Method and system for evaluating service life of nanofiltration membrane for water treatment and electronic equipment

Abstract

The invention belongs to the technical field of water treatment, and particularly relates to a method and system for evaluating the service life of a nanofiltration membrane for water treatment and electronic equipment. According to the method, a multi-dimensional evaluation index system covering the membrane performance of the nanofiltration membrane, the operation cost of the nanofiltration membrane and the effluent quality of the nanofiltration membrane is constructed, the index weight is determined in combination with a subjective and objective comprehensive weighting method, a quantitative evaluation model is established, and whether the nanofiltration membrane needs to be replaced or not is judged by calculating a comprehensive evaluation index and comparing the comprehensive evaluation index with a preset threshold value. The method solves the problems that the existing nanofiltration membrane replacement condition depends on artificial experience, lacks objective judgment basis and is insufficient in rationality, can maximize the use value of the nanofiltration membrane and reduce the comprehensive operation cost of a drinking water treatment system on the premise of ensuring that the effluent quality reaches the standard, and is suitable for various drinking water treatment nanofiltration systems.

Description

Technical Field

[0001] This invention belongs to the field of water treatment technology, and specifically relates to a method, system, and electronic device for evaluating the lifetime of nanofiltration membranes used in water treatment. Background Technology

[0002] Nanofiltration membranes, as an important branch of membrane separation technology, offer separation performance between ultrafiltration and reverse osmosis, and can precisely retain molecular weights up to 200. Organic compounds (such as dyes and humic acid) and salt ions (such as divalent anions) with a value of 2000 Da have important applications in deep treatment of industrial wastewater and purification of drinking water.

[0003] Nanofiltration membranes are core components of advanced drinking water treatment systems, and their operational status directly impacts effluent quality and treatment costs. During long-term operation, nanofiltration membranes experience performance degradation due to fouling and wear, necessitating timely replacement to ensure water supply safety. Currently, the determination of nanofiltration membrane replacement milestones in the water treatment industry is primarily based on single indicators (such as decreased membrane flux or a doubling of transmembrane pressure differential) or the operational experience of staff. This approach has significant drawbacks: it focuses solely on membrane performance parameters, neglecting the synergistic effects of operating costs and water quality compliance thresholds. This leads to replacement decisions that are either overly conservative (premature replacement wastes membrane resources) or overly risky (delayed replacement results in substandard water quality or a surge in energy consumption).

[0004] Current technologies lack a multi-dimensional, quantitative evaluation system, making it difficult to balance the relationship between water quality assurance, membrane lifespan, and operating costs, and hindering the provision of scientifically sound replacement recommendations. Therefore, there is an urgent need to develop a comprehensive, multi-factor-based method and system for evaluating the lifespan of nanofiltration membranes. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-dimensional and quantitative evaluation system to balance the relationship between water quality assurance, membrane lifespan and operating costs, and to provide scientific and reasonable recommendations for replacement nodes.

[0006] The objective of this invention is achieved through the following technical solution: In a first aspect, the present invention provides a method for evaluating the lifetime of a nanofiltration membrane for water treatment, comprising: Obtain the attribute data of the nanofiltration membrane, including the membrane performance, operating cost, and effluent water quality; preprocess the attribute data of the nanofiltration membrane to obtain standardized data of the nanofiltration membrane; The standardized data of the nanofiltration membrane are input into the nanofiltration membrane evaluation system model to obtain the comprehensive evaluation index of the nanofiltration membrane; the comprehensive evaluation index of the nanofiltration membrane is used to determine whether the nanofiltration membrane should be replaced.

[0007] In some specific embodiments of the present invention, the method further includes constructing a nanofiltration membrane evaluation system model based on a weighted method: , w i =Aw si +Bw oi , in, E As a comprehensive evaluation index, E The range of values ​​is [0, 1]. n The total number of evaluation indicators, x i ′ for the first i Standardized data for each indicator; w i For the first i The overall weight of each indicator; w si For the first i The subjective weights of each indicator are determined through an expert survey using the AHP method. w oi For the first i The objective weights of each indicator are determined by the entropy weight method based on the historical standardized data of the nanofiltration membrane, and the historical standardized data of the nanofiltration membrane corresponds to the standardized data attributes of the nanofiltration membrane. A The proportion of subjective weight, B The proportion of objective weights, A + B = 1 ,and 1 > B > A > 0 .

[0008] In some specific embodiments of the present invention, the step of preprocessing the property data of the nanofiltration membrane to obtain standardized data of the nanofiltration membrane includes: Membrane performance index data is calculated based on current and historical data of membrane performance. Operating cost index data is calculated based on current and historical data of operating costs. Effluent water quality index data is calculated based on current and historical data of effluent water quality. The membrane performance index data, operating cost index data, and effluent water quality index data are nanofiltration membrane index data. The positive data of nanofiltration membrane is obtained by positively processing both the index data of nanofiltration membrane and the corresponding historical index data of nanofiltration membrane. The normalized data of nanofiltration membranes are obtained by normalizing the positive data.

[0009] In some specific embodiments of the present invention, the calculation of membrane performance index data based on current membrane performance data and historical collected membrane performance data includes: Membrane flux attenuation rate = ( J 0 J t ) / J 0×100%, The rate of decrease in sulfate rejection rate = ( R 0 R t ) / R 0×100%, Transmembrane pressure differential growth rate = ( TMP t TMP 0) / TMP 0×100%, Based on the above formula, the membrane performance index data are obtained, including the membrane flux decline rate, the decrease rate of sulfate rejection, and the increase rate of transmembrane pressure difference. J 0 represents the initial flux of the new membrane. J t The current operating membrane flux, R 0 represents the initial rejection rate. Rt The current retention rate, TMP 0 represents the initial transmembrane pressure difference of the new membrane. TMP t The current transmembrane pressure difference represents the historical data of membrane performance, including the initial flux of the new membrane, the initial rejection rate, and the initial transmembrane pressure difference. The current operating membrane flux, the current rejection rate, and the current transmembrane pressure difference represent the current data of membrane performance.

[0010] In some specific embodiments of the present invention, the step of positively processing both the index data of the nanofiltration membrane and the corresponding historical index data of the nanofiltration membrane to obtain positively processed data of the nanofiltration membrane includes: The membrane performance index data and corresponding historical index data are used to obtain the forward value of membrane performance through the reciprocal method. Similarly, the operating cost index data and corresponding historical index data are used to obtain the forward value of operating cost through the reciprocal method. The effluent water quality index data and corresponding historical index data are the forward value of effluent water quality. For example, if the index data of the nanofiltration membrane is 0, then the minimum value ε=10 is used. 6 The positive data for nanofiltration membranes include: positive data for membrane performance, positive data for operating costs, and positive data for effluent quality. The process of normalizing the forward data of nanofiltration membranes to obtain standardized data includes: based on x'=(x + -x +min ) / (x + max -x + min ) Map all the forwarded data to the interval [0, 1], where, x + This is positive data for the indicator data. x + max The maximum value of the historical indicator data corresponding to this indicator after positive transformation. ，x + min This is the minimum value of the historical indicator data corresponding to this indicator after positive transformation.

[0011] In some specific embodiments of the present invention, determining whether to replace the nanofiltration membrane based on the comprehensive evaluation index includes: When the comprehensive evaluation index is greater than the mandatory replacement threshold, it is determined that no replacement is required; When the comprehensive evaluation index is less than or equal to the mandatory replacement threshold, it is determined that replacement is necessary; among which... The mandatory replacement threshold is preset based on the minimum requirements of drinking water quality standards and the limits of membrane performance.

[0012] In some specific embodiments of the present invention, the step of determining that no replacement is needed when the comprehensive evaluation index is greater than the mandatory replacement threshold further includes: The warning threshold is set based on the upper limit of unit water production cost and the water quality compliance margin, and the reminder threshold is set in combination with the membrane rated service life and average decay rate. The reminder threshold > the warning threshold > the forced replacement threshold. When the comprehensive evaluation index is greater than the warning threshold, it indicates that the nanofiltration membrane is operating well and has not degraded significantly. When the alert threshold is greater than or equal to the comprehensive evaluation index and greater than the warning threshold, it indicates that the membrane performance has begun to degrade, and it is recommended to continuously monitor the changes in the indicators. When the warning threshold is greater than or equal to the comprehensive evaluation index and the mandatory replacement threshold, it indicates that the membrane performance has seriously deteriorated, and it is recommended to develop a replacement plan and replace the membrane within 1-3 months.

[0013] In a second aspect, the present invention provides a system for evaluating the lifetime of nanofiltration membranes for water treatment, comprising: The module is used to build a nanofiltration membrane evaluation system model based on the weighting method. The acquisition and preprocessing module is used to acquire the property data of the nanofiltration membrane and preprocess the property data of the nanofiltration membrane to obtain the standardized data of the nanofiltration membrane. The model processing module is used to input standardized data into the nanofiltration membrane evaluation system model to obtain the comprehensive evaluation index of the nanofiltration membrane. The evaluation module is used to determine whether the nanofiltration membrane needs to be replaced based on the comprehensive evaluation index.

[0014] In some specific embodiments of the present invention, the construction module includes a collection submodule (collecting historical standardized data of multiple attribute data), a weighting submodule (determining the comprehensive weight of each attribute data), and a model module (constructing a linear weighted summation model and using it to calculate the comprehensive evaluation index).

[0015] In some specific embodiments of the present invention, the acquisition and preprocessing module includes: a data acquisition unit for multiple indicators, used to acquire current data for each indicator (membrane flux is acquired by an electromagnetic flowmeter on the permeate side, sulfate rejection rate is detected and calculated by an ion chromatograph, transmembrane pressure difference is acquired by a pressure transmitter, energy consumption is acquired by an electricity meter, reagent consumption is recorded by a metering device, cleaning frequency is statistically analyzed by an operation log, conductivity is monitored by an online conductivity meter, and TOC is detected by an online analyzer or an offline combustion oxidation method); a data storage submodule, which retrieves historical acquisition data and historical indicator data stored therein; and a calculation submodule, used to calculate the indicator data of each indicator, and then perform standardization processing to obtain standardized data of each indicator.

[0016] In some specific embodiments of the present invention, the calculation submodule further includes: a forward module and a normalization module. The forward module is used to forward process the indicator data of multiple indicators to obtain forward data; the normalization module uses the min-max normalization method to map all forward-normalized data to the interval [0, 1]; the normalization formula is: x'=(x + -x + min ) / (x + max -x + min ) ,in x + This is positive data for the indicator data. x + max This is the maximum value of the historical indicator data corresponding to this indicator after positive transformation. x + min This is the minimum value of the historical indicator data corresponding to this indicator after positive transformation.

[0017] In a third aspect, the present invention provides an electronic device including a processor and a memory, the memory storing computer-executable instructions that, when executed, cause the processor to perform the method described in any of the preceding claims.

[0018] In some specific embodiments of the present invention, the electronic device includes a processor and a memory storing computer-executable instructions. When the executable instructions are executed, the processor performs the evaluation method for the lifespan of nanofiltration membranes for water treatment as described in the first aspect of the present invention, including all steps of acquiring nanofiltration membrane attribute data, preprocessing nanofiltration membrane attribute data, constructing and calculating a nanofiltration membrane evaluation model, and determining nanofiltration membrane replacement nodes.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon one or more programs that, when executed by a processor, implement the evaluation method described in any of the preceding claims.

[0020] The technical solution provided by this invention has the following technical contributions: It constructs a multi-dimensional evaluation index system covering three core dimensions: membrane performance, cost, and water quality, avoiding the one-sidedness of judging by a single index; it adopts a comprehensive subjective and objective weighting method to determine the index weights, respecting industry experience while conforming to actual operational data characteristics; through a quantified comprehensive evaluation index and multi-level thresholds, it achieves accurate determination of replacement nodes, balancing water quality assurance, membrane resource utilization, and operating costs. The method is clear, highly operable, and applicable to drinking water nanofiltration membrane systems with different water sources and treatment scales, with a wide range of applications. It solves the problems of one-sided judgment and lack of quantitative basis in existing nanofiltration membrane replacement node assessments, achieving accurate and scientific determination of nanofiltration membrane replacement nodes. Attached Figure Description

[0021] Figure 1 A schematic diagram illustrating the principle of the method for evaluating the lifetime of nanofiltration membranes for water treatment provided in this embodiment of the invention.

[0022] Figure 2 This is a schematic diagram of the structure of a nanofiltration membrane lifetime evaluation system for water treatment provided in an embodiment of the present invention.

[0023] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of a computer-readable medium provided in an embodiment of the present invention. Detailed Implementation

[0025] The following description is intended to disclose the present invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description can be applied to other embodiments, modifications, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the invention.

[0026] Exemplary embodiments of the invention will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limiting the invention to the embodiments set forth herein. Rather, these exemplary embodiments are provided to make the invention more comprehensive and complete, and to facilitate a full communication of the inventive concept to those skilled in the art. The same reference numerals in the drawings denote the same or similar elements, components, or parts, and therefore repeated descriptions of them will be omitted.

[0027] Subject to the technical concept of this invention, the features, structures, characteristics or other details described in a particular embodiment may be combined in one or more other embodiments in a suitable manner.

[0028] In the description of specific embodiments, the features, structures, characteristics, or other details described in this invention are intended to enable those skilled in the art to fully understand the embodiments. However, it is not excluded that those skilled in the art can practice the technical solutions of this invention without one or more of the specific features, structures, characteristics, or other details.

[0029] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0030] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0031] The terms “and / or” or “and / or” include all combinations of any one or more of the listed items.

[0032] The following description is based on specific embodiments.

[0033] Example 1 like Figure 1 The method shown is for evaluating the lifespan of nanofiltration membranes used in water treatment, and is used to comprehensively assess the lifespan of nanofiltration membranes.

[0034] Step S0: Construct a nanofiltration membrane evaluation system model A municipal waterworks uses a nanofiltration membrane system for advanced drinking water treatment, which has been operating continuously for over 5 years. To scientifically assess the lifespan of the nanofiltration membrane and determine replacement points, a multi-dimensional evaluation index system was constructed, encompassing "nanofiltration membrane performance, nanofiltration membrane operating costs, and nanofiltration membrane effluent quality," covering the core influencing factors of nanofiltration membrane operation. 1) Membrane performance of nanofiltration membranes (reflecting the degree of membrane degradation) Membrane flux decay rate (core indicator): The calculation formula is as follows (J 0 J t ) / J 0 ×100% ,in J 0 represents the initial flux of the new membrane. J t This represents the current operating membrane flux; Retention rate decrease rate (key indicator): For sulfate, the calculation formula is as follows: (R 0 R t ) / R 0 ×100% ,in R 0 represents the initial rejection rate. Rt This represents the current retention rate. Transmembrane pressure difference growth rate (auxiliary indicator): The calculation formula is ( TMP t TMP 0) / TMP 0× 100% ,in TMP 0 represents the initial transmembrane pressure difference of the new membrane. TMP t This represents the current transmembrane pressure difference.

[0035] 2) Operating costs of nanofiltration membranes (reflecting economic rationality) Energy consumption per unit of water production (kWh / m³): The calculation formula is as follows W / Q ,in W The monthly electricity consumption Q Monthly water production; Unit permeate chemical consumption (L / m³): Calculation formula is as follows M / Q ,in M This refers to the total amount of various medicines consumed each month. Q Monthly water production; Membrane cleaning frequency (times / month): Number of times the membrane is chemically cleaned per month.

[0036] 3) The quality of the effluent from the nanofiltration membrane (reflecting the ability to ensure compliance with standards) Product water conductivity removal rate (%): Calculation formula is as follows(σ 0 σ t ) / σ 0× 100% ,in σ 0 represents the conductivity of the incoming water. σ t For the conductivity of the produced water; TOC removal rate of permeate (%): The calculation formula is as follows (T 0 T t ) / T 0× 100% ,in T 0 represents the TOC value of the influent. T t This refers to the TOC value of the produced water.

[0037] 4) Determination of overall weight For the above eight nanofiltration membrane indicators, a combined "subjective + objective" weighting method was adopted, taking into account both industry experience and objective data patterns: ① Subjective weight w si The AHP method was used, with 5-8 experts making judgments to determine the importance of each indicator pairwise, constructing a judgment matrix. Eight nanofiltration membrane indicators were selected as evaluation criteria for replacement nodes. Table 1. Specifications of Nanofiltration Membranes Using a 1-9 scale (1 = equally important, 9 = extremely important), the importance of the eight indicators was compared pairwise, and an AHP judgment matrix was constructed after integrating expert opinions. Table 2. AHP Judgment Matrix Based on Expert Opinions The subjective weights of each indicator were calculated after normalizing the AHP matrix and performing a consistency check; the calculation results are [0.15, 0.22, 0.08, 0.06, 0.04, 0.03, 0.25, 0.17]. ②Objective weight w oi Collect historical index data of the nanofiltration membrane system for 12 consecutive months, and then normalize the data (negative indices are represented by the reciprocal x). + After processing (=1 / x), the historical normalized data matrix of nanofiltration membranes is obtained: Table 3. Historical Standardized Data Matrix for Nanofiltration Membranes Using the entropy weight method, based on the historical standardized data of the aforementioned nanofiltration membrane obtained after preprocessing, the information entropy of each indicator is calculated. ,in ，x ij ′ represents the standardized data of the i-th indicator in the j-th month, and n is the number of months selected, which is 12 in this embodiment; then, the entropy weight formula is used... Calculate the objective weights; the results are [0.0289, 0.0925, 0.0297, 0.0484, 0.2368, 0.5577, 0.0042, 0.0017]; Based on w i =Aw si +Bw oi Comprehensive weight w i The subjective and objective weights are combined in a 4:6 ratio to ensure that the weights align with industry understanding while also reflecting the characteristics of actual operational data. The weights are then calculated based on a comprehensive weighting. i =0.4×w si +0.6×w oi w si w represents the subjective weight of the i-th indicator. oi Let be the objective weight of the i-th indicator, and the calculation result is [0.102, 0.169, 0.060, 0.055, 0.119, 0.241, 0.152, 0.103].

[0038] The total weight is 1.000, verification passed.

[0039] 5) The evaluation system model for nanofiltration membranes is constructed using a linear weighted summation method: Model formula: , in, E This is a comprehensive evaluation index (with a value range of [0, 1]). n This represents the total number of evaluation indicators (n=8 in this example). w i For the first i The combined weight of each indicator x i ′ represents the standardized data for the i-th indicator.

[0040] The closer E is to 1, the better the nanofiltration membrane is operating and it does not need to be replaced; the closer E is to 0, the worse the membrane performance, operating costs, or water quality are, and it needs to be replaced immediately.

[0041] Step S1: Obtain the property data of the nanofiltration membrane. 1) Membrane performance of nanofiltration membranes a. Collect current data Membrane flux is collected by an electromagnetic flow meter on the product water side; current membrane flux. J t =20 L / m 2•h; Sulfate rejection rate is calculated by detecting the sulfate concentration in the influent and permeate using ion chromatography. The current sulfate rejection rate is... R t The transmembrane pressure difference is 89%; the current transmembrane pressure difference is acquired through a pressure transmitter. TMP t =0.6 MPa; sampling frequency is 1 time / day.

[0042] b. Retrieve historical data ①Historical data collection: Initial membrane flux J 0=23 L / m 2 ·h; Initial sulfate rejection rate R 0 is 98%; initial transmembrane pressure difference TMP 0 = 0.4 MPa.

[0043] ②Historical indicator data: The historical minimum membrane flux decline rate was 0; the historical minimum retention rate decline rate was 0; and the historical minimum transmembrane pressure difference growth rate was 0.

[0044] 2) Operating costs of nanofiltration membranes a. Collect current data Energy consumption is collected via electricity meters, and water production is collected via water meters. The current monthly electricity consumption of the system is... W 300,000 kWh, monthly water production Q 300,000 m 3 The consumption of chemicals is recorded through the metering device of the chemical dosing system, showing the current monthly total consumption of various chemicals. M The value is 36,000,000 L; the frequency of chemical cleaning is statistically analyzed through the operation log, and the current number of membrane chemical cleanings is 1; calculated on a monthly basis.

[0045] b. Retrieve historical data ①Historical data collection: Initial water production energy consumption: 1.1 kWh / m 3 Initial permeate chemical consumption: 10 L / m³ 3 The initial membrane chemical cleaning frequency is 0.3 times / month.

[0046] ②Historical indicator data: The highest historical energy consumption for water production was 1.2 kWh / m³. 3 The lowest historical energy consumption per unit of water production is 0.9 kWh / m³. 3 ; The highest historical unit per unit of water production chemical consumption was 15 L / m³. 3 The lowest historical unit water production reagent consumption was 10 L / m³. 3 ; The highest historical frequency of membrane chemical cleaning was 2 times per month, and the lowest historical frequency was 0.3 times per month.

[0047] 3) Effluent quality of nanofiltration membrane a. Collect current data Conductivity is monitored in real time using an online conductivity meter. σ 0 represents the current influent conductivity, which is 428 μS / cm. σ t The current conductivity of the produced water is 231 μS / cm; TOC was detected using an online TOC analyzer or an offline combustion oxidation method. T 0 represents the current influent TOC level of 3.1 mg / L. T t The current TOC content of the produced water is 0.4 mg / L.

[0048] b. Retrieve historical data ①Historical data collection: Initial influent conductivity σ0 = 395 μS / cm, initial product water conductivity σ t =166μS / cm; Initial influent TOC value T 0 = 2.8 mg / L, TOC value of permeate T t =0.2mg / L.

[0049] ②Historical indicator data: The highest historical removal rate of permeate conductivity was 58%, and the lowest historical removal rate of permeate conductivity was 42%. The highest historical TOC removal rate in permeate was 92%, and the lowest historical TOC removal rate in permeate was 85%.

[0050] Step S2: Preprocess the nanofiltration membrane property data to obtain standardized nanofiltration membrane data. 1) Calculate indicator data a. Membrane performance index data Membrane flux decay rate = (J 0 J t ) / J 0 ×100% =(23 20) / 23×100%≈13.04%; Retention rate decline rate = (R 0 R t ) / R0×100% =(98%) (89%) / 98%×100%≈9.18%; Transmembrane pressure differential growth rate =(TMP t TMP 0 ) / TMP 0 ×100% =(0.48 0.4) / 0.4×100%=20%.

[0051] b. Operating cost indicators Unit water production energy consumption = W / Q =300000 / 300000=1.0 kWh / m 3 ; Unit water production reagent consumption = M / Q =36000000 / 300000=12 L / m 3 ; Membrane chemical cleaning frequency: Number of membrane chemical cleanings per month, 1.

[0052] c. Effluent water quality indicators Product water conductivity removal rate = (σ 0 σ t ) / σ 0 ×100% =46%, TOC removal rate in permeate = (T 0 T t ) / T 0 ×100% =87%.

[0053] 2) Positive data processing of indicators The data for membrane performance indicators and operating cost indicators (negative indicators, the larger the value, the more unfavorable) are converted into positive data using the reciprocal method. The data for effluent water quality indicators (positive indicators, the larger the value, the more favorable) are then the positive data. For example, if the indicator data for nanofiltration membranes is 0, then the minimum value is used. ε =10 6 Replace 0.

[0054] a. Membrane performance of nanofiltration membranes ① Positive trend in indicator data: Membrane flux decay rate: 1 / 13.04%≈1 / 0.1304≈7.67 Retention rate decrease rate: 1 / 9.18% ≈ 1 / 0.0918 ≈ 10.89; Transmembrane pressure differential growth rate: 1 / 20.00% = 5.

[0055] ② Positive transformation of historical indicator data: Maximum historical membrane flux decline rate: 1 / ε =10 6 The lowest historical membrane flux decay rate was 7.67%. The historical maximum retention rate decline rate: 1 / ε =10 6 The lowest historical membrane flux decline rate was 10.89%. The highest historical increase in transmembrane pressure differential was: 1 / ε =10 6 The lowest historical membrane flux decay rate was 5.

[0056] b. Operating costs of nanofiltration membranes ① Positive trend in indicator data: Energy consumption per unit of water production: 1 / 1 = 1; Unit water production reagent consumption: 1 / 12 ≈ 0.083; Membrane chemical cleaning frequency: 1 / 1 = 1.

[0057] ② Positive transformation of historical indicator data: Lowest historical energy consumption per unit of water production: 1 / 1.2 ≈ 0.83; Highest historical energy consumption per unit of water production: 1 / 0.9 ≈ 1.11; The lowest historical unit water production chemical consumption was 1 / 15 ≈ 0.067, and the highest historical unit water production chemical consumption was 1 / 10 = 0.1. The lowest historical frequency of membrane chemical cleaning is 1 / 2 = 0.5, and the highest historical frequency is 1 / 0.3 = 3.33.

[0058] c. Effluent quality from nanofiltration membranes ① Positive trend in indicator data: Product water conductivity removal rate: 0.46; TOC removal rate in permeate: 0.87; ② Positive transformation of historical indicator data: Lowest historical permeate conductivity removal rate: 0.42; Highest historical permeate conductivity removal rate: 0.58; Lowest historical TOC removal rate in permeate: 0.85; highest historical TOC removal rate in permeate: 0.92.

[0059] 3) Forward data normalization processing The min-max normalization method is used to map all the forward-directed data to the interval [0, 1].

[0060] The normalization formula is: x'=(x + -x+ min ) / (x + max -x + min ) ,in x + This is positive data for the indicator data. x + max This is the maximum value of the historical indicator data corresponding to this indicator after positive transformation. x + min This is the minimum value of the historical indicator data corresponding to this indicator after positive transformation.

[0061] The minimum and maximum values, determined based on the factory's historical indicator data, are shown in Table 4 below: Table 4. Normalization Process for Forward-Oriented Data Therefore, the normalized data vector xi′ is: [0, 0, 0, 0.61, 0.48, 0.17, 0.25, 0.29].

[0062] Step S3: Input the standardized data of the nanofiltration membrane into the nanofiltration membrane evaluation system model to obtain the comprehensive evaluation index of the nanofiltration membrane. The normalized and standardized data are then input into the evaluation index system model to calculate the comprehensive evaluation index E, quantifying the overall operating status of the nanofiltration membrane. Model formula: , in, E As a comprehensive evaluation index, E ranges from [0, 1]. n The total number of evaluation indicators, w i For the first i The combined weight of each indicator x i ′ for the first i Standardized data for each indicator.

[0063] In this embodiment, w i The values ​​are [0.102, 0.169, 0.060, 0.055, 0.119, 0.241, 0.152, 0.103]. x iGiven the expression [0, 0, 0, 0.61, 0.48, 0.17, 0.25, 0.29], substitute the data to calculate: E = (0.102 × 0) + (0.169 × 0) + (0.060 × 0) + (0.055 × 0.61) + (0.119 × 0.48) + (0.241 × 0.17) + (0.152 × 0.25) + (0.103 × 0.29) = 0.22 Step S4: Determine whether to replace the nanofiltration membrane based on the comprehensive evaluation index. Based on industry standards, operating cost thresholds, and water quality safety requirements, a judgment threshold is set to determine whether the nanofiltration membrane needs to be replaced. 1) Preset threshold The mandatory replacement threshold (E3) is set based on the minimum requirements of drinking water quality standards and the limits of membrane performance: E3=0.2.

[0064] Several threshold values ​​can also be set to indicate the overall operating status of the nanofiltration membrane: The warning threshold (E2) is set based on the upper limit of unit water production cost (e.g., 30% increase compared to the new membrane stage) and the margin for water quality compliance: E2=0.3; Set a warning threshold (E1) based on the membrane's rated service life and average decay rate: E1=0.5; The threshold for reminders is E1 > the threshold for warnings is E2 > the threshold for forced replacement is E3.

[0065] 2) Judgment Rules a. When E ≤ E 3: If the membrane performance is severely degraded, the operating cost is soaring, or the water quality is close to exceeding the standard, it is determined that "replacement is necessary" to avoid affecting the safety of water supply.

[0066] b. When E > E3: The nanofiltration membrane is operating normally and is determined to be "no replacement required". Then continue to compare E with the values ​​of E1 and E2: ① When the comprehensive evaluation index E > the warning threshold E1, it indicates that the nanofiltration membrane is operating well and has not significantly degraded; ② When the reminder threshold E1 ≥ comprehensive evaluation index E > warning threshold E2, it indicates that the membrane performance has begun to degrade, but there is still no need to replace it. It is recommended to continuously monitor the changes in the indicators. ③ When the warning threshold E2 ≥ comprehensive evaluation index E > mandatory replacement threshold E3, it indicates that the membrane performance has deteriorated significantly. It is recommended to develop a replacement plan based on the operating conditions, effluent water quality, or operating costs, and replace the membrane within 1-3 months.

[0067] 3) Decision to change nodes Therefore, based on the evaluation method for the lifespan of nanofiltration membranes for water treatment provided by this invention, a comprehensive evaluation is performed. If the comprehensive evaluation index E=0.22 > E3, then the nanofiltration membrane "does not need to be replaced." Furthermore, based on the comprehensive evaluation index E=0.22, which conforms to E2>E>E3, it indicates that the current nanofiltration membrane performance is significantly degraded. It is recommended to develop a replacement plan based on operating conditions, effluent water quality, or operating costs, and replace the membrane within 1-3 months. This evaluation method not only determines whether the nanofiltration membrane needs replacement but also indicates the overall operating status of the nanofiltration membrane, reflecting its performance condition and facilitating accurate identification of the replacement time.

[0068] Example 2 like Figure 2 As shown, a system for evaluating the lifetime of nanofiltration membranes for water treatment includes: The construction module 201 is used to construct a nanofiltration membrane evaluation system model based on the weighting method. The nanofiltration membrane evaluation system model is constructed based on the membrane performance of the nanofiltration membrane, the operating cost index of the nanofiltration membrane, the historical standardized data of the effluent water quality of the nanofiltration membrane, and the comprehensive weight of each of the historical standardized data. The comprehensive weight is determined by a subjective and objective comprehensive weighting method. The acquisition and preprocessing module 202 is used to acquire the property data of the nanofiltration membrane and preprocess the property data of the nanofiltration membrane to obtain the standardized data of the nanofiltration membrane. The model processing module 203 is used to input standardized data into the nanofiltration membrane evaluation system model to obtain the comprehensive evaluation index of the nanofiltration membrane. The evaluation module 204 is used to determine whether to replace the nanofiltration membrane based on the comprehensive evaluation index. The comprehensive evaluation index is compared with a preset judgment threshold to determine whether to replace the nanofiltration membrane.

[0069] Optionally, module 201 includes: multiple collection sub-modules for collecting historical standardized data on multiple indicators (such as membrane flux decay rate, rejection rate decline rate, transmembrane pressure difference growth rate, unit permeate energy consumption, unit permeate reagent consumption, membrane cleaning frequency, permeate conductivity removal rate, permeate TOC removal rate, etc.); a weighting sub-module for determining the comprehensive weight of each indicator; and a model module for constructing an evaluation system model for nanofiltration membranes and calculating a comprehensive evaluation index based on the model.

[0070] Optional, the model module constructs an evaluation system model for nanofiltration membranes: Model formula: , w i =Aw si +Bw oi , in, EThis is a comprehensive evaluation index (with a value range of [0, 1]). n The total number of evaluation indicators, x i ′ represents the standardized data for the i-th indicator. w i For the first i The overall weight of each indicator; w si The subjective weight of the i-th indicator. w oi Let be the objective weight of the i-th indicator; A The proportion of subjective weight, B The proportion of objective weights, A + B = 1 ,and 1 > B > A > 0 .

[0071] The closer E is to 1, the better the nanofiltration membrane is operating and it does not need to be replaced; the closer E is to 0, the worse the membrane performance, operating costs, or water quality are, and it needs to be replaced immediately.

[0072] Optionally, the acquisition and preprocessing module 202 includes: a collector for multiple indicators, used to collect the current data of each indicator; a data storage submodule, used to retrieve the historical collected data and historical indicator data stored therein; and a calculation submodule, used to calculate the indicator data of each indicator, and then to obtain the standardized data of each indicator through standardization processing.

[0073] Optionally, there are several data acquisition options, such as: membrane flux is collected by an electromagnetic flow meter on the permeate side; sulfate rejection rate is calculated by detecting the sulfate concentration in the feed water and permeate using an ion chromatograph; transmembrane pressure difference is collected by a pressure transmitter, with a collection frequency of once per day; energy consumption is collected by an electricity meter; reagent consumption is recorded by the metering device of the reagent dosing system; chemical cleaning frequency is statistically analyzed by the operation log and calculated monthly; conductivity is monitored in real time by an online conductivity meter; and TOC is detected by an online TOC analyzer or an offline combustion oxidation method.

[0074] Optionally, the calculation submodule also includes: a forwarding module and a normalization module. The forwarding module is used to forward process the indicator data of multiple indicators to obtain forwarded data; the normalization module uses the min-max normalization method to map all forwarded data to the interval [0, 1]; the normalization formula is: x'=(x + -x + min ) / (x + max -x + min ) ,in x+ This is positive data for the indicator data. x + max This is the maximum value of the historical indicator data corresponding to this indicator after positive transformation. x + min This is the minimum value of the historical indicator data corresponding to this indicator after positive transformation.

[0075] It should be noted that the technical essence of Embodiment 2 is the same as that of Embodiment 1. If there is anything unclear, please refer to Embodiment 1.

[0076] The functions of the apparatus in this embodiment have been described in the above method embodiments. Therefore, for any parts not detailed in this embodiment, please refer to the relevant descriptions in the foregoing embodiments, which will not be repeated here.

[0077] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0079] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0080] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0081] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for evaluating the lifetime of nanofiltration membranes for water treatment, characterized in that, include: Obtain the attribute data of the nanofiltration membrane, including: the membrane performance of the nanofiltration membrane, the operating cost of the nanofiltration membrane, and the effluent quality of the nanofiltration membrane; The property data of the nanofiltration membrane is preprocessed to obtain standardized data of the nanofiltration membrane; The standardized data of the nanofiltration membrane are input into the nanofiltration membrane evaluation system model to obtain the comprehensive evaluation index of the nanofiltration membrane. The decision to replace the nanofiltration membrane is based on its comprehensive evaluation index.

2. The evaluation method according to claim 1, characterized in that, It also includes a nanofiltration membrane evaluation system model based on the weighting method: ， w i =Aw si +Bw oi ， in, E As a comprehensive evaluation index, E The range of values ​​is [0, 1]. n The total number of evaluation indicators, x i ′ for the first i Standardized data for each indicator; w i For the first i The overall weight of each indicator; w si For the first i Subjective weighting of each indicator; w oi For the first i The objective weight of each indicator; A The proportion of subjective weight, B The proportion of objective weights, A+B=1 ,and 1 > B > A > 0 .

3. The method according to claim 1, characterized in that, The step of preprocessing the property data of the nanofiltration membrane to obtain standardized data of the nanofiltration membrane includes: Membrane performance index data is calculated based on current and historical data of membrane performance. Operating cost index data is calculated based on current and historical data of operating costs. Effluent water quality index data is calculated based on current and historical data of effluent water quality. The membrane performance index data, operating cost index data, and effluent water quality index data are nanofiltration membrane index data. The positive data of nanofiltration membrane is obtained by positively processing both the index data of nanofiltration membrane and the corresponding historical index data of nanofiltration membrane. The normalized data of nanofiltration membranes are obtained by normalizing the positive data.

4. The method according to claim 3, characterized in that, The membrane performance index data calculated based on current membrane performance data and historical collected membrane performance data includes: Membrane flux attenuation rate = ( J 0 J t ) / J 0×100%, The rate of decrease in sulfate rejection rate = ( R 0 R t ) / R 0×100%, Transmembrane pressure differential growth rate = ( TMP t TMP 0) / TMP 0×100%, in, J 0 represents the initial flux of the new membrane. J t The current operating membrane flux, R 0 represents the initial rejection rate. Rt The current retention rate, TMP 0 represents the initial transmembrane pressure difference of the new membrane. TMP t The current transmembrane pressure difference represents the historical data of membrane performance, including the initial flux of the new membrane, the initial rejection rate, and the initial transmembrane pressure difference. The current operating membrane flux, the current rejection rate, and the current transmembrane pressure difference represent the current data of membrane performance.

5. The method according to claim 3, characterized in that, The process of positively processing both the nanofiltration membrane's index data and its corresponding historical index data to obtain positively processed nanofiltration membrane data includes: The membrane performance index data and corresponding historical index data are used to obtain the forward value of membrane performance through the reciprocal method. Similarly, the operating cost index data and corresponding historical index data are used to obtain the forward value of operating cost through the reciprocal method. The effluent water quality index data and corresponding historical index data are the forward value of effluent water quality. For example, if the index data of the nanofiltration membrane is 0, then the minimum value ε=10 is used. 6 The positive data for nanofiltration membranes include: positive data for membrane performance, positive data for operating costs, and positive data for effluent quality. The process of normalizing the forward data of nanofiltration membranes to obtain standardized data includes: based on x'=(x + -x + min ) / (x + max -x + min ) Map all the forwarded data to the interval [0, 1], where, x + This is positive data for the indicator data. x + max The maximum value of the historical indicator data corresponding to this indicator after positive transformation. ，x + min This is the minimum value of the historical indicator data corresponding to this indicator after positive transformation.

6. The method according to claim 1, characterized in that, The step of determining whether to replace the nanofiltration membrane based on the comprehensive evaluation index includes: When the comprehensive evaluation index is greater than the mandatory replacement threshold, it is determined that no replacement is required; When the comprehensive evaluation index is less than or equal to the mandatory replacement threshold, it is determined that replacement is mandatory; among which... The mandatory replacement threshold is preset based on the minimum requirements of drinking water quality standards and the limits of membrane performance.

7. The method according to claim 6, characterized in that, The determination that no replacement is needed when the comprehensive evaluation index is greater than the mandatory replacement threshold also includes: The warning threshold is set based on the upper limit of unit water production cost and the water quality compliance margin, and the reminder threshold is set in combination with the membrane rated service life and average decay rate. The reminder threshold > the warning threshold > the forced replacement threshold. When the comprehensive evaluation index is greater than the warning threshold, it indicates that the nanofiltration membrane is operating well and has not degraded significantly. When the alert threshold is greater than or equal to the comprehensive evaluation index and greater than the warning threshold, it indicates that the membrane performance has begun to degrade, and it is recommended to continuously monitor the changes in the indicators. When the warning threshold is greater than or equal to the comprehensive evaluation index and the mandatory replacement threshold, it indicates that the membrane performance has seriously deteriorated, and it is recommended to develop a replacement plan and replace the membrane within 1-3 months.

8. A system for evaluating the lifetime of nanofiltration membranes for water treatment, characterized in that, include: The module is used to build a nanofiltration membrane evaluation system model based on the weighting method. The acquisition and preprocessing module is used to acquire the property data of the nanofiltration membrane and preprocess the property data of the nanofiltration membrane to obtain the standardized data of the nanofiltration membrane. The model processing module is used to input standardized data into the nanofiltration membrane evaluation system model to obtain the comprehensive evaluation index of the nanofiltration membrane. The evaluation module is used to determine whether the nanofiltration membrane needs to be replaced based on the comprehensive evaluation index.

9. An electronic device, wherein, The electronic device includes: Processor; and, A memory storing computer-executable instructions, which, when executed, cause the processor to perform the method according to any one of claims 1-7.

10. A computer-readable storage medium, wherein, The computer-readable storage medium stores one or more programs that, when executed by a processor, implement the method of any one of claims 1-7.

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