module, used to correct the cleaning working conditions of the cleaning device according to the working condition correction coefficient, and control the cleaning device to clean the reverse osmosis device according to the corrected working conditions.

[0033] In summary, the embodiment of the present invention provides an online intelligent cleaning control method and system for a reverse osmosis device, which includes: obtaining and evaluating the water inlet working condition data of the reverse osmosis device to obtain a water inlet state evaluation value; obtaining and evaluating the water quality index data in the circulating water that affects the scaling of the reverse osmosis device to obtain a water quality state evaluation value; comprehensively determining the scaling degree value of the reverse osmosis device based on the water inlet state evaluation value and the water quality state evaluation value, and determining the cleaning working conditions of the cleaning device based on the scaling degree value; re-determining the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determining the working condition correction coefficient based on the difference between the scaling degree values ​​before and after; and controlling the cleaning device to clean the reverse osmosis device after correcting the cleaning working conditions of the cleaning device according to the working condition correction coefficient. The present invention can timely detect and control the scaling and fouling of the reverse osmosis device, improve the operating efficiency and water quality stability, reduce maintenance costs and reduce the risk of failure.

[0034] Finally, it should be noted that: Obviously, a person skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technology, the present invention is also intended to include these modifications and variations.

[0035] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Technical personnel in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0036] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0037] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings. However, it is easy for a person skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, a person skilled in the art can make equivalent changes or substitutions to closely related technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0038] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. An online intelligent cleaning control method for a reverse osmosis device, characterized in that: include: Acquire the water inlet condition data of the reverse osmosis device, analyze and evaluate the water inlet condition data, and obtain the water inlet state evaluation value of the reverse osmosis device; Obtain water quality index data in circulating water that affects scaling of reverse osmosis devices, analyze and evaluate the water quality index data, and obtain a water quality status evaluation value of circulating water; Comprehensively determine the scaling degree value of the reverse osmosis device based on the water inlet state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water, and determine the cleaning working conditions of the cleaning device according to the scaling degree value; Re-determine the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determine the working condition correction coefficient based on the difference between the scaling degree values ​​before and after; The cleaning working conditions of the cleaning device are corrected according to the working condition correction coefficient, and the cleaning device is controlled to clean the reverse osmosis device according to the corrected working conditions.

2. The online intelligent cleaning control method of a reverse osmosis device according to claim 1, characterized in that: The step of obtaining the water inlet condition data of the reverse osmosis device, analyzing and evaluating the water inlet condition data, and obtaining the water inlet state evaluation value of the reverse osmosis device includes: Obtaining water inlet condition data of the reverse osmosis device within a preset time, the water inlet condition data including water inlet pressure data and water inlet flow data; Determine the data value of each data in the water inlet pressure data and the water inlet flow data respectively, and calculate the average value according to the data value of each data in the water inlet pressure data and the water inlet flow data respectively, to obtain the average water inlet pressure value and the average water inlet flow value respectively; The average water inlet pressure value and the average water inlet flow value are evaluated and valued respectively, and the average water inlet pressure evaluation value and the average water inlet flow evaluation value are obtained respectively; The maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data are obtained respectively, and the range values ​​are calculated according to the maximum data value and the minimum data value in the water inlet pressure data and the water inlet flow data respectively, so as to obtain the water inlet pressure range value and the water inlet flow range value respectively; The water inlet pressure extreme difference value and the water inlet flow extreme difference value are evaluated and valued respectively, and the water inlet pressure extreme difference evaluation value and the water inlet flow extreme difference evaluation value are obtained respectively; The water inlet state evaluation value of the reverse osmosis device is determined according to the average water inlet pressure evaluation value, the average water inlet flow evaluation value, the water inlet pressure extreme difference evaluation value, and the water inlet flow extreme difference evaluation value, wherein the calculation formula of the water inlet state evaluation value of the reverse osmosis device is: X=a*(P+M)+b*(Q+N), Among them, X is the water inlet state evaluation value of the reverse osmosis device, a is the first conversion coefficient, P is the average water inlet pressure evaluation value, M is the average water inlet flow evaluation value, b is the second conversion coefficient, Q is the water inlet pressure extreme difference evaluation value, and N is the water inlet flow extreme difference evaluation value.

3. The online intelligent cleaning control method of a reverse osmosis device according to claim 2 is characterized in that: The method of obtaining water quality index data in the circulating water that affects the scaling of the reverse osmosis device, and analyzing and evaluating the water quality index data to obtain a water quality status evaluation value of the circulating water includes: Take the water quality index data that affects the scaling of the reverse osmosis device in the circulating water, which includes the calcium content data, iron content data, silicon content data and phosphorus content data; Determine the data value of each of the calcium content data, the iron content data, the silicon content data, and the phosphorus content data, respectively, and calculate the average value according to the data value of each of the calcium content data, the iron content data, the silicon content data, and the phosphorus content data, respectively, to obtain the average calcium content value, the average iron content value, the average silicon content value, and the average phosphorus content value; Obtaining a preset standard average calcium content value, a standard average iron content value, a standard average silicon content value, and a standard average phosphorus content value, and respectively calculating the differences between the standard average calcium content value, the standard average iron content value, the standard average silicon content value, and the standard average phosphorus content value and the average calcium content value, the average iron content value, the average silicon content value, and the average phosphorus content value, to obtain a calcium content difference value, an iron content difference value, a silicon content difference value, and a phosphorus content difference value, respectively; The calcium content difference value, the iron content difference value, the silicon content difference value and the phosphorus content difference value are evaluated and valued respectively, and the average calcium content evaluation value, the average iron content evaluation value, the average silicon content evaluation value and the average phosphorus content evaluation value are obtained respectively; The water quality status assessment value of the circulating water is calculated based on the average calcium content assessment value, the average iron content assessment value, the average silicon content assessment value and the average phosphorus content assessment value, wherein the calculation formula for the water quality status assessment value of the circulating water is: Y=(T+U+V+O) / 4, Among them, Y is the water quality status assessment value of circulating water, T is the average calcium content assessment value, U is the average iron content assessment value, V is the average silicon content assessment value, and O is the average phosphorus content assessment value.

4. The online intelligent cleaning control method of a reverse osmosis device according to claim 3 is characterized in that: The method of comprehensively determining the scaling degree value of the reverse osmosis device based on the water inlet state evaluation value of the reverse osmosis device and the water quality state evaluation value of the circulating water comprises: Obtaining an inlet water status evaluation value of the reverse osmosis device and a water quality status evaluation value of the circulating water, and determining preset weights corresponding to the inlet water status evaluation value and the water quality status evaluation value; The scaling degree value of the reverse osmosis device is calculated according to the influent state evaluation value, the water quality state evaluation value and the corresponding preset weights, wherein the calculation formula of the scaling degree value of the reverse osmosis device is: S=α*X+β*Y, Wherein, S is the scaling degree value of the reverse osmosis device, α is the preset weight of the water inlet state evaluation value of the reverse osmosis device, X is the water inlet state evaluation value of the reverse osmosis device, β is the preset weight of the water quality state evaluation value of the circulating water, and Y is the water quality state evaluation value of the circulating water.

5. The online intelligent cleaning control method of a reverse osmosis device according to claim 4, characterized in that: Determining the cleaning working conditions of the cleaning device according to the scaling degree value includes: Obtaining the scaling degree value △G and the preset scaling degree preset value G0, and determining the preset preset difference g1, preset difference g2, third preset difference g3 and fourth preset difference g4, and g1<g2<g3<g4; presetting a preset working condition matrix A1 (a1, b1), a preset working condition matrix A2 (a2, b2), a third preset working condition matrix A3 (a3, b3) and a fourth preset working condition matrix A4 (a4, b4), wherein a1-a4 are sequentially to the fourth preset dosage, and a1<a2<a3<a4, b1-b4 are sequentially to the fourth preset cleaning temperature, and b1<b2<b3<b4; According to the difference between the scaling degree value △G and the preset scaling degree preset value G0, a preset working condition matrix Ai is selected as the working condition of the cleaning device; When △G-G0≤g1, the preset working condition matrix A1 is selected as the working condition of the cleaning device; When g1<△G-G0≤g2, the preset working condition matrix A2 is selected as the working condition of the cleaning device; When g2<△G-G0≤g3, the third preset working condition matrix A3 is selected as the working condition of the cleaning device; When g3<ΔG-G0≤g4, the fourth preset working condition matrix A4 is selected as the working condition of the cleaning device.

6. The online intelligent cleaning control method of a reverse osmosis device according to claim 5, characterized in that: The method of re-determining the scaling degree value of the reverse osmosis device after running the cleaning working condition for a period of time, and determining the working condition correction coefficient based on the difference between the scaling degree values ​​before and after, includes: After the cleaning device has been running for a period of time according to the cleaning working conditions, the scaling degree value of the reverse osmosis device is re-determined; Obtaining the last scaling degree value and the re-determined scaling degree value, calculating the difference between the last scaling degree value and the re-determined scaling degree value, and obtaining the scaling degree difference value; Presetting a corresponding relationship between a working condition correction coefficient and a scaling degree difference value interval, wherein the corresponding relationship between a working condition correction coefficient and a scaling degree difference value interval is associated with a corresponding working condition correction coefficient for each scaling degree difference value interval; The scaling degree difference value is obtained, and based on the mapping relationship between the scaling degree difference value interval to which the scaling degree difference value belongs within the difference coefficient-scaling degree difference value interval correspondence relationship, the working condition correction coefficient corresponding to the scaling degree difference value interval is selected as the working condition correction coefficient of the cleaning device.

7. The online intelligent cleaning control method of a reverse osmosis device according to claim 6, characterized in that: The method of correcting the cleaning working conditions of the cleaning device according to the working condition correction coefficient, and controlling the cleaning device to clean the reverse osmosis device according to the corrected working conditions, comprises: Obtain the working condition correction coefficient mi selected by the cleaning device, and correct the cleaning working condition matrix Ai (ai, bi) of the cleaning device according to the working condition correction coefficient mi. The corrected cleaning working condition matrix is ​​Ai (ai*mi, bi*mi); The corrected cleaning working condition matrix is ​​used as the working condition of the cleaning device, and the cleaning device is controlled according to the working condition to clean the reverse osmosis device.

8. An online intelligent cleaning control system for a reverse osmosis device, characterized in that: include: The first acquisition module is used to acquire the water inlet condition data of the reverse osmosis device, and analyze and evaluate the water inlet condition data to obtain the water inlet state evaluation value of the reverse osmosis device; The second acquisition module is used to obtain water quality index data in the circulating water that affects the scaling of the reverse osmosis device, and analyze and evaluate the water quality index data to obtain a water quality status evaluation value of the circulating water; An analysis module, for comprehensively determining a scaling degree value of the reverse osmosis device based on an evaluation value of an inlet water state of the reverse osmosis device and an evaluation value of a water quality state of circulating water, and determining a cleaning working condition of a cleaning device according to the scaling degree value; A determination module, used to re-determine the scaling degree value of the reverse osmosis device after running for a period of time according to the cleaning working conditions, and determine the working condition correction coefficient based on the difference between the two scaling degree values ​​before and after; The correction module is used to correct the cleaning working conditions of the cleaning device according to the working condition correction coefficient, and control the cleaning device to clean the reverse osmosis device according to the corrected working conditions.

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