Method and system for evaluating service life of ultrafiltration membrane

Abstract

The invention discloses a method and a system for evaluating the service life of an ultrafiltration membrane. The method comprises the following steps: acquiring data corresponding to a plurality of ultrafiltration membrane evaluation indexes in a historical operation cycle; screening out a life evaluation core index and a plurality of life evaluation auxiliary indexes from all the ultrafiltration membrane evaluation indexes; constructing a plurality of life evaluation models based on the life evaluation core index and each life evaluation auxiliary index; respectively inputting the service life evaluation core index data and the service life evaluation auxiliary index data corresponding to the ultrafiltration membrane column needing to be subjected to service life prediction into each service life evaluation model to obtain a plurality of service life prediction values corresponding to the ultrafiltration membrane column; and carrying out weighted average on the plurality of life prediction values corresponding to the ultrafiltration membrane column to obtain a comprehensive life prediction value of the ultrafiltration membrane column. By means of the scheme, the service life of the ultrafiltration membrane can be predicted more accurately, and objectization and datamation of membrane service life evaluation are achieved.

Description

Technical Field

[0001] The present application generally relates to the technical field of ultrafiltration membrane quality assessment, and more specifically, to an ultrafiltration membrane life assessment method and system. Background Art

[0002] By using PVDF ultrafiltration membrane, the membrane bioreactor (MBR) process has the advantages of good effluent quality, small footprint, and less residual sludge, and is widely used in the field of sewage treatment and reuse. However, the long-term operation of PVDF ultrafiltration membranes can easily lead to a decrease in system water production and substandard effluent quality due to membrane pollution and aging, increasing operation and maintenance costs.

[0003] In the prior art, sewage treatment plants judge membrane life only through life data provided by membrane manufacturers or when system water output and effluent quality do not meet standards, membrane life is considered to have ended. However, these methods do not combine the historical operation of the ultrafiltration system to effectively identify and quantify membrane pollution, guide chemical cleaning, analyze membrane service life, and lack a scientific and reasonable membrane life assessment program to provide comprehensive assessment guidance for ultrafiltration process operation.

[0004] In view of this, there is an urgent need to provide an ultrafiltration membrane life assessment solution to obtain the ultrafiltration membrane life by combining various data to achieve objectivity and data-based ultrafiltration membrane life assessment. Summary of the invention

[0005] In order to at least solve one or more of the technical problems mentioned above, the present application proposes an ultrafiltration membrane life assessment scheme in multiple aspects, in order to construct a scientific and comprehensive ultrafiltration membrane life assessment index system, establish an accurate and efficient ultrafiltration membrane life assessment method, and develop an online ultrafiltration membrane life assessment system. The three are interrelated and synergistic, which can overcome the inherent defects of traditional ultrafiltration membrane life assessment methods in data acquisition, analysis and prediction timeliness, and realize the objective, data-based and dynamic assessment of the ultrafiltration membrane life. Thereby accurately grasping the operating status of the ultrafiltration membrane, ensuring the stable and efficient operation of the membrane system, reducing the energy consumption and maintenance costs of the membrane system, and extending the service life of the ultrafiltration membrane.

[0006] In the first aspect, the present application provides a method for evaluating the life of an ultrafiltration membrane, comprising: obtaining data corresponding to multiple ultrafiltration membrane evaluation indicators within a historical operating cycle; screening out a life evaluation core indicator and multiple life evaluation auxiliary indicators from all ultrafiltration membrane evaluation indicators; constructing multiple life evaluation models based on the life evaluation core indicator and each life evaluation auxiliary indicator; inputting the life evaluation core indicator data and life evaluation auxiliary indicator data corresponding to an ultrafiltration membrane column that needs to be life predicted into each life evaluation model to obtain multiple life prediction values ​​corresponding to the ultrafiltration membrane column; and performing weighted averaging on the multiple life prediction values ​​corresponding to the ultrafiltration membrane column to obtain a comprehensive life prediction value of the ultrafiltration membrane column.

[0007] In some embodiments, the multiple ultrafiltration membrane evaluation indicators include water quality historical indicators and operating condition historical indicators. The water quality historical indicators include: water temperature, inlet COD, inlet SS, effluent COD, effluent SS, effluent fecal coliform group, COD cumulative removal, SS cumulative removal; the operating condition historical indicators include: operating days, daily processing volume, inlet MLSS, chemical cleaning agent dosage, flow rate, transmembrane pressure difference, cumulative treated water volume, flux, specific flux, chemical cleaning cycle and cumulative chemical cleaning intensity.

[0008] In some embodiments, in the process of screening out a core indicator for life assessment and multiple auxiliary indicators for life assessment from all ultrafiltration membrane evaluation indicators, the following steps are performed: one indicator among all indicators is used as a comparison indicator; the core indicator for life assessment is obtained based on the correlation coefficient between each indicator among all indicators and the comparison indicator; and multiple auxiliary indicators for life assessment are obtained based on the correlation coefficient between each indicator among all indicators and the core indicator for life assessment.

[0009] In some embodiments, in the process of obtaining the core indicator of life assessment based on the correlation coefficient between each indicator among all indicators and the comparison indicator, the indicator with the smallest correlation coefficient with the comparison indicator among all indicators is used as the core indicator of life assessment.

[0010] In some embodiments, in the process of obtaining multiple life assessment auxiliary indicators based on the correlation coefficient between each indicator among all indicators and the life assessment core indicator, the following steps are performed: the correlation coefficient between the life assessment core indicator and the comparison indicator is used as the first setting coefficient; the indicators among all indicators whose correlation coefficient with the life assessment core indicator is greater than or equal to the first setting coefficient and less than the second setting coefficient are used as life assessment auxiliary indicators; wherein the second setting coefficient is less than 0.

[0011] In some embodiments, in the process of constructing multiple life assessment models based on the life assessment core indicator and each life assessment auxiliary indicator, the following steps are performed: construct multiple coordinate systems with each life assessment auxiliary indicator as the horizontal coordinate and the life assessment core indicator as the vertical coordinate; obtain the first fitting curve and the second fitting curve between the life assessment auxiliary indicator and the life assessment core indicator in each coordinate system to obtain multiple primary life assessment models; evaluate each primary life assessment model, and adjust each primary life assessment model based on the evaluation results to obtain multiple final life assessment models.

[0012] In some embodiments, in the process of obtaining a first fitting curve and a second fitting curve between a life assessment auxiliary indicator and a life assessment core indicator in each coordinate system to obtain multiple primary life assessment models, the following steps are performed: the highest value of multiple life assessment core indicators in each chemical cleaning cycle and the lowest value of multiple life assessment core indicators in each chemical cleaning cycle corresponding to each life assessment auxiliary indicator are collected; the highest values ​​of multiple life assessment core indicators and the lowest values ​​of multiple life assessment core indicators are averaged to obtain the average value of the highest values ​​and the average value of the lowest values; the highest value of the corresponding life assessment core indicator and the lowest value of the corresponding life assessment core indicator are eliminated based on the difference between the highest value and the average value of the highest value of each life assessment core indicator and the difference between the lowest value and the average value of the lowest value of each life assessment core indicator; the highest value of the life assessment core indicator after the elimination process and the lowest value of the life assessment core indicator after the elimination process are linearly fitted in each coordinate system to obtain a first fitting curve and a second fitting curve, thereby obtaining multiple primary life assessment models.

[0013] In some embodiments, the model parameters corresponding to the primary life assessment model include the slope of the first fitting curve, the intercept of the first fitting curve, the slope of the second fitting curve, and the intercept of the second fitting curve; in the process of evaluating each primary life assessment model and adjusting each primary life assessment model based on the evaluation results, the following steps are performed: evaluating the goodness of fit and prediction accuracy of each primary life assessment model; judging whether the goodness of fit of each primary life assessment model is greater than a preset goodness of fit value, and whether the prediction accuracy of each primary life assessment model is greater than a preset accuracy value; in response to the goodness of fit of each primary life assessment model being greater than the preset goodness of fit value, and the prediction accuracy of each primary life assessment model being greater than the preset accuracy value, the parameters of each primary life assessment model are not adjusted; in response to the goodness of fit of the primary life assessment model being not greater than the preset goodness of fit value, or the prediction accuracy of the primary life assessment model being not greater than the preset accuracy value, the parameters of the corresponding primary life assessment model are adjusted until the goodness of fit of the corresponding primary life assessment model is greater than the preset goodness of fit value, and the prediction accuracy of the corresponding primary life assessment model is greater than the preset accuracy value.

[0014] In some embodiments, in the process of obtaining multiple life prediction values ​​corresponding to the ultrafiltration membrane column, each life evaluation model performs the following steps: obtaining data corresponding to the life evaluation auxiliary indicator at the intersection of the first fitting curve and the second fitting curve in the corresponding coordinate system; converting the data corresponding to the life evaluation auxiliary indicator into a life prediction value.

[0015] In the second aspect, the present application provides an ultrafiltration membrane life assessment system, the system comprising: the system comprises a front-end module, a back-end module, a database module and an algorithm module; the front-end module is used to receive instructions input by a user, and display the corresponding data stored in the database module based on the instructions; the back-end module is used to receive data sent by the front-end module, and pass the data to the algorithm module for processing; the database module is used to store data corresponding to multiple ultrafiltration membrane evaluation indicators within a historical operating cycle; the algorithm module is used to execute the ultrafiltration membrane life assessment method as described in any embodiment of the first aspect to perform ultrafiltration membrane life assessment.

[0016] Through the ultrafiltration membrane life assessment scheme provided above, the embodiment of the present application selects life assessment core indicators and multiple life assessment auxiliary indicators from all ultrafiltration membrane evaluation indicators, and constructs multiple life evaluation models based on the life assessment core indicators and each life assessment auxiliary indicator, which can more accurately predict the life of the ultrafiltration membrane and realize the objectivity and dataization of membrane life assessment.

[0017] Furthermore, the embodiment of the present application is based on the online evaluation model of the ultrafiltration membrane life evaluation system, which can collect and analyze various key parameters in the operation process of the ultrafiltration membrane in real time and accurately. Through the systematic analysis of these parameters, it is possible to effectively avoid the serious response lag problem existing in the traditional manual prediction model, as well as the deviation and delay in judging the operating status of the membrane system due to excessive reliance on manual experience. It fully guarantees the stability and efficiency of the membrane system operation, significantly extends the actual service life of the ultrafiltration membrane, and improves the overall operating efficiency.

[0018] Compared with the prior art, the present invention has the following beneficial effects: it can establish a scientific and comprehensive ultrafiltration membrane life evaluation index system in combination with the historical operation of the ultrafiltration system, establish an accurate and efficient ultrafiltration membrane life evaluation method, and develop an online ultrafiltration membrane life evaluation system to achieve a scientific and reasonable evaluation of the ultrafiltration membrane life, avoiding the problem of inaccurate evaluation when only a single parameter or a few parameters are used for life evaluation. In this way, the ultrafiltration membrane operation status can be accurately grasped, the membrane system can be ensured to operate stably and efficiently, the energy consumption and maintenance cost of the membrane system can be reduced, and the service life of the ultrafiltration membrane can be extended. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become easy to understand. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0020] Figure 1 An exemplary flow chart of the ultrafiltration membrane life assessment method according to an embodiment of the present application is shown;

[0021] Figure 2 An exemplary flow chart of screening out a core indicator for life assessment and a plurality of auxiliary indicators for life assessment according to an embodiment of the present application is shown;

[0022] Figure 3 An exemplary flow chart of constructing multiple life evaluation models based on the life evaluation core index and various life evaluation auxiliary indexes according to an embodiment of the present application is shown;

[0023] Figure 4 An exemplary flow chart of obtaining multiple primary life assessment models according to an embodiment of the present application is shown;

[0024] Figure 5 An example diagram of a life evaluation method formed by the core index of specific flux and the auxiliary index of operating days in an embodiment of the present application is shown;

[0025] Figure 6 An exemplary flow chart of adjusting each primary life assessment model based on the evaluation results according to an embodiment of the present application is shown;

[0026] Figure 7 An exemplary structural block diagram of an ultrafiltration membrane life assessment system according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0028] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present application indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0029] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this application specification and claims, unless the context clearly indicates otherwise, the singular forms of "a", "an" and "the" are intended to include plural forms. It should also be further understood that the term "and / or" used in this application specification and claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0030] As used in this specification and claims, the term "if" may be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if it is determined" or "if [the described condition or event] is detected" may be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [the described condition or event] is detected" or "in response to detecting [the described condition or event]" depending on the context. When determining the maximum or minimum value of [the described condition or event], the comparison operation is performed directly on the complete numerical value including the positive and negative signs, and the numerical value size is considered separately without stripping the sign.

[0031] The specific implementation of the present application is described in detail below with reference to the accompanying drawings.

[0032] Figure 1 An exemplary flow chart of an ultrafiltration membrane life assessment method 100 according to an embodiment of the present application is shown.

[0033] like Figure 1 As shown, in step S110, data corresponding to multiple ultrafiltration membrane evaluation indicators in a historical operation cycle are obtained.

[0034] In an embodiment of the present application, multiple ultrafiltration membrane evaluation indicators include water quality history indicators and operating condition history indicators. Water quality history indicators include: water temperature, inlet COD, inlet SS, outlet COD, outlet SS, outlet fecal coliform group, COD cumulative removal, SS cumulative removal. Operating condition history indicators include: operating days, daily processing volume, inlet MLSS, chemical cleaning agent dosage, flow rate, transmembrane pressure difference, cumulative treated water volume, flux, specific flux, chemical cleaning cycle and cumulative chemical cleaning intensity.

[0035] In an embodiment of the present application, firstly, the data corresponding to the historical water quality indicators including water temperature, inlet COD, inlet SS, outlet COD, outlet SS, outlet fecal coliform group, etc. and the data corresponding to the historical working condition indicators including the number of days of operation, daily processing volume, inlet MLSS, chemical cleaning agent dosage, flow rate, transmembrane pressure difference, chemical cleaning cycle, etc. are collected. The data sources of these data include but are not limited to manually transcribed system operation reports, monitoring and data acquisition systems (SCADA), distributed control systems (DCS), etc. Then, the collected data are pre-processed, and in the pre-processing process, the data format and standard are unified, and irrelevant data are eliminated, missing values ​​are filled, deleted or differenced, and abnormal values ​​are corrected or deleted to ensure the consistency and integrity of the data. Then, the COD cumulative removal amount, SS cumulative removal amount, cumulative treated water volume, flux, specific flux and cumulative chemical cleaning intensity are obtained based on the collected data. Thus, the data corresponding to multiple ultrafiltration membrane evaluation indicators in the historical operation cycle are obtained.

[0036] Specifically, the cumulative COD removal is obtained based on the inlet COD and the outlet COD, the cumulative SS removal is obtained based on the inlet SS and the outlet SS, the cumulative treated water flux is obtained based on the operating days and the daily processing volume, and the cumulative chemical cleaning intensity is obtained based on the chemical cleaning agent dosage and the chemical cleaning cycle.

[0037] Specifically, the flux is obtained based on the membrane flux calculation formula, and the specific flux data is obtained based on the specific flux calculation formula. The membrane flux calculation formula is: J = Q / A, J is the flux, the unit is L / (m 2 ·h), Q is the flow rate in L / h, A is the effective filtration area of ​​the membrane in m 2 The specific flux reflects the decline trend of ultrafiltration membrane performance. The specific flux calculation formula is F = J / T, where F is the specific flux, and the unit is L / (m 2 ·h·kPa), J is the flux, the unit is L / (m 2 ·h), T is the transmembrane pressure difference, in kPa.

[0038] By processing multiple water quality historical indicator data and operating condition historical indicator data involved in the historical operation cycle, it is possible to provide a larger data basis for the screening of subsequent life assessment core indicators and life assessment auxiliary indicators, thereby improving the accuracy of subsequent ultrafiltration membrane life assessment.

[0039] After executing step S110, in step S120, a life assessment core indicator and a plurality of life assessment auxiliary indicators are screened out from all ultrafiltration membrane evaluation indicators.

[0040] In the embodiments of the present application, the specific process of selecting the core life evaluation index and multiple life evaluation auxiliary indexes from all ultrafiltration membrane evaluation indexes can be found in Figure 2 .

[0041] Figure 2 An exemplary flow chart for screening out a core indicator for life assessment and a plurality of auxiliary indicators for life assessment according to an embodiment of the present application is shown.

[0042] like Figure 2 As shown, in step S210, one of all the indicators is used as a comparison indicator. In step S220, a life assessment core indicator is obtained based on the correlation coefficient between each of all the indicators and the comparison indicator. In step S230, multiple life assessment auxiliary indicators are obtained based on the correlation coefficient between each of all the indicators and the life assessment core indicator.

[0043] In some embodiments of the present application, the number of operating days is used as a comparison index. In other embodiments of the present application, other indicators may also be used as comparison indicators, and the present application does not limit this.

[0044] In some embodiments of the present application, the correlation coefficient is obtained by using the Pearson correlation coefficient calculation formula. In other embodiments of the present application, the correlation coefficient may also be obtained by using other correlation coefficient calculation formulas, which are not limited in the present application.

[0045] Specifically, the Pearson correlation coefficient calculation formula is: r is the correlation coefficient between the two indicators, X i and Y i are the values ​​corresponding to the two indicators respectively. and Represents the average value of the two indicators.

[0046] In an embodiment of the present application, in the process of obtaining the core indicator of life assessment based on the correlation coefficient between each indicator among all indicators and the comparison indicator, the indicator with the smallest correlation coefficient with the comparison indicator among all indicators is used as the core indicator of life assessment.

[0047] By taking the indicator with the smallest correlation coefficient with the comparison indicator as the core indicator of life assessment, we can ensure that the core indicator of life assessment has high independence and representativeness in the assessment process, which helps to avoid duplication and redundancy between indicators, thereby optimizing the scientificity and effectiveness of the entire evaluation system.

[0048] In the embodiment of the present application, in the process of obtaining multiple life assessment auxiliary indicators based on the correlation coefficient between each indicator among all indicators and the life assessment core indicator, first, the correlation coefficient between the life assessment core indicator and the comparison indicator is used as the first setting coefficient. Then, among all indicators, the indicators whose correlation coefficient with the life assessment core indicator is greater than or equal to the first setting coefficient and less than the second setting coefficient are used as life assessment auxiliary indicators.

[0049] Specifically, the second setting coefficient is less than 0.

[0050] In the embodiments of the present application, the specific value of the second setting coefficient can be set according to actual needs and historical experience, and the present application does not limit it here.

[0051] In some embodiments of the present application, the number of operating days is used as a comparison index, and the second setting coefficient is set to -0.7. In the specific process of executing the aforementioned steps S220 and S230, the index with the smallest correlation coefficient with the comparison index among all the indexes is the specific flux, which is used as the core index of life assessment, and the index with a correlation coefficient with the core index of life assessment among all the indexes greater than or equal to the first setting coefficient and less than the second setting coefficient is the number of operating days, the cumulative chemical cleaning intensity, and the cumulative amount of treated water. Therefore, the number of operating days, the cumulative chemical cleaning intensity, and the cumulative amount of treated water are used as auxiliary indicators for life assessment.

[0052] By setting the correlation coefficient with the core indicators of life assessment within a certain range as auxiliary indicators of life assessment, it can be ensured that the auxiliary indicators of life assessment maintain correlation with the core indicators of life assessment to a certain extent, and the richness of the indicators and the accuracy of the assessment can be balanced to avoid deviations caused by over-reliance on a certain indicator.

[0053] In an embodiment of the present application, in the aforementioned process of obtaining the core indicators and auxiliary indicators of life assessment, the core indicators and auxiliary indicators are determined through objective correlation coefficients, which reduces the impact of subjective judgment on the evaluation results and improves the objectivity and reliability of the evaluation process.

[0054] After executing step S120, in step S130, multiple life assessment models are constructed based on the life assessment core indicators and various life assessment auxiliary indicators.

[0055] In the embodiment of the present application, the specific steps involved in step S130 can be found in Figure 3 .

[0056] Figure 3 An exemplary flow chart of constructing multiple life evaluation models based on life evaluation core indicators and various life evaluation auxiliary indicators according to an embodiment of the present application is shown.

[0057] like Figure 3 As shown, in step S310, multiple coordinate systems are constructed with each life assessment auxiliary indicator as the horizontal coordinate and the life assessment core indicator as the vertical coordinate. In step S320, the first fitting curve and the second fitting curve between the life assessment auxiliary indicator and the life assessment core indicator are obtained in each coordinate system to obtain multiple primary life assessment models. In step S330, each primary life assessment model is evaluated, and each primary life assessment model is adjusted based on the evaluation results to obtain multiple final life assessment models.

[0058] In the embodiments of the present application, in the process of obtaining multiple primary life assessment models, a linear regression algorithm may be used, or other algorithms may be used, and the present application does not limit this.

[0059] In the embodiment of the present application, the specific steps involved in step S320 can be found in Figure 4 .

[0060] Figure 4 An exemplary flow chart for obtaining multiple primary life assessment models according to an embodiment of the present application is shown.

[0061] like Figure 4As shown, in step S410, the highest values ​​of multiple life assessment core indicators in each chemical cleaning cycle and the lowest values ​​of multiple life assessment core indicators in each chemical cleaning cycle corresponding to each life assessment auxiliary indicator are collected. In step S420, the highest values ​​of multiple life assessment core indicators and the lowest values ​​of multiple life assessment core indicators are averaged to obtain the highest value average value and the lowest value average value. In step S430, based on the difference between the highest value and the highest value average value of each life assessment core indicator and the difference between the lowest value and the lowest value average value of each life assessment core indicator, the highest value of the corresponding life assessment core indicator and the lowest value of the corresponding life assessment core indicator are eliminated. In step S440, the highest value of the life assessment core indicator after elimination and the lowest value of the life assessment core indicator after elimination are linearly fitted in each coordinate system to obtain a first fitting curve and a second fitting curve, thereby obtaining multiple primary life assessment models.

[0062] In an embodiment of the present application, in the process of eliminating the highest value of the corresponding life assessment core indicator and the lowest value of the corresponding life assessment core indicator based on the difference between the highest value and the average value of the highest value of each life assessment core indicator and the difference between the lowest value and the average value of the lowest value of each life assessment core indicator, when the difference obtained by subtracting the average value of the highest value from the highest value of the corresponding life assessment core indicator is a set percentage of the average value of the highest value, the highest value of the corresponding life assessment core indicator is eliminated. At the same time, when the difference obtained by subtracting the lowest value of the corresponding life assessment core indicator from the average value of the lowest value is a set percentage of the average value of the lowest value, the lowest value of the corresponding life assessment core indicator is eliminated.

[0063] In the embodiments of the present application, the aforementioned set percentage can be set according to actual needs and historical experience, and the present application does not limit it here. For example, in some embodiments of the present application, the aforementioned set percentage is 20%. Therefore, when the difference between the highest value of the corresponding life assessment core indicator and the average value of the highest value is 20% of the average value of the highest value, the highest value of the corresponding life assessment core indicator is eliminated. At the same time, when the difference between the average value of the lowest value and the lowest value of the corresponding life assessment core indicator is 20% of the average value of the lowest value, the lowest value of the corresponding life assessment core indicator is eliminated.

[0064] By eliminating the highest value and the lowest value of the corresponding life assessment core indicator, abnormal points can be removed to ensure that the selected highest value and the lowest value of the life assessment core indicator can effectively reflect the trend of membrane life changes and improve the accuracy and reliability of the prediction results.

[0065] In one embodiment of the present application, when the specific flux is used as the core indicator of life evaluation and the number of operating days is used as one of the auxiliary indicators of life evaluation, the specific flux and the number of operating days of the membrane column 1 and the membrane column 2 of the ultrafiltration membrane in each coordinate system are linearly fitted to obtain a first fitting curve 11 corresponding to the membrane column 1, a second fitting curve 12 corresponding to the membrane column 1, a first fitting curve 21 corresponding to the membrane column 2, and a second fitting curve 22 corresponding to the membrane column 2. For details, please refer to Figure 5 .

[0066] By obtaining the fitting curve and thus forming a life assessment model, the complex internal relationship between the core indicators of life assessment and the auxiliary indicators of life assessment can be captured, and more accurate prediction results can be obtained.

[0067] In the embodiment of the present application, the specific steps involved in step S330 can be found in Figure 6 .

[0068] Figure 6 An exemplary flowchart of adjusting various primary life assessment models based on evaluation results according to an embodiment of the present application is shown.

[0069] like Figure 6 As shown, in step S610, the goodness of fit and prediction accuracy of each primary life evaluation model are evaluated. In step S620, it is determined whether the goodness of fit of each primary life evaluation model is greater than the preset value of the goodness of fit, and whether the prediction accuracy of each primary life evaluation model is greater than the preset value of the accuracy. In response to the goodness of fit of each primary life evaluation model being greater than the preset value of the goodness of fit, and the prediction accuracy of each primary life evaluation model being greater than the preset value of the accuracy, in step S630, the parameters of each primary life evaluation model are not adjusted. In response to the goodness of fit of a primary life evaluation model being not greater than the preset value of the goodness of fit, or the prediction accuracy of a primary life evaluation model being not greater than the preset value of the accuracy, in step S640, the parameters of the corresponding primary life evaluation model are adjusted. Then, return to step S620, and judge the goodness of fit and prediction accuracy of the primary life evaluation model after parameter adjustment until the goodness of fit of the corresponding primary life evaluation model is greater than the preset value of the goodness of fit and the prediction accuracy of the corresponding primary life evaluation model is greater than the preset value of the accuracy, and then execute step S630.

[0070] In an embodiment of the present application, in the process of evaluating the goodness of fit of each primary life assessment model, the determination coefficient of the primary life assessment model can be used to evaluate the goodness of fit of each primary life assessment model, or other methods can be used to evaluate the goodness of fit of each primary life assessment model, and the present application does not limit this.

[0071] In an embodiment of the present application, in the process of evaluating the prediction accuracy of each primary life evaluation model, each primary life evaluation model is verified using ultrafiltration membrane operation data as a validation set data to obtain the prediction accuracy of each primary life evaluation model, thereby ensuring the generalization ability of the model.

[0072] In the embodiments of the present application, the aforementioned preset goodness of fit value and preset accuracy value can be set according to actual needs, and the present application does not limit this.

[0073] In an embodiment of the present application, model parameters corresponding to the primary life assessment model include the slope of the first fitting curve, the intercept of the first fitting curve, the slope of the second fitting curve, and the intercept of the second fitting curve.

[0074] Specifically, the slope of the first fitting curve is used to characterize the recovery rate of membrane performance after chemical cleaning, and the slope of the second fitting curve is used to characterize the degradation rate of membrane pollution performance. When the goodness of fit and / or accuracy of the primary life evaluation model do not meet the requirements, the parameters of the corresponding primary life evaluation model are adjusted, so as to gradually improve the reliability and practicality of the primary life evaluation model, so as to improve the overall prediction accuracy.

[0075] After executing step S130, the life assessment core indicator data and life assessment auxiliary indicator data corresponding to the ultrafiltration membrane array that needs to be predicted are respectively input into each life assessment model to obtain multiple life prediction values ​​corresponding to the ultrafiltration membrane array.

[0076] In the embodiment of the present application, after the life assessment core index data and life assessment auxiliary index data corresponding to the ultrafiltration membrane array for which life prediction is required are input into each life assessment model, in the process of obtaining multiple life prediction values ​​corresponding to the ultrafiltration membrane array, each life assessment model performs the following steps: First, the data corresponding to the life assessment auxiliary index at the intersection of the first fitting curve and the second fitting curve is obtained in the corresponding coordinate system. Then, the data corresponding to the life assessment auxiliary index is converted into a life prediction value.

[0077] In the embodiment of the present application, at the intersection of the first fitting curve and the second fitting curve, the life assessment core indicator drops to a predetermined threshold value, and it remains unchanged after chemical cleaning is immediately performed. Therefore, the data corresponding to the life assessment auxiliary indicator at the intersection of the first fitting curve and the second fitting curve is the data for predicting the end of life.

[0078] In the embodiments of the present application, when converting the data corresponding to different life assessment auxiliary indicators into life prediction values, different conversion methods are used, and the present application does not limit this. For example, the cumulative treated water volume can be converted into a life prediction value by the water production scale and the membrane area, and the cumulative chemical cleaning intensity can be converted into a life prediction value by the chemical cleaning agent dosage and the chemical cleaning cycle.

[0079] After executing step S140, a weighted average of the multiple life prediction values ​​corresponding to the ultrafiltration membrane array is performed to obtain a comprehensive life prediction value of the ultrafiltration membrane array.

[0080] In an embodiment of the present application, in the process of weighted averaging the multiple life prediction values ​​corresponding to the ultrafiltration membrane column, different weights can be assigned to the corresponding life prediction values ​​based on the types of life assessment auxiliary indicators, and the present application does not limit this.

[0081] By taking a weighted average of the multiple life prediction values ​​corresponding to the ultrafiltration membrane array to obtain a comprehensive life prediction value of the ultrafiltration membrane array, the possible deviation of a single prediction model can be effectively reduced, all available information can be fully integrated, and a more comprehensive and accurate comprehensive life prediction value can be constructed.

[0082] In summary, through the ultrafiltration membrane life assessment scheme provided above, the embodiment of the present application selects the life assessment core indicators and multiple life assessment auxiliary indicators from all ultrafiltration membrane evaluation indicators, and constructs multiple life evaluation models based on the life assessment core indicators and each life assessment auxiliary indicator, which can more accurately predict the life of the ultrafiltration membrane and realize the objectivity and dataization of membrane life assessment.

[0083] Compared with the prior art, the embodiments of the present application have the following beneficial effects: it can establish a scientific and comprehensive ultrafiltration membrane life evaluation index system in combination with the historical operation of the ultrafiltration system, establish an accurate and efficient ultrafiltration membrane life evaluation method, and develop an online ultrafiltration membrane life evaluation system to achieve a scientific and reasonable evaluation of the ultrafiltration membrane life, avoiding the problem of inaccurate evaluation when only a single parameter or a few parameters are used for life evaluation. In this way, the ultrafiltration membrane operation status can be accurately grasped, the membrane system can be ensured to operate stably and efficiently, the energy consumption and maintenance cost of the membrane system can be reduced, and the service life of the ultrafiltration membrane can be extended.

[0084] The present application also provides an ultrafiltration membrane life assessment system. Figure 7 The ultrafiltration membrane life evaluation system is explained in detail.

[0085] Figure 7 An exemplary structural block diagram of an ultrafiltration membrane life assessment system according to an embodiment of the present application is shown.

[0086] like Figure 7As shown, the system 700 includes a front-end module 710 , a back-end module 720 , a database module 730 and an algorithm module 740 .

[0087] Specifically, the front-end module 710 is used to receive instructions input by the user, and display the corresponding data stored in the database module based on the instructions.

[0088] In an embodiment of the present application, the front-end module 710 may include a user interface unit 711, a data display unit 712, a data input unit 713 and a user interaction unit 714. The user interface unit 711 is used to provide a front-end user interface, which can perform user login, data query, data screening, data modification, data export and data display, wherein these data include but are not limited to SS, COD, fecal coliform group, flow, transmembrane pressure difference, MLSS, chemical cleaning agent name and dosage, cleaning time, etc. The data display unit 712 is used to display the membrane life evaluation prediction results in real time, including the corresponding change trend chart of the life evaluation index system and the life prediction result chart, so as to understand the actual system operation and cleaning effect during the membrane life cycle. The data input unit 713 is used to manually enter or modify the data that cannot be obtained online, and can reconfigure the relevant parameters according to the changes in the system operation, and can manually modify the screening point and selection point for evaluation and prediction. The user interaction unit 714 is used to provide data retrieval, screening and export functions.

[0089] Specifically, the back-end module 720 is used to receive data sent by the front-end module and pass the data to the algorithm module for processing.

[0090] In the implementation of the present application, the back-end module 720 may include a data docking unit 721, a logic business unit 722, an interface integration unit 723 and a security authentication unit 724. The data docking unit 721 is used to manage the connection, access and cache of the database module 730. The logic business unit 722 is used to manage the process and logic rules of data collection, processing and analysis. The interface integration unit 723 is used to provide an API interface for the front-end module 710 service call and manage the data exchange format. The security authentication unit 724 is used to verify and authorize the identity of the logged-in user and limit non-user access rights.

[0091] Specifically, the database module 730 is used to store data corresponding to multiple ultrafiltration membrane evaluation indicators within a historical operation cycle.

[0092] In an embodiment of the present application, the database module 730 may include a data storage unit 731 and a data management unit 732. The data storage unit 731 is used to store historical import data of the membrane system, online monitoring data, model prediction parameters, system modification data records, model prediction results, etc. The data management unit 732 is used to perform data query, modification, addition, deletion, and export functions to ensure data consistency and security.

[0093] In some embodiments of the present application, the database module 730 uses MySQL 8.0.23 as a database management system. MySQL is a widely used relational database system that provides stable storage and efficient data retrieval capabilities, supports cross-platform operations and multiple programming languages, and ensures the flexibility and scalability of the system. Specifically, it includes but is not limited to real-time monitoring data tables (water quality and online operation monitoring data) for analyzing the daily membrane system operation, real-time monitoring time series statistical data tables (membrane flux, specific flux) for analyzing and evaluating the performance change trend of the membrane system in different time periods of continuous operation, real-time monitoring of membrane group data tables (membrane group filtration area, use date, official membrane life) for membrane group maintenance or replacement to provide data reference, real-time monitoring of membrane cleaning data tables (chemical cleaning agents, cleaning time, cleaning agent dosage) for optimizing chemical cleaning solutions, delaying membrane pollution, and real-time monitoring of extended membrane service life prediction results data tables (membrane life) for membrane system operation and maintenance and replacement decisions to provide data support.

[0094] Specifically, the algorithm module 740 is used to execute the ultrafiltration membrane life assessment method 100 as described above.

[0095] In an embodiment of the present application, the algorithm module 740 may include a data preprocessing unit 741, a model training unit 742 and a prediction execution unit 743. The data preprocessing unit 741 is used to clean and preprocess the data in the database, fill, delete or interpolate missing values, and correct or delete abnormal values. The model training unit 742 is used to determine the characteristic variables according to the establishment of the membrane life evaluation index system, use the linear regression analysis algorithm to construct the life evaluation model, define the structure of the life evaluation model including the slope and intercept, calculate the model parameters using the collected historical data through the least squares method and other optimization algorithms to complete the linear fitting, and evaluate and optimize the life evaluation model. The prediction execution unit 743 uses the trained life evaluation model to predict the operating parameters of all ultrafiltration membrane columns and output the life prediction results of all ultrafiltration membrane columns.

[0096] The embodiment of the present application provides an online evaluation model through the ultrafiltration membrane life evaluation system, which can collect and analyze various key parameters in the ultrafiltration membrane operation process in real time and accurately. As a result, it can effectively avoid the serious lag disadvantages inherent in traditional manual predictions, as well as the problem of delays in judging the operating status of the membrane system due to excessive reliance on manual experience. In addition, it can comprehensively guarantee the stable and efficient operation of the membrane system, significantly extend the actual service life of the ultrafiltration membrane, and improve the overall operating efficiency.

Claims

1. A method for evaluating the life of an ultrafiltration membrane, characterized in that: include: Obtain data corresponding to multiple ultrafiltration membrane evaluation indicators within a historical operation cycle; Select the core indicators for life assessment and multiple auxiliary indicators for life assessment from all ultrafiltration membrane assessment indicators; Construct multiple life evaluation models based on the core indicators of life evaluation and various auxiliary indicators of life evaluation; Inputting the life assessment core indicator data and life assessment auxiliary indicator data corresponding to the ultrafiltration membrane series for which life prediction is required into each life evaluation model to obtain multiple life prediction values ​​corresponding to the ultrafiltration membrane series; The weighted average of multiple life prediction values ​​corresponding to the ultrafiltration membrane column is used to obtain a comprehensive life prediction value of the ultrafiltration membrane column.

2. The method for evaluating the life of an ultrafiltration membrane according to claim 1, characterized in that: The multiple ultrafiltration membrane evaluation indicators include water quality historical indicators and operating condition historical indicators, and the water quality historical indicators include: water temperature, inlet COD, inlet SS, effluent COD, effluent SS, effluent fecal coliform group, COD cumulative removal, SS cumulative removal; The operating condition history indicators include: operating days, daily processing volume, inlet water MLSS, chemical cleaning agent usage, flow rate, transmembrane pressure difference, cumulative processed water volume, flux, specific flux, chemical cleaning cycle and cumulative chemical cleaning intensity.

3. The method for evaluating the life of an ultrafiltration membrane according to claim 1, characterized in that: In the process of selecting the core indicators for life evaluation and multiple auxiliary indicators for life evaluation from all ultrafiltration membrane evaluation indicators, the following steps are performed: Use one indicator among all indicators as a comparison indicator; The core indicators of life assessment are obtained based on the correlation coefficients between each indicator and the comparison indicator in all indicators; Based on the correlation coefficient between each indicator in all indicators and the core indicator of life assessment, multiple auxiliary indicators of life assessment are obtained.

4. The method for evaluating the life of an ultrafiltration membrane according to claim 3, characterized in that: In the process of obtaining the core indicator of life assessment based on the correlation coefficient between each indicator among all indicators and the comparison indicator, the indicator with the smallest correlation coefficient with the comparison indicator among all indicators is used as the core indicator of life assessment.

5. The method for evaluating the life of an ultrafiltration membrane according to claim 4, characterized in that: In the process of obtaining multiple life assessment auxiliary indicators based on the correlation coefficients of each indicator among all indicators and the life assessment core indicator, the following steps are performed: The correlation coefficient between the core indicator of life assessment and the comparative indicator is used as the first setting coefficient; Among all the indicators, the indicators whose correlation coefficient with the core indicator of life assessment is greater than or equal to the first set coefficient and less than the second set coefficient are used as auxiliary indicators of life assessment; Wherein, the second setting coefficient is less than 0.

6. The method for evaluating the life of an ultrafiltration membrane according to claim 2, characterized in that: In the process of building multiple life assessment models based on the life assessment core indicators and various life assessment auxiliary indicators, the following steps are performed: Construct multiple coordinate systems with each life assessment auxiliary indicator as the horizontal coordinate and the life assessment core indicator as the vertical coordinate; Obtaining a first fitting curve and a second fitting curve between the auxiliary life assessment index and the core life assessment index in each coordinate system to obtain a plurality of primary life assessment models; Each primary life assessment model is evaluated, and each primary life assessment model is adjusted based on the evaluation result to obtain multiple final life assessment models.

7. The method for evaluating the life of an ultrafiltration membrane according to claim 6, characterized in that: In the process of obtaining the first fitting curve and the second fitting curve between the auxiliary life assessment index and the core life assessment index in each coordinate system and obtaining multiple primary life assessment models, the following steps are performed: Collecting the highest values ​​of multiple life assessment core indicators in each chemical cleaning cycle corresponding to each life assessment auxiliary indicator and the lowest values ​​of multiple life assessment core indicators in each chemical cleaning cycle; The highest values ​​of multiple life assessment core indicators and the lowest values ​​of multiple life assessment core indicators are averaged to obtain the average value of the highest values ​​and the average value of the lowest values; Based on the difference between the highest value and the average value of the highest value of each life assessment core indicator and the difference between the lowest value and the average value of the lowest value of each life assessment core indicator, the highest value of the corresponding life assessment core indicator and the lowest value of the corresponding life assessment core indicator are eliminated; In each coordinate system, linear fitting is performed on the highest value of the core indicator of life assessment after elimination and the lowest value of the core indicator of life assessment after elimination to obtain a first fitting curve and a second fitting curve, thereby obtaining multiple primary life assessment models.

8. The method for evaluating the life of an ultrafiltration membrane according to claim 6 or 7, characterized in that: The model parameters corresponding to the primary life assessment model include the slope of the first fitting curve, the intercept of the first fitting curve, the slope of the second fitting curve, and the intercept of the second fitting curve; In the process of evaluating each primary life assessment model and adjusting each primary life assessment model based on the evaluation results, the following steps are performed: Evaluate the goodness of fit and prediction accuracy of each primary life assessment model; Determine whether the goodness of fit of each primary life evaluation model is greater than a preset goodness of fit value, and whether the prediction accuracy of each primary life evaluation model is greater than a preset accuracy value; In response to the goodness of fit of each primary life assessment model being greater than a preset goodness of fit value, and the prediction accuracy of each primary life assessment model being greater than a preset accuracy value, the parameters of each primary life assessment model are not adjusted; In response to the fact that the goodness of fit of the primary life evaluation model is not greater than the preset goodness value, or the prediction accuracy of the primary life evaluation model is not greater than the preset accuracy value, the parameters of the corresponding primary life evaluation model are adjusted until the goodness of fit of the corresponding primary life evaluation model is greater than the preset goodness of fit value, and the prediction accuracy of the corresponding primary life evaluation model is greater than the preset accuracy value.

9. The method for evaluating the life of an ultrafiltration membrane according to claim 1, characterized in that: In the process of obtaining a plurality of life prediction values ​​corresponding to the ultrafiltration membrane array, each life evaluation model performs the following steps: Acquire data corresponding to the auxiliary indicator of life assessment at the intersection of the first fitting curve and the second fitting curve in the corresponding coordinate system; The data corresponding to the auxiliary indicators of life assessment are converted into life prediction values.

10. An ultrafiltration membrane life assessment system, characterized in that: The system includes a front-end module, a back-end module, a database module and an algorithm module; The front-end module is used to receive instructions input by the user and display the corresponding data stored in the database module based on the instructions; The back-end module is used to receive the data sent by the front-end module and pass the data to the algorithm module for processing; The database module is used to store data corresponding to multiple ultrafiltration membrane evaluation indicators within a historical operation cycle; The algorithm module is used to execute the ultrafiltration membrane life assessment method as described in any one of claims 1-9.

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