Membrane pollution state evaluation method, device, equipment and medium of membrane bioreactor

Abstract

The invention discloses a membrane pollution state evaluation method, device and equipment of a membrane bioreactor and a medium, and relates to the technical field of membrane method water treatment.The membrane pollution state evaluation method comprises the steps that membrane pollution monitoring index data of the membrane bioreactor are periodically collected, and a periodic time sequence data set used for analyzing and evaluating membrane pollution changes is generated according to the membrane pollution monitoring index data; analyzing the membrane pollution monitoring index data in the periodic time sequence data set according to a preset pollution evaluation rule to determine an index evaluation value corresponding to a membrane pollution monitoring index in the membrane pollution monitoring index data; and determining the pollution state of the membrane bioreactor according to the index evaluation value. Therefore, by analyzing the membrane pollution monitoring data, the membrane pollution potential and state change are mastered, the membrane system operation condition adaptability is evaluated, the reversible membrane pollution degree change and the irreversible membrane pollution degree change are distinguished, special data processing and analysis software does not need to be developed, and the low cost and the reliability, stability and accuracy of the monitoring data are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of membrane water treatment, in particular to a membrane pollution state evaluation method, device, equipment and medium of a membrane bioreactor. BACKGROUND

[0002] In the application process of membrane water treatment process, membrane pollution and the membrane performance attenuation caused by the membrane pollution are key problems affecting the operation efficiency of the membrane system. Monitoring the generation of membrane pollution in the operation process of the membrane system and analyzing the state change trend are crucial for understanding and controlling the membrane pollution.

[0003] In the related art, acoustic / optical / electrical and physical and chemical technologies can be used to characterize membrane pollution, but the analysis method for characterizing the membrane pollution process by using acoustic / optical / electrical and physical and chemical technologies is relatively complex, professional data processing and analysis software is needed for data processing and analysis, and there are limitations in practicality and simplicity, high cost, and no related reports have been applied in actual projects. Non-professional operation and management personnel cannot master it.

[0004] In the related art, the membrane system application can also be used to evaluate the membrane pollution state, but in the membrane system application process, it is difficult to establish an accurate, appropriate and universal pollution mechanism model due to the influence of various working conditions and environments, and a large amount of actual operation data needs to be monitored for a long time to analyze, involves many parameters, and the intelligent algorithm prediction robustness is poor. Professional personnel need to spend a lot of effort to develop and try to apply complex intelligent algorithms and constantly optimize them, which also restricts the application of membrane pollution process analysis and diagnosis in actual membrane system projects, and the management guidance for actual membrane system projects is poor. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a membrane pollution state evaluation method, device, equipment and medium of a membrane bioreactor, which can master the development potential and state change of membrane pollution by analyzing the membrane pollution monitoring data, evaluate the operation condition adaptability of the membrane system, distinguish the change of reversible membrane pollution and irreversible membrane pollution, and do not need to develop special data processing and analysis software. While ensuring low cost, it also ensures the reliability, stability and accuracy of the monitoring data. The specific scheme is as follows:

[0006] In a first aspect, the present application discloses a membrane pollution state evaluation method of a membrane bioreactor, comprising:

[0007] Periodically collecting membrane pollution monitoring index data of the membrane bioreactor, and generating periodic time sequence data sets for analyzing and evaluating the change of membrane pollution according to the membrane pollution monitoring index data;

[0008] analyzing the membrane pollution monitoring indicator data in the periodic time sequence data set according to a preset pollution evaluation rule to determine an index evaluation value corresponding to a membrane pollution monitoring indicator in the membrane pollution monitoring indicator data;

[0009] determining a pollution state of the membrane bioreactor according to the index evaluation value.

[0010] Optionally, the membrane pollution monitoring indicator data of the membrane bioreactor is periodically collected, and a periodic time sequence data set for analyzing and evaluating membrane pollution changes is generated according to the membrane pollution monitoring indicator data, including:

[0011] collecting data of the membrane bioreactor according to a collection period corresponding to each membrane pollution monitoring indicator of the membrane bioreactor to obtain membrane pollution monitoring indicator data of several periods;

[0012] determining an effective collection period corresponding to each membrane pollution monitoring indicator in the membrane pollution monitoring indicator data of the several periods, and filtering the membrane pollution monitoring indicator data of the several periods based on the effective collection period to obtain invalid data in the membrane pollution monitoring indicator data of the several periods;

[0013] eliminating the invalid data from the membrane pollution monitoring indicator data of the several periods, and eliminating the invalid data in the membrane pollution monitoring indicator data of the several periods to obtain eliminated membrane pollution monitoring indicator data;

[0014] respectively performing mean value processing on data corresponding to each membrane pollution monitoring indicator in the eliminated membrane pollution monitoring indicator data to obtain mean value processed membrane pollution monitoring indicator data;

[0015] generating a periodic time sequence data set for analyzing and evaluating membrane pollution changes based on the mean value processed membrane pollution monitoring indicator data.

[0016] Optionally, the analyzing the membrane pollution monitoring indicator data in the periodic time sequence data set according to a preset pollution evaluation rule to determine an index evaluation value corresponding to a membrane pollution monitoring indicator in the membrane pollution monitoring indicator data includes:

[0017] determining a plurality of target membrane pollution monitoring indicators and an evaluation period corresponding to the plurality of target membrane pollution monitoring indicators based on a preset index evaluation requirement;

[0018] extracting target membrane pollution monitoring indicator data corresponding to the plurality of target membrane pollution monitoring indicators and the evaluation period from the periodic time sequence data set;

[0019] According to the target membrane pollution monitoring index data, index evaluation data corresponding to the evaluation period of the several target membrane pollution monitoring indexes is calculated, and corresponding index evaluation values are calculated according to the index evaluation data.

[0020] Optionally, the calculation of the index evaluation data corresponding to the evaluation period of the several target membrane pollution monitoring indexes according to the target membrane pollution monitoring index data and the calculation of the corresponding index evaluation values according to the index evaluation data include:

[0021] According to the target membrane pollution monitoring index data, data effective mean value, data effective maximum value and / or data effective minimum value corresponding to the evaluation period of the several target membrane pollution monitoring indexes, maximum value mean value corresponding to the data effective maximum value and / or minimum value mean value corresponding to the data effective minimum value are calculated.

[0022] An index initial value is determined by the data effective mean value or the maximum value mean value, and an index change rate, an index change cumulative value and an evaluation period index contribution value are determined by the data effective mean value or the data effective maximum value or the data effective minimum value.

[0023] An evaluation period index change mean value is determined by the difference between the index initial value and the data effective mean value or by the difference between the index initial value and the maximum value mean value.

[0024] An index contribution degree value is determined based on the ratio of the evaluation period index contribution value to the corresponding data effective mean value or the data effective maximum value or the data effective minimum value.

[0025] Optionally, the determination of the pollution state of the membrane bioreactor according to the index evaluation values includes:

[0026] If the index change rate is a negative value, it is determined that the membrane pollution state in the period corresponding to the index change rate is good; if the index change rate is a positive value, it is determined that the membrane pollution state in the period corresponding to the index change rate is serious; if the index change rate changes from a negative value to a positive value in two adjacent periods, it is determined that the membrane pollution state corresponding to the two adjacent periods is aggravated.

[0027] If the evaluation period index change mean value and the index change cumulative value are both negative values, it is determined that there is currently an abnormal membrane pollution.

[0028] If the evaluation period index contribution value is greater than the evaluation period index change mean value or the index contribution degree is in a preset first interval, it is determined that the membrane bioreactor does not have stubborn pollution.

[0029] If the evaluation period index contribution value is less than the evaluation period index change mean value, and the index contribution degree is not in the preset first interval, it is determined that the membrane bioreactor has stubborn pollution.

[0030] Optionally, if the evaluation period index contribution value is less than the evaluation period index change mean value, and the index contribution degree is not in the preset first interval, it is determined that the membrane bioreactor has stubborn pollution, comprising:

[0031] If the evaluation period index contribution value is less than the evaluation period index change mean value, and the index contribution degree is in the preset second interval, it is determined that the membrane bioreactor has stubborn pollution, and the stubborn pollution ratio is less than the preset stubborn pollution ratio threshold.

[0032] If the evaluation period index contribution value is less than the evaluation period index change mean value, and the index contribution degree is in the preset third interval, it is determined that the stubborn pollution ratio of the membrane bioreactor is greater than the preset stubborn pollution ratio threshold.

[0033] In a second aspect, the application discloses a membrane pollution state evaluation device for a membrane bioreactor, comprising:

[0034] A data set generation module is configured to periodically collect membrane pollution monitoring index data of the membrane bioreactor, and generate a periodic time sequence data set for analyzing and evaluating membrane pollution changes according to the membrane pollution monitoring index data.

[0035] A data analysis module is configured to analyze the membrane pollution monitoring index data in the periodic time sequence data set according to a preset pollution evaluation rule, to determine an index evaluation value corresponding to a membrane pollution monitoring index in the membrane pollution monitoring index data.

[0036] A pollution state evaluation module is configured to determine a pollution state of the membrane bioreactor according to the index evaluation value.

[0037] In a third aspect, the application discloses an electronic device, comprising:

[0038] A memory is configured to save a computer program.

[0039] A processor is configured to execute the computer program to implement the membrane pollution state evaluation method for the membrane bioreactor as described above.

[0040] In a fourth aspect, the application discloses a computer readable storage medium configured to save a computer program, wherein the computer program is executed by a processor to implement the membrane pollution state evaluation method for the membrane bioreactor as described above.

[0041] In the present application, the membrane pollution monitoring index data of the membrane bioreactor can be periodically collected, and a periodic time series data set for analyzing and evaluating the membrane pollution change can be generated according to the membrane pollution monitoring index data. The membrane pollution monitoring index data in the periodic time series data set can be analyzed according to a preset pollution evaluation rule to determine the index evaluation value of the membrane pollution monitoring index corresponding to the membrane pollution monitoring index data. The pollution state of the membrane bioreactor can be determined according to the index evaluation value.

[0042] Therefore, by the method of the present application, a periodic time series data set is generated by periodically collecting the membrane pollution monitoring index data of the membrane bioreactor, and the generated data set is used to analyze and evaluate the membrane pollution change. Then, the membrane pollution monitoring index data in the data set is analyzed according to the preset rule to determine the index evaluation value of the membrane pollution monitoring index corresponding to the membrane pollution monitoring index data. Finally, the pollution state of the membrane bioreactor can be determined according to the index evaluation value obtained by the analysis. In this way, the development stage of the membrane pollution can be analyzed, and the data can be analyzed to evaluate the adaptability of the membrane system operation condition, distinguish the degree of change of the reversible membrane pollution and the irreversible membrane pollution, timely guide the on-site operation and maintenance personnel to make targeted condition adjustment or take targeted cleaning measures, and ensure the stable operation of the membrane system. To some extent, the problem of relying on long-term monitoring of membrane system operation data and consuming time and effort is solved, a special data processing and analysis software does not need to be developed, the cost is low, and the reliability, stability and accuracy of the monitoring data are ensured. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can be obtained by the drawings provided by the person skilled in the art without creating labor.

[0044] Figure 1 A membrane pollution state evaluation method flowchart of a membrane bioreactor disclosed in the present application;

[0045] Figure 2 A membrane pollution state evaluation device structure schematic diagram of a membrane bioreactor disclosed in the present application;

[0046] Figure 3 A structure diagram of an electronic device disclosed in the present application. DETAILED DESCRIPTION

[0047] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0048] In the related art, the analysis method for characterizing the membrane pollution process by using sound / optical / electricity and physical chemistry technologies is relatively complex, high in cost, and limited in practicability and simplicity. The method for evaluating the membrane pollution by using the membrane system is affected by various working conditions, and it is difficult to establish an accurate, appropriate and universal pollution mechanism model.

[0049] In order to overcome the above technical problems, the present application discloses a membrane pollution state evaluation method, device, equipment and medium of a membrane bioreactor, which can master the membrane pollution development potential and state change by analyzing the membrane pollution monitoring data, evaluate the membrane system operation condition adaptability, distinguish the reversible membrane pollution and irreversible membrane pollution degree change, and do not need to develop special data processing and analysis software, which ensures the reliability, stability and accuracy of the monitoring data while ensuring the low cost.

[0050] Referring to Figure 1 The present application discloses a membrane pollution state evaluation method of a membrane bioreactor, which comprises:

[0051] In step S11, the membrane pollution monitoring index data of the membrane bioreactor is periodically collected, and a periodic time sequence data set for analyzing and evaluating the membrane pollution change is generated according to the membrane pollution monitoring index data.

[0052] In the embodiment, the membrane pollution monitoring index data of the membrane bioreactor is collected, and then the periodic time sequence data set is generated according to the collected data. Specifically, the membrane bioreactor is data collected according to the collection period corresponding to each membrane pollution monitoring index of the membrane bioreactor, so as to obtain the membrane pollution monitoring index data of several periods. It should be noted that different membrane pollution monitoring indexes of the membrane bioreactor correspond to different collection periods. For example, in the constant flow operation mode of the membrane bioreactor, the collection period of important data such as transmembrane pressure difference and specific membrane flux can be set to 5-10 seconds, and the collection of indexes such as water quality and temperature which change slowly can be set to 1 minute. And the collected data needs to be collected within the effective collection period of filtration or water production, and within the 95%-105% effective confidence interval of the preset working condition control parameter. The working condition control parameters include but are not limited to the following indexes: water production or backwash flow in constant flow mode, or water inlet pressure, water production pressure, water outlet pressure and design temperature in constant pressure control mode.

[0053] Further, in order to select effective monitoring data, it is necessary to eliminate invalid data and abnormal data in the membrane pollution monitoring index data of several periods to obtain the membrane pollution monitoring index data after elimination. Specifically, it is necessary to determine the effective collection period corresponding to each membrane pollution monitoring index in the membrane pollution monitoring index data of several periods, and filter the membrane pollution monitoring index data of several periods based on the effective collection period to obtain invalid data in the membrane pollution monitoring index data of several periods. During data collection, non-effective period data may be collected, so it is necessary to filter the membrane pollution monitoring index data of several periods according to the effective collection period corresponding to each membrane pollution monitoring index. For example, during the period when the membrane filtration system or water production equipment stops running; during at least one running period in the initial period after the membrane filtration system starts running or after cleaning; and during the period of 5 to 120 seconds after the filtration, cleaning or circulation equipment restarts. Therefore, it is necessary to filter the data based on the effective collection period, and then determine the invalid data in the membrane pollution monitoring index data of several periods. Then, the invalid data needs to be eliminated to obtain the first membrane pollution monitoring index data after elimination. In the data processing stage, abnormal data in the first membrane pollution monitoring index data after elimination can be finally identified, for example, due to the influence of equipment working condition mutation, instrument information loss or signal transmission distortion or other external interference factors, the instantaneous characteristic index may exhibit abnormal values or fluctuations, such as data loss or instantaneous mutation. Therefore, the related abnormal data needs to be identified and eliminated from the first membrane pollution monitoring index data after elimination to obtain the second membrane pollution monitoring index data after elimination.

[0054] In this embodiment, the data corresponding to each membrane pollution monitoring index in the membrane pollution monitoring index data after elimination needs to be processed by mean value to obtain the membrane pollution monitoring index data after mean value; and the periodic time sequence data set for analyzing and evaluating the change of membrane pollution is generated based on the membrane pollution monitoring index data after mean value. It needs to be noted that, in order to avoid the influence of instantaneous data abnormality or fluctuation on the evaluation of monitoring evaluation index change, the mean value of evaluation index in a plurality of continuous collection periods in the effective collection period is taken as the effective evaluation value to constitute the periodic time sequence data set.

[0055] In this way, the data quality of the constructed data set can be ensured, and the processed data is the data required for membrane pollution state evaluation. In this way, the accuracy of membrane pollution state evaluation is indirectly improved by controlling the data quality.

[0056] Step S12, according to the preset pollution evaluation rule, the membrane pollution monitoring index data in the periodic time sequence data set is analyzed to determine the index evaluation value corresponding to the membrane pollution monitoring index in the membrane pollution monitoring index data.

[0057] In this embodiment, the membrane pollution monitoring index data in the data set needs to be analyzed to determine the index evaluation value corresponding to the membrane pollution monitoring index in the membrane pollution monitoring index data. Specifically, a plurality of target membrane pollution monitoring indexes and evaluation periods corresponding to the plurality of target membrane pollution monitoring indexes need to be determined based on the preset index evaluation requirements, that is, different lengths of evaluation periods need to be selected for evaluation according to the actual operation condition of the membrane system, the evaluation analysis purpose or requirement. The evaluation period includes at least one complete filtration operation period, and the filtration operation period includes at least one water production, stop and water washing cycle process. On this basis, at least two or more key indexes (such as membrane flux, specific membrane flux, transmembrane pressure difference, certain water quality index, removal rate, etc.) are selected from the above-mentioned membrane pollution time sequence data set to realize comprehensive evaluation and analysis of the membrane pollution state, thereby improving the scientificity and integrity of the membrane pollution evaluation result. It needs to be noted that the evaluation period is the period for evaluating the index, for example, the index in a single filtration operation period is evaluated, and the evaluation period is a single filtration operation period. If the index in multiple filtration operation periods is evaluated, the evaluation period is the corresponding multiple filtration operation periods.

[0058] Further, target membrane pollution monitoring index data corresponding to the plurality of target membrane pollution monitoring indexes and the evaluation period need to be extracted from the periodic time sequence data set, and then the index evaluation data of the plurality of target membrane pollution monitoring indexes in the evaluation period is calculated according to the target membrane pollution monitoring index data, and the corresponding index evaluation value is calculated according to the index evaluation data. It needs to be noted that the values of each index in the membrane pollution monitoring index data set can be expressed and analyzed in multiple ways. For example, the effective mean value, effective maximum value or effective minimum value of the membrane pollution monitoring index in the water production stage of a single filtration operation period can be used to represent; the effective mean value, effective maximum value or effective minimum value of the membrane pollution monitoring index in the water production stage of a plurality of continuous filtration operation periods can be used to represent; in addition, the effective mean value, effective maximum value and / or effective minimum value of the membrane pollution monitoring index in a plurality of water production periods in a plurality of hours or a day, or the effective mean value of the corresponding monitoring index maximum value or minimum value can be used to represent. Therefore, the effective mean value, effective maximum value and / or effective minimum value of the data, the maximum value mean value corresponding to the effective maximum value of the data and / or the minimum value mean value corresponding to the effective minimum value of the data of the plurality of target membrane pollution monitoring indexes in the evaluation period can be calculated according to the target membrane pollution monitoring index data.

[0059] For example, the transmembrane pressure (TMP) is taken as an example:

[0060] The effective mean value of TMP in a single water production process is denoted as: ;

[0061] The effective maximum value of TMP in a single operation cycle is recorded as: ;

[0062] The effective minimum value of TMP in a single operation cycle is recorded as: ;

[0063] The maximum value of the effective maximum value of TMP in a single operation cycle is recorded as: ;

[0064] The minimum value of the effective minimum value of TMP in a single operation cycle is recorded as: .

[0065] Among them, the initial value of the index needs to be determined by the effective average value or the maximum average value. Specifically, when calculating the initial transmembrane pressure value, the initial running period of the membrane bio-reactor (Membrane Bio-Reactor, MBR) system has not yet entered a stable state, and it is preferred to start from the j (j>1)th running cycle, which is the initial running period of the membrane system, and the corresponding time is recorded as t0. The TMP at the water production stage of the initial running cycle is taken as: av,j or The initial value of the transmembrane pressure TMP0 is calculated as: or , with units of kPa.

[0066] Among them, the index change rate, the evaluation period index change average, and the evaluation period index contribution value need to be determined by the effective average value or the effective maximum value or the effective minimum value of the data. Specifically, the index change rate k can be expressed in multiple forms. For example, in the jth running cycle, the approximate linear fitting change rate of the effective value of the transmembrane pressure in the ith water production process can be expressed as:

[0067] , where j>1 and the unit is kPa / min;

[0068] It needs to be noted that, represents the change value of the transmembrane pressure in unit time . k j,i is the change rate of the transmembrane pressure in a single continuous water production filtration. By analyzing this index, the rationality of the parameters such as water production filtration length, water production amount, or membrane flux can be evaluated, and the membrane pollution change trend under the corresponding conditions can also be evaluated.

[0069] Further, the index change rate k can be calculated by approximately linear fitting of the n transmembrane pressure effective average values TMP av,j,i or the n transmembrane pressure effective maximum values TMP max,j,i in the jth running cycle, which is recorded as:

[0070] or , unit is kPa / minute;

[0071] It should be noted that k j This is the intermittent rate of change of transmembrane pressure differential during an operating cycle, including periods of water production downtime. By analyzing this parameter, the rationality of operating conditions, including cycle downtime parameters, can be assessed, as well as the membrane fouling trend under these conditions.

[0072] Among them, the cumulative value of indicator change C j The mean transmembrane pressure difference TMP in the first water production process in the jth operation cycle av,j,1 (or maximum TMP max,j,1 ) and the i-th time (1 <i≤n)产水过程内跨膜压差均值TMP av,j,i (or maximum TMP max,j+1,i ), recorded as: ;or , unit is kPa.

[0073] It should be noted that the cumulative value of indicator change C j It reflects the cumulative value of the pressure difference change caused by the accumulated membrane fouling (including reversible fouling and / or irreversible fouling) on ​​the membrane surface or in the pores during the j-th operating cycle, and is used to evaluate the fouling trend of membrane pollutant accumulation or membrane pore blockage during the operating cycle.

[0074] Among them, the contribution value of the evaluation cycle indicator E j The mean transmembrane pressure difference TMP in the first water production process in the j+1th operation cycle av,j+1,1 (or maximum TMP max,j+1,1 ), and the mean transmembrane pressure difference TMP during the nth water production process in the jth operation cycle av,j,n (or maximum TMP max,j,n ), recorded as: E j =TMP av,j,n - TMP av,j+1,1 or E j =TMP max, j, n - TMP max, j+1,1 , unit is kPa.

[0075] It should be noted that the evaluation cycle indicator contribution value E j It reflects the contribution of membrane pollutants that are easily removed by cleaning to the transmembrane pressure difference after the j-th backwash or cleaning, which serves as the j-th reversible pollution evaluation index.

[0076] Further, the evaluation period index change average value D is determined by the difference between the index initial value and the data effective average value or by the difference between the index initial value and the maximum average value. Specifically, the evaluation period index change average value D is represented by the following formula: j TMP is the average value of the transmembrane pressure difference in the n water production processes in the j operation period. av,j TMP is the maximum average value of the transmembrane pressure difference. The difference between the corresponding initial reference value TMP0 and the average value is represented by the following formula: or , and the unit is kPa.

[0077] It should be noted that the evaluation period index change average value D j represents the pressure difference change index caused by the accumulation of membrane pollutants on the surface or the blockage of pores after the membrane system has been running for j cycles, and is used to evaluate the degree of membrane pollution accumulated in the membrane system after the membrane system has been running for j operation cycles.

[0078] Further, the index contribution degree value P is determined based on the ratio of the evaluation period index contribution value to the corresponding data effective average value or data effective maximum value or data effective minimum value. Specifically, the index contribution degree value P is represented by the following formula: j P represents the contribution degree or proportion of the transmembrane pressure difference increase caused by the jth reversible pollution, and the index contribution degree value P is represented by the following formula: j = (E j / TMP max, j, n ).

[0079] It should be noted that the index contribution degree value P j can be used to evaluate the effect of backwashing or cleaning on removing membrane pollution.

[0080] Therefore, the pollution state of the membrane bioreactor can be evaluated by the above-mentioned indexes, which provides a theoretical basis for the pollution state evaluation of the membrane bioreactor and effectively improves the accuracy of the pollution state evaluation of the membrane bioreactor.

[0081] In step S13, the pollution state of the membrane bioreactor is determined according to the index evaluation value.

[0082] In this embodiment, the pollution state of the membrane bioreactor is determined based on the determined index evaluation value. If the index change rate is negative, it is determined that the membrane pollution state in the period corresponding to the index change rate is good. If the index change rate is positive, it is determined that the membrane pollution state in the period corresponding to the index change rate is serious. If the index change rate changes from negative to positive in two adjacent periods, it is determined that the membrane pollution state corresponding to the two adjacent periods is aggravated. Specifically, in the initial or early period of the MBR system operation, the index change rate k j,iThere can be fluctuation changes, negative values in some periods, positive values in some periods, and the index change rate gradually increases and tends to be positive as the membrane system continuously runs. If the index change rate is negative during the current water production process, it may be due to the fact that at the beginning of the cycle water production, the pollutants in the filtrate tend to accumulate on the membrane surface under the action of filtration pressure, resulting in a rapid increase in transmembrane pressure difference in a short time. However, these pollutants accumulate to a certain thickness on the membrane surface, but due to the loose density of the accumulation, they are easily affected by the stripping effect of external water or gas flushing and separated from the membrane surface. In this case, the membrane fouling shows a certain degree of reversibility, and the probability of entering the membrane hole to block the filter channel is low. At the same time, the effective filter channels in the local area of the membrane surface can be reopened, so that the transmembrane pressure difference decreases in the later stage of the water production process. This shows that the membrane fouling potential or degree is low at this stage, so it can be determined that the current membrane fouling state is good.

[0083] On the other hand, if the index change rate is positive during the current water production process, it may be that the pollutants in the filtrate accumulate on the membrane surface with relatively large pollution potential. In this case, some membrane pollutants may have a certain interfacial chemical potential with the membrane surface, so they are relatively more likely to adhere to the membrane surface, and the stripping effect of external water or gas flushing may not be able to remove the membrane pollutants from the membrane surface in a short time, thereby causing irreversible membrane fouling to occur. In addition, the probability of pollutants entering the membrane filter channel to cause hole blockage increases, further aggravating the degree of membrane fouling, and this process corresponds to the continuous rising trend of the transmembrane pressure difference during the water production process period. Therefore, it can be determined that the current membrane fouling state is serious.

[0084] In another aspect, if the index change rate is negative in one water production period and positive in another period, this fluctuation change reflects the dynamic characteristics of membrane fouling behavior. As the membrane system continuously produces water and filters, the amount of pollutants in the feed water accumulated on the membrane surface increases, and the tendency of pollutants in the filtrate to accumulate on the membrane surface under the action of filtration pressure eventually reaches a steady state balance with the stripping tendency of external water or gas flushing. At this time, the index change rate changes from approximately zero to positive, indicating that the amount of pollutants in the filtered liquid accumulated on the membrane surface or in the membrane hole begins to gradually increase, and the membrane fouling develops to a certain extent. It can be determined that the membrane fouling states corresponding to the adjacent two periods gradually increase.

[0085] It needs to be explained that in addition to the filtration pressure and the influence of external hydraulic or gas scouring, the accumulation of membrane pollution on the surface of the MBR membrane is also affected by a variety of factors, including system operating conditions (such as water production flux, filtration duration and cycle times, etc.), influent water quality (such as changes in pollutant types and concentrations, etc.), environmental temperature, pH or microorganisms and other influencing factors. These factors jointly determine the development trend of membrane pollution and its influence on the filtration performance of the MBR membrane system. Therefore, starting from the theory of membrane filtration or permeation, the membrane pollution state can be judged by evaluating the mean value of the cycle index change and the cumulative value of the index change. In the process of membrane permeation or filtration, the mean value of the cycle index change and the cumulative value of the index change are normally positive values. If the mean value of the cycle index change and the cumulative value of the index change are both negative values, it indicates that there may be signal drift or instability of the monitoring instrument, which may lead to abnormal data, or there are pollutants that are intercepted or adsorbed on the local surface or pores of the membrane during the filtration process, which are detached from the membrane surface under the action of external aeration scouring or membrane filament shaking, thereby causing the transmembrane pressure difference to decrease. At this time, it can be determined that there is an abnormal membrane pollution.

[0086] It further needs to be explained that when the reversible pollution evaluation index evaluation cycle index contribution value in the corresponding water production stage in several operation cycles is greater than the mean value of the evaluation cycle index change, or the index contribution degree is in the preset first interval (0.6, 0.9), it indicates that the jth backwashing or cleaning will remove part or most of the pollutants accumulated or adhered on the membrane surface or clogged in the membrane pores, which have not been compressed or compacted and are easy to clean, reflecting that the type of membrane pollution contribution in the current j operation period is mainly reversible pollution type, and the degree of membrane pollution is relatively light, so it can be determined that the membrane bioreactor does not have stubborn pollution.

[0087] On the other hand, when the reversible pollution evaluation index evaluation cycle index contribution value in the corresponding water production stage in several operation cycles is less than the mean value of the evaluation cycle index change, or the index contribution degree is not in the preset first interval, it is determined that the membrane bioreactor has stubborn pollution. Specifically, when the evaluation cycle index contribution value is less than the mean value of the evaluation cycle index change, and the index contribution degree is in the preset second interval (0.4, 0.6), it indicates that the continuous several water backwashing or other physical cleaning in this period can only strip and remove part of the pollutants accumulated on the membrane surface, and the proportion of pollutants that are not easy to remove is increasing, indicating that the type of membrane pollution is changing from easy-to-remove pollution type to non-removable pollution type, so it can be determined that the membrane bioreactor has stubborn pollution, and the stubbornness ratio is less than the preset stubborn pollution ratio threshold.

[0088] In still another aspect, if the evaluation period index contribution value is less than the evaluation period index change mean value, and the index contribution degree is in a preset third interval (less than 0.4), it indicates that at this time, the membrane pollution contribution type is mainly not easy to remove pollution. At this time, the reverse washing or other mechanical cleaning under the secondary operating condition may temporarily be difficult to remove most of the pollutants on the membrane surface or membrane pores from the membrane. Define this time as the membrane reversible pollution critical cleaning time, and after the running period ends, this time can be used as a trigger judgment condition for adjusting the physical cleaning such as reverse washing time or reverse washing intensity, and increasing chemical cleaning such as chemical strengthening cleaning.

[0089] In the embodiment, the periodically collected membrane pollution monitoring index data of the membrane bioreactor need to generate a periodic time sequence data set, and the generated data set is used to analyze and evaluate the membrane pollution change. Then the membrane pollution monitoring index data in the data set needs to be analyzed according to the preset rules to determine the index evaluation value of the membrane pollution monitoring index corresponding to the membrane pollution monitoring index data. Finally, the pollution state of the membrane bioreactor can be determined according to the index evaluation value obtained by the analysis. In this way, the development potential and state change of the membrane pollution can be mastered through the membrane pollution monitoring data analysis, the operation condition adaptability of the membrane system can be evaluated, the reversible membrane pollution and irreversible membrane pollution degree change can be distinguished, the on-site operation and maintenance personnel can be guided to make targeted condition adjustment or take targeted cleaning measures in time, and the stable operation of the membrane system is ensured. To some extent, the problem of relying on long-term monitoring of membrane system operation data and consuming time and effort is solved, a special data processing and analysis software does not need to be developed, the cost is low, and the reliability, stability and accuracy of the monitoring data are ensured.

[0090] As a preferred embodiment, when evaluating the membrane pollution state of the membrane bioreactor, a mixed method of multiple indexes can be used for evaluation, for example, the mixed method of membrane specific flux and transmembrane pressure difference is used for evaluation of the membrane pollution state, and the calculation method of the index evaluation value corresponding to the membrane specific flux is similar to that of the transmembrane pressure difference, which is described in the content recorded in step S12, and will not be described here. In the initial several running periods of the membrane bioreactor (MBR) system, if the transmembrane pressure difference change rate k j,i and the cumulative change value C j are continuously and stably positive, and the change values thereof all exceed the set threshold range, and the membrane specific flux change value (K) is within the preset membrane specific flux change threshold range, it indicates that one or more conditions (such as water production, aeration amount, filtration period length, etc., influent water quality or temperature, etc.) of the current operating condition may not be suitable for the normal operation of the current membrane system. At this time, the related operating condition parameters need to be checked or adjusted to ensure the stability of the system operation.

[0091] As a preferred embodiment, the periodic acquisition of the membrane pollution monitoring index data of the membrane bioreactor needs to use various instruments, including but not limited to water production flow meters, water production pressure, water production temperature, and water quality detection instruments, and the like.

[0092] Referring to Figure 2 As shown in the drawings, the embodiment of the present application discloses a membrane pollution state evaluation device of a membrane bioreactor, which comprises:

[0093] The data set generation module 11 is configured to periodically acquire the membrane pollution monitoring index data of the membrane bioreactor, and generate a periodic time sequence data set for analyzing and evaluating the membrane pollution change according to the membrane pollution monitoring index data.

[0094] The data analysis module 12 is configured to analyze the membrane pollution monitoring index data in the periodic time sequence data set according to a preset pollution evaluation rule, so as to determine the index evaluation value of the membrane pollution monitoring index corresponding to the membrane pollution monitoring index data.

[0095] The pollution state evaluation module 13 is configured to determine the pollution state of the membrane bioreactor according to the index evaluation value.

[0096] In the embodiment, the periodic time sequence data set is generated by periodically acquiring the membrane pollution monitoring index data of the membrane bioreactor, and the generated data set is used to analyze and evaluate the membrane pollution change. Then, the membrane pollution monitoring index data in the data set is analyzed according to the preset rule, so as to determine the index evaluation value of the membrane pollution monitoring index corresponding to the membrane pollution monitoring index data. Finally, the pollution state of the membrane bioreactor can be determined according to the index evaluation value obtained by the analysis. In this way, the development potential and state change of the membrane pollution can be mastered by analyzing the membrane pollution monitoring data, the operation condition adaptability of the membrane system can be evaluated, the degree of change of the reversible membrane pollution and the irreversible membrane pollution can be distinguished, the on-site operation and maintenance personnel can be guided to make targeted condition adjustment or take targeted cleaning measures in time, and the stable operation of the membrane system is ensured. To some extent, the problem of relying on long-term monitoring of membrane system operation data and consuming time and effort is solved, a special data processing and analysis software does not need to be developed, the cost is low, and the reliability, stability and accuracy of the monitoring data are ensured.

[0097] In some embodiments, the data set generation module 11 can specifically comprise:

[0098] The data acquisition unit is configured to acquire data of the membrane bioreactor according to the acquisition period corresponding to each membrane pollution monitoring index of the membrane bioreactor, so as to obtain the membrane pollution monitoring index data of several periods.

[0099] a data filtering unit, configured to determine an effective collection time period corresponding to each membrane pollution monitoring indicator in the membrane pollution monitoring indicator data of the plurality of periods, and filter the membrane pollution monitoring indicator data of the plurality of periods based on the effective collection time period to obtain invalid data in the membrane pollution monitoring indicator data of the plurality of periods;

[0100] a data elimination unit, configured to eliminate the invalid data from the membrane pollution monitoring indicator data of the plurality of periods, and eliminate the invalid data in the membrane pollution monitoring indicator data of the plurality of periods to obtain post-elimination membrane pollution monitoring indicator data;

[0101] a data mean unit, configured to perform mean processing on data corresponding to each membrane pollution monitoring indicator in the post-elimination membrane pollution monitoring indicator data respectively to obtain post-mean membrane pollution monitoring indicator data;

[0102] a data set generation unit, configured to generate a periodic time sequence data set for analyzing and evaluating membrane pollution changes based on the post-mean membrane pollution monitoring indicator data.

[0103] In some embodiments, the data analysis module 12 can specifically include:

[0104] an evaluation parameter determination sub-module, configured to determine a plurality of target membrane pollution monitoring indicators based on a preset index evaluation requirement, and an evaluation period corresponding to the plurality of target membrane pollution monitoring indicators;

[0105] a data extraction sub-module, configured to extract target membrane pollution monitoring indicator data corresponding to the plurality of target membrane pollution monitoring indicators and the evaluation period from the periodic time sequence data set;

[0106] a data calculation sub-module, configured to calculate index evaluation data of the plurality of target membrane pollution monitoring indicators in the evaluation period according to the target membrane pollution monitoring indicator data, and calculate a corresponding index evaluation value according to the index evaluation data.

[0107] In some embodiments, the data calculation sub-module can specifically include:

[0108] a first data calculation unit, configured to calculate a data effective mean value, a data effective maximum value and / or a data effective minimum value of the plurality of target membrane pollution monitoring indicators in the evaluation period, a maximum value mean value corresponding to the data effective maximum value and / or a minimum value mean value corresponding to the data effective minimum value according to the target membrane pollution monitoring indicator data;

[0109] a second data calculation unit configured to determine an initial value of an index based on the valid data mean value or the maximum value mean value, and determine a change rate of the index, a cumulative value of the index change, and a contribution value of the index of the evaluation period based on the valid data mean value or the valid data maximum value or the valid data minimum value;

[0110] a third data calculation unit configured to determine a change mean value of the index of the evaluation period based on a difference between the initial value of the index and the valid data mean value or a difference between the initial value of the index and the maximum value mean value;

[0111] a fourth data calculation unit configured to determine a contribution degree value of the index based on a ratio of the contribution value of the index of the evaluation period to the valid data mean value or the valid data maximum value or the valid data minimum value.

[0112] In some embodiments, the pollution state evaluation module 13 can specifically include:

[0113] a state judgment sub-module configured to determine that a membrane pollution state of a time period corresponding to the change rate of the index is good if the change rate of the index is negative, determine that the membrane pollution state of the time period corresponding to the change rate of the index is serious if the change rate of the index is positive, and determine that the membrane pollution state corresponding to two adjacent time periods is aggravated if the change rate of the index changes from negative to positive in the two adjacent time periods;

[0114] a first pollution judgment sub-module configured to determine that there is an abnormal membrane pollution if both the change mean value of the index of the evaluation period and the cumulative value of the index change are negative;

[0115] a second pollution judgment sub-module configured to determine that there is no stubborn pollution in the membrane bioreactor if the contribution value of the index of the evaluation period is greater than the change mean value of the index of the evaluation period or the contribution degree of the index is in a preset first interval;

[0116] a third pollution judgment sub-module configured to determine that there is stubborn pollution in the membrane bioreactor if the contribution value of the index of the evaluation period is less than the change mean value of the index of the evaluation period and the contribution degree of the index is not in the preset first interval.

[0117] In some embodiments, the third pollution judgment sub-module can further include:

[0118] a first pollution judgment unit configured to determine that there is stubborn pollution in the membrane bioreactor if the contribution value of the index of the evaluation period is less than the change mean value of the index of the evaluation period and the contribution degree of the index is in a preset second interval, and a stubborn pollution ratio is less than a preset stubborn pollution ratio threshold value;

[0119] The second pollution judgment unit is configured to determine that the stubborn pollution proportion of the membrane bioreactor is greater than the preset stubborn pollution proportion threshold if the evaluation period index contribution value is less than the evaluation period index change mean value and the index contribution degree is in a preset third interval.

[0120] Further, the embodiment of the present application further discloses an electronic device, Figure 3 is an electronic device 20 structure diagram shown according to an exemplary embodiment, the contents in the figure cannot be considered as any limitation on the use range of the present application.

[0121] Figure 3 The electronic device 20 structure diagram provided by the embodiment of the present application. The electronic device 20, specifically can include: at least one processor 21, at least one memory 22, power supply 23, communication interface 24, input output interface 25 and communication bus 26. Wherein, the memory 22 is used for storing computer program, the computer program is loaded and executed by the processor 21, to realize the related steps in the membrane pollution state evaluation method of membrane bioreactor disclosed in any preceding embodiment. In addition, the electronic device 20 in the embodiment of the present application specifically can be electronic computer.

[0122] In the embodiment, the power supply 23 is used for providing working voltage for each hardware device on the electronic device 20; the communication interface 24 can create data transmission channel between the electronic device 20 and external device, and the communication protocol followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited here; the input output interface 25 is used for obtaining external input data or outputting data to the outside world, and the specific interface type can be selected according to the specific application needs, which is not specifically limited here.

[0123] In addition, the memory 22 as the carrier of resource storage can be read-only memory, random access memory, disk or optical disk, etc., and the resources stored thereon can include operating system 221, computer program 222, etc., and the storage mode can be temporary storage or permanent storage.

[0124] Wherein, the operating system 221 is used for managing and controlling each hardware device on the electronic device 20 and the computer program 222, which can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program capable of completing the membrane pollution state evaluation method of membrane bioreactor executed by the electronic device 20 disclosed in any preceding embodiment, the computer program 222 can further include computer program capable of completing other specific work.

[0125] Further, the application also discloses a computer readable storage medium for storing a computer program; wherein the computer program is executed by a processor to realize the membrane pollution state evaluation method of the membrane bioreactor disclosed above. The specific steps of the method can refer to the corresponding content disclosed in the foregoing embodiments, and will not be described here in detail.

[0126] The various embodiments are described in the specification by progressive stages, and each embodiment focuses on the difference from other embodiments. The same or similar parts between various embodiments can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant part can refer to the method part.

[0127] The skilled person can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly show the interchangeability of hardware and software, the components and steps of the examples have been described in the above description. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the application.

[0128] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, a software module executed by a processor, or a combination of both. The software module can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0129] Finally, it should be noted that, in this document, relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0130] The technical solutions provided by the present application are described in detail above, and the principles and implementation manners of the present application are described by using specific examples. The above description of the examples is only used to help understand the method of the present application and its core idea; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manners and application ranges will be changed, and the above description of the content of the specification should not be understood as a limitation on the present application.

Claims

1. A method for evaluating the membrane fouling state of a membrane bioreactor, characterized in that: include: Periodically collecting membrane fouling monitoring index data of a membrane bioreactor, and generating a periodic time series data set for analyzing and evaluating membrane fouling changes based on the membrane fouling monitoring index data; Analyzing the membrane pollution monitoring index data in the periodic time series data set according to a preset pollution evaluation rule to determine an index evaluation value corresponding to the membrane pollution monitoring index in the membrane pollution monitoring index data; The contamination state of the membrane bioreactor is determined according to the indicator evaluation value.

2. The membrane fouling state evaluation method of a membrane bioreactor according to claim 1, characterized in that: The periodic collection of membrane fouling monitoring index data of the membrane bioreactor and the generation of a periodic time series data set for analyzing and evaluating membrane fouling changes based on the membrane fouling monitoring index data include: Collecting data from the membrane bioreactor according to the collection period corresponding to each membrane fouling monitoring indicator of the membrane bioreactor to obtain membrane fouling monitoring indicator data for several periods; determining an effective collection period corresponding to each membrane pollution monitoring indicator in the membrane pollution monitoring indicator data of the plurality of cycles, and filtering the membrane pollution monitoring indicator data of the plurality of cycles based on the effective collection period to obtain invalid data in the membrane pollution monitoring indicator data of the plurality of cycles; Eliminating the invalid data from the membrane pollution monitoring index data of the plurality of cycles, and eliminating the invalid data in the membrane pollution monitoring index data of the plurality of cycles to obtain eliminated membrane pollution monitoring index data; Performing mean processing on the data corresponding to each membrane fouling monitoring index in the eliminated membrane fouling monitoring index data to obtain mean membrane fouling monitoring index data; A periodic time series data set for analyzing and evaluating membrane pollution changes is generated based on the averaged membrane pollution monitoring index data.

3. The method for evaluating membrane fouling status of a membrane bioreactor according to any one of claims 1 or 2, characterized in that: The analyzing the membrane pollution monitoring index data in the periodic time series data set according to the preset pollution evaluation rule to determine the index evaluation value corresponding to the membrane pollution monitoring index in the membrane pollution monitoring index data includes: Determining a number of target membrane fouling monitoring indicators and evaluation cycles corresponding to the number of target membrane fouling monitoring indicators based on preset indicator evaluation requirements; Extracting target membrane fouling monitoring indicator data corresponding to the plurality of target membrane fouling monitoring indicators and the evaluation period from the periodic time series data set; The indicator evaluation data corresponding to the target membrane pollution monitoring indicators in the evaluation period are calculated according to the target membrane pollution monitoring indicator data, and the corresponding indicator evaluation values ​​are calculated according to the indicator evaluation data.

4. The method for evaluating membrane fouling status of a membrane bioreactor according to claim 3, characterized in that: The step of calculating the index evaluation data corresponding to the target membrane pollution monitoring indexes in the evaluation period according to the target membrane pollution monitoring index data, and calculating the corresponding index evaluation values ​​according to the index evaluation data, includes: Calculate, based on the target membrane pollution monitoring indicator data, the effective mean value of the data, the effective maximum value of the data and / or the effective minimum value of the data corresponding to the effective maximum value of the data, and / or the average value of the minimum value corresponding to the effective minimum value of the data for the target membrane pollution monitoring indicators in the evaluation period; Determine the initial value of the indicator by the effective mean value of the data or the maximum mean value, and determine the indicator change rate, the cumulative value of the indicator change and the evaluation period indicator contribution value by the effective mean value of the data or the effective maximum value of the data or the effective minimum value of the data; Determine the evaluation period indicator change mean value by the difference between the initial value of the indicator and the effective mean value of the data or by the difference between the initial value of the indicator and the mean value of the maximum value; The indicator contribution degree value is determined based on the ratio of the evaluation period indicator contribution value to the corresponding data effective mean value or the data effective maximum value or the data effective minimum value.

5. The method for evaluating membrane fouling status of a membrane bioreactor according to claim 4, characterized in that: Determining the contamination state of the membrane bioreactor according to the indicator evaluation value includes: If the index change rate is a negative value, it is determined that the membrane fouling state in the period corresponding to the index change rate is good; if the index change rate is a positive value, it is determined that the membrane fouling state in the period corresponding to the index change rate is serious; if the index change rate changes from a negative value to a positive value in two adjacent periods, it is determined that the membrane fouling state corresponding to the two adjacent periods is aggravated; If the mean value of the change in the evaluation period indicator and the cumulative value of the change in the indicator are both negative, it is determined that there is currently an abnormal membrane fouling; If the evaluation period indicator contribution value is greater than the evaluation period indicator change mean value or the indicator contribution degree is within a preset first interval, it is determined that the membrane bioreactor does not have stubborn contamination; If the evaluation period indicator contribution value is less than the evaluation period indicator change mean value, and the indicator contribution degree is not within the preset first interval, it is determined that stubborn contamination exists in the membrane bioreactor.

6. The method for evaluating membrane fouling status of a membrane bioreactor according to claim 5, characterized in that: If the evaluation period indicator contribution value is less than the evaluation period indicator change mean value, and the indicator contribution degree is not within the preset first interval, then determining that the membrane bioreactor has stubborn contamination includes: If the evaluation period indicator contribution value is less than the evaluation period indicator change mean value, and the indicator contribution degree is within the preset second interval, it is determined that the membrane bioreactor has stubborn fouling, and the stubborn fouling ratio is less than the preset stubborn fouling ratio threshold; If the evaluation period indicator contribution value is less than the evaluation period indicator change mean value, and the indicator contribution degree is within the preset third interval, it is determined that the stubborn fouling ratio of the membrane bioreactor is greater than the preset stubborn fouling ratio threshold.

7. A membrane fouling status evaluation device for a membrane bioreactor, characterized in that: include: A data set generation module is used to periodically collect membrane fouling monitoring index data of the membrane bioreactor, and generate a periodic time series data set for analyzing and evaluating membrane fouling changes based on the membrane fouling monitoring index data; a data analysis module, configured to analyze the membrane pollution monitoring index data in the periodic time series data set according to a preset pollution evaluation rule to determine an index evaluation value corresponding to the membrane pollution monitoring index in the membrane pollution monitoring index data; The pollution state evaluation module is used to determine the pollution state of the membrane bioreactor according to the indicator evaluation value.

8. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the membrane fouling status evaluation method of a membrane bioreactor according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that Used to store a computer program, wherein when the computer program is executed by a processor, the method for evaluating the membrane fouling state of a membrane bioreactor according to any one of claims 1 to 6 is implemented.

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