Multi-dimensional risk index linkage-based method and system for quality grading and adaptive control of urban reclaimed water used in industrial circulating water

Abstract

This invention discloses a method and system for the classification and adaptive control of urban greywater reuse in industrial circulating water based on multi-dimensional risk index linkage. The method includes: online monitoring of water quality indicators; constructing scaling risk index, corrosion risk index, and biological risk index, and integrating them into a comprehensive risk index; classifying greywater according to the comprehensive risk index to determine the destination of makeup water or pretreatment method; adjusting at least two parameters among membrane recovery rate, wastewater discharge ratio, scale inhibitor, corrosion inhibitor, bactericide dosage, and side-filter operation strategy according to changes in each risk index; and adaptively correcting the risk index weights, classification thresholds, and linkage parameters using feedback signals such as heat exchanger pressure drop, corrosion rate, and biological slime. This invention significantly reduces the comprehensive risks of scaling, corrosion, and biological pollution, improves water recovery rate, reduces chemical consumption and cleaning frequency, and ensures long-term stable operation of the system.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for industrial water treatment and circulating cooling water, specifically to a method and system for the graded and adaptive control of urban greywater reuse for industrial circulating water based on multi-dimensional risk index linkage. Background Technology

[0002] Reusing urban greywater for industrial circulating cooling water replenishment is an important way for industries such as steel, power, and petrochemicals to achieve water conservation and reduce fresh water intake. Currently, engineering projects typically adopt a route of "secondary greywater treatment effluent → (if necessary) advanced treatment → circulating water replenishment," coupled with circulating water chemical dosing and sewage control to keep the system's scaling, corrosion, and microbial risks within acceptable ranges. However, compared to surface water or tap water, urban greywater is significantly affected by factors such as the sewage source structure, rainwater-sewage switching, seasonal temperature, pipeline infiltration, and fluctuations in treatment unit load, resulting in significant fluctuations in water quality, mainly reflected in conductivity, hardness / alkalinity, dissolved silica (SiO2), and chloride ions (Cl). - The synchronous changes in indicators such as organic matter (TOC, UV254) and turbidity. Under high concentration ratio operation conditions of circulating water, the above fluctuations are easily amplified by the concentration effect, thus triggering a combined risk of scaling, corrosion and biological pollution, mainly manifested in: 1) Multi-factor coupling of scaling risk: Hardness, alkalinity, pH, temperature and SiO2 together determine the tendency of carbonate scale and silicate scale to form. When using a single LSI or only using conductivity as the control index, it is difficult to cover silica scale, mixed scale and local supersaturation induced deposition, which can easily lead to increased pressure drop of heat exchanger, decreased heat transfer coefficient and increased cleaning frequency.

[0003] 2) Corrosion risk in high Cl- concentrations - Significant scale-up at high concentration ratios: Cl in urban wastewater - and SO4 2- The concentration of Cl varies with the incoming water flow. During the process of increasing the concentration ratio to save water, the circulating system... - SO4 2- The simultaneous enrichment of corrosive ions, coupled with dissolved oxygen, pH deviation, and temperature changes, can easily lead to an increased risk of pitting corrosion, crevice corrosion, and under-deposition corrosion, manifested as increased corrosion rate, increased leakage risks, and shortened equipment life.

[0004] 3) The risks of organic matter and microorganisms are higher and more dynamic: Urban water generally contains a certain amount of biodegradable organic matter and recalcitrant organic matter. Fluctuations in TOC, UV254 and turbidity can easily trigger the growth of microorganisms and the deposition of biological slime. In circulating water systems, the demand for bactericides and the rate of residual chlorine decay are significantly affected by water quality and temperature. If a bactericide strategy with a fixed cycle or fixed dosage is still adopted, it is easy to encounter the dilemma of "insufficient bactericides leading to slime / biofilm" or "excessive dosage leading to high chemical consumption and by-product risks".

[0005] 4) Lack of interface standards and linkage mechanism for "water quality classification - operating condition classification": In engineering, reclaimed water is often uniformly incorporated into the water replenishment tank, and a fixed recovery rate or fixed discharge ratio is adopted for operation. Chemical dosing is controlled by single variables (such as conductivity, LSI or residual chlorine). When the incoming water quality changes drastically or multiple indicators deteriorate at the same time, manual adjustment is lagging and relies on experience. It is difficult to achieve timely coordination and optimization between "membrane recovery rate - discharge ratio - chemical dosage", resulting in increased chemical consumption, frequent scaling and cleaning, increased corrosion risk and high system energy consumption.

[0006] Existing technologies often focus on a single risk dimension for control (e.g., controlling only LSI to prevent scaling, only controlling conductivity to regulate wastewater discharge, or only controlling residual chlorine to inhibit bacteria), or employ empirical control methods with fixed operating parameters. A systematic approach has yet to be developed that addresses fluctuations in urban reclaimed water quality, comprehensively considers the coupling relationship between scaling, corrosion, and biological pollution risks, and accordingly achieves graded utilization of reclaimed water and adaptive linkage adjustment of operating parameters. Therefore, it is necessary to propose a graded and adaptive control method and system based on multi-dimensional risk index linkage to improve the water recovery rate of the circulating water system and reduce overall operating costs while ensuring the safe and stable operation of equipment. Summary of the Invention

[0007] This invention aims to solve the following problems existing in the process of reusing urban greywater for industrial circulating cooling water makeup: ① Fluctuations in water quality lead to multiple overlapping risks that are difficult to comprehensively assess under the same dimension: TOC and Cl in urban greywater - Indicators such as hardness / alkalinity, SiO2, and turbidity fluctuate significantly with changes in incoming water and operating conditions, and are amplified when the concentration ratio of circulating water increases. This leads to a coupled and compounded risk of scaling, corrosion, and biological contamination. Traditional single LSI or single conductivity indicators are insufficient to simultaneously cover silica / mixed scale and Cl... - Risks of corrosion and biofilm formation.

[0008] ② The control strategy is mainly based on single variables and fixed parameters, resulting in a delayed response: Most existing systems adopt a fixed discharge ratio / fixed recovery rate operation mode, and the dosing is based on single variable experience control such as conductivity or LSI. There is a lack of synergistic constraints on corrosion risk and biological risk, which leads to mutual restraint between "scale control-corrosion control-bacterial control", and the adjustment is delayed and dependent on manual intervention.

[0009] ③ Lack of differentiated and graded utilization and linkage interface: Urban wastewater is often uniformly incorporated into the water replenishment pool, lacking a graded diversion mechanism based on comprehensive risk, making it difficult to achieve differentiated and graded utilization of "direct water replenishment - deep treatment required - restricted use / bypass", resulting in high-risk water entering the system and causing operational fluctuations.

[0010] ④ Increased operational risks and costs: Scaling leads to increased pressure drop in heat exchangers and more frequent cleaning; corrosion causes increased leakage and maintenance risks; biological slime causes heat transfer deterioration and increased chemical consumption; the overall energy and chemical consumption of the system is too high, making it difficult to achieve the goals of water conservation and efficiency improvement.

[0011] To address the aforementioned technical problems, this invention proposes a method and system for the graded and adaptive control of urban greywater reuse in industrial circulating water based on multidimensional risk index linkage. By designing a method involving online monitoring, multidimensional risk index construction, graded decision-making, linked control of operating parameters, and feedback closed-loop adaptive correction, this method can achieve safe and stable operation of the industrial circulating cooling water system and improve water recovery rate even under conditions of fluctuating urban greywater quality. This invention is achieved through the following technical solution: In a first aspect, the present invention provides a method for the quality classification and adaptive control of urban greywater reuse for industrial circulating cooling water based on multi-dimensional risk index linkage, comprising the following steps: Obtain water quality indicators for urban greywater and / or circulating cooling water systems online; Based on the aforementioned water quality indicators, the scaling risk index Rs, corrosion risk index Rc, and biological risk index Rb are calculated respectively, and Rs, Rc, and Rb are normalized to the same dimension range. The comprehensive risk index Rtotal is obtained by weighting and fusing the data with adjustable weights α, β, and γ, where Rtotal = α·Rs + β·Rc + γ·Rb, and α + β + γ = 1. According to Rtotal, urban wastewater is classified into at least three categories and its destination is determined: Category 1 enters the circulating water makeup; Category 2 enters the membrane deep treatment and is used as makeup; Category 3 is subject to restricted use or bypass treatment. The operating parameters are adjusted in conjunction with the changes in Rs, Rc, and Rb. The operating parameters include at least two or more of the following: membrane treatment unit recovery rate, fouling ratio, scale inhibitor dosage, corrosion inhibitor dosage, bactericide dosage, and side-stream filtration / filtration operation strategy. Collect operational feedback signals, which include at least one or more of the following: heat exchanger pressure drop growth rate, corrosion monitoring value, and biofilm characterization index; when any feedback signal exceeds the corresponding threshold, increase the risk index weight corresponding to the feedback signal, tighten the corresponding quality classification threshold or strengthen the corresponding linkage adjustment parameter, and then perform normalization update on α, β, and γ to satisfy α+β+γ=1.

[0012] As a preferred embodiment of the present invention, the formula for calculating the scaling risk index Rs is as follows: Rs=a1×LSI+a2×C(SiO2)+a3×H+a4×f(T); Where a1-a4 are coefficients, determined by regression of historical data, online identification or segmented calibration; LSI is the Langerile saturation index; C(SiO2) is the SiO2 concentration in water; H is the hardness of water; f(T) is the temperature correction term, f(T)=(T-Tref) / Tspan, where T is the online temperature monitoring value, Tref is the reference temperature, and Tspan is the temperature span constant.

[0013] As a preferred embodiment of the present invention, the formula for calculating the corrosion risk index Rc is as follows: Rc=b1×C(Cl - )+b2×C(SO4 2- )+b3×C(DO)+b4×|pH-pHref|; Where b1-b4 are coefficients, determined based on regression of historical data from the field, online identification, or segmented calibration; C(Cl - ) is Cl in water - Concentration, C(SO4) 2- SO4 in water 2- Concentration, C(DO) is the dissolved oxygen DO concentration; pH is the online monitored acidity / alkalinity value of the urban wastewater and / or circulating cooling water system; pHref is a preset reference pH value, which is the target control pH or the center value of the allowable control range of the circulating cooling water system.

[0014] As a preferred embodiment of the present invention, the formula for calculating the biological risk index Rb is as follows: Rb=c1×TOC+c2×A+c3×TU+c4×kCl; Wherein, c1-c4 are coefficients, determined based on regression of historical data, online identification, or segmented calibration; TOC is the total carbon content of organic matter in water; A is the ultraviolet absorbance of water at a wavelength of 254 nm; TU is the turbidity of water; kCl is the residual chlorine decay rate in water, kCl=(lnC0-lnCt) / Δt, where C0 is the residual chlorine concentration at the beginning of the time window, Ct is the residual chlorine concentration at the end of the time window; and Δt is the preset time window.

[0015] As a preferred embodiment of the present invention, Rs, Rc, and Rb are respectively subjected to minimum-maximum normalization: Xn = (X - Xmin) / (Xmax - Xmin); wherein Xn is the normalized risk index value (dimensionless), used to represent the normalized scaling risk index Rs, corrosion risk index Rc or biological risk index Rb; X is the original risk index value before normalization, which is the calculation result of the scaling risk index Rs, corrosion risk index Rc or biological risk index Rb; Xmin is the minimum reference value for normalization, which is the minimum value of the original risk index value X in historical statistics or a rolling window; Xmax is the maximum reference value for normalization, which is the maximum value of the original risk index value X in historical statistics or a rolling window.

[0016] As a preferred technical solution of the present invention, the step of dividing urban reclaimed water into at least three categories according to Rtotal comprises: when Rtotal ≤ 0.4, it is the first category of water; when 0.4 < Rtotal ≤ 0.7, it is the second category of water; when Rtotal > 0.7, it is the third category of water; and the water quality classification and grading thresholds are allowed to be dynamically corrected with differences in seasons, loads or equipment materials.

[0017] As a preferred technical solution of the present invention, the coordinated regulation comprises: When the scaling risk index Rs rises, at least one of the following operations is performed: reducing the recovery rate of the membrane treatment unit, increasing the scale inhibition control intensity, and strictly constraining key indicators of circulating water; When the corrosion risk index Rc rises, at least one of the following operations is performed: increasing the blowdown ratio, increasing the dosage of corrosion inhibitor, and dynamically limiting the upper limit of the conductivity of circulating water; When the biological risk index Rb rises, at least one of the following operations is performed: enhancing sterilization agent dosing, enhancing the operation of side filtration / filtration, and dynamically adjusting the residual chlorine control target according to the residual chlorine decay rate.

[0018] In a second aspect, the present invention provides a water quality classification, grading and adaptive control system for reusing urban reclaimed water in industrial circulating cooling water based on multi-dimensional risk index coordination, comprising: An online monitoring unit, configured to acquire water quality indicators of urban reclaimed water and / or a circulating cooling water system online; A risk index calculation unit, configured to calculate the scaling risk index Rs, corrosion risk index Rc, and biological risk index Rb and perform normalization processing thereon; A fusion assessment unit, configured to calculate the comprehensive risk index Rtotal according to Rtotal=α·Rs+β·Rc+γ·Rb, where α+β+γ=1; A water quality classification and grading decision unit, configured to perform at least three levels of water quality classification and grading according to Rtotal and output a destination instruction; A coordinated control unit, configured to adjust at least two types of operating parameters according to changes in Rs, Rc, and Rb; The operation feedback acquisition unit is used to collect one or more of the following: heat exchanger pressure drop growth rate, corrosion monitoring value, and biofilm characterization index; The feedback correction unit is used to adjust α, β, γ and / or the quality and grade threshold and linkage control parameters when the running feedback signal exceeds the limit, and to perform normalization update on α, β, γ to satisfy α+β+γ=1.

[0019] As a preferred embodiment of the present invention, the online monitoring unit includes multiple online or semi-online monitoring instruments for conductivity, pH, temperature, turbidity, hardness, alkalinity, silica, chloride ions, sulfate, dissolved oxygen, total organic carbon or ultraviolet absorbance, residual chlorine and residual chlorine decay rate.

[0020] As a preferred embodiment of the present invention, the linkage control unit is communicatively connected to at least two of the following actuators: membrane depth treatment unit recovery rate adjustment mechanism, drain valve group, scale inhibitor metering pump, corrosion inhibitor metering pump, bactericide metering pump, and side filter / filtration unit start / stop and backwashing control mechanism.

[0021] Compared with the prior art, the beneficial effects of the present invention include: This invention addresses the multi-risk coupling problem of urban greywater reuse for industrial circulating cooling water makeup by establishing an integrated control system encompassing "online monitoring, multi-dimensional risk indices for scaling, corrosion, and biological contamination, graded utilization, linkage between recovery rate, wastewater discharge ratio, and chemical dosage, and adaptive correction through closed-loop operational feedback." By diverting greywater according to comprehensive risk levels, high-risk water is prevented from directly entering the system. A dynamic balance between water conservation and equipment safety is achieved through multi-object coordinated adjustment of RO recovery rate, wastewater discharge ratio, and chemical dosage. Furthermore, operationally measured indicators such as pressure drop, corrosion, and biological slime are used to inversely adjust weights and thresholds, enabling adaptive response to fluctuations in incoming water and changes in operating conditions. Compared to fixed-parameter and single-variable control methods, this invention significantly reduces the combined risks of scaling, corrosion, and biological contamination, decreases chemical consumption and cleaning / maintenance frequency, and improves the water recovery rate and long-term stable operation capability of the circulating water system. Detailed Implementation

[0022] To make the technical solution, objectives, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and do not constitute a limitation thereof. The present invention provides a method and system for online monitoring, multi-dimensional risk index construction, quality-level decision-making, operational parameter linkage control, and feedback closed-loop adaptive correction, which can achieve safe and stable operation of industrial circulating cooling water systems and improve water recovery rates under fluctuating urban reclaimed water quality conditions. The method steps are as follows: (1) Raw water and system preparation 1) Circulating water system: including water replenishment, circulation, side filtration / filtration, sewage discharge and return water circuits, equipped with sewage discharge regulating valve group and necessary bypass switching pipelines.

[0023] 2) Advanced treatment unit: including one or more combinations of UF / NF / RO, with adjustable recovery rate and online monitoring of permeate / concentrate.

[0024] 3) Online monitoring unit: Includes at least conductivity, pH, temperature, and turbidity; preferably also includes hardness / alkalinity, SiO2, and Cl. - SO4 2- Online or semi-online indicators such as dissolved oxygen (DO), total oxygen concentration (TOC) or UV254, residual chlorine and residual chlorine decay rate.

[0025] 4) Dosing unit: including scale inhibitor, corrosion inhibitor, bactericide metering and dosing device and adjustable dosing mechanism.

[0026] 5) Operational feedback acquisition unit: including at least one or more of the following: heat exchanger pressure drop or heat exchanger performance indicators, corrosion monitoring (coating / probe / electrochemical) and bio-slime characterization parameters (such as slime thickness, ATP or equivalent indicators).

[0027] (2) Construction and comprehensive assessment of multidimensional risk index 1) Construction of the scaling risk index Rs: A scaling risk model is constructed using LSI, SiO2 concentration, hardness H, and temperature correction terms. The preferred form is as follows: Rs=a1×LSI+a2×C(SiO2)+a3×H+a4×f(T); Wherein, a1-a4 are regression / calibration coefficients, used to characterize the contribution weight of each scaling risk influencing factor to the scaling risk index Rs; the coefficients can be determined after normalizing the input quantities, or the coefficients themselves can absorb dimensional differences, making Rs a dimensionless index.

[0028] Temperature T is obtained from online temperature measurement points in the system, commonly including: outlet water temperature of the greywater supply pipe / replenishment tank; temperature of the circulating water return / supply main pipe; and temperature of critical heat exchanger branches (hot end / cold end) (optional, for more precise local risks). In engineering, PT100, thermocouples, or integrated temperature transmitters are generally used to connect to PLC / DCS / SCADA.

[0029] Calculation of f(T): Convert T into a dimensionless correction. f(T)=(T-Tref) / Tspan, where Tref: reference temperature (for example, 25°C, or the annual average return water temperature can also be taken); Tspan: temperature span constant (for example, 20°C, representing the typical variation range from 25°C to 45°C). The obtained f(T) is a dimensionless quantity: T=Tref→f(T)=0 (reference risk); T>Tref→f(T)>0 (risk increase); T<Tref→f(T)<0 (risk decrease; if it is not desired to reduce the risk at low temperatures, a lower limit truncation of f(T) to 0 can be implemented in practice).

[0030] Function of the temperature correction term f(T): Under scenarios such as high summer temperatures, the hot end of the heat exchanger, and elevated return water temperature of the cooling tower, Rs can automatically increase the scaling risk under the same water quality conditions, preventing the model from only considering chemical equilibrium while ignoring kinetic and heat transfer conditions.

[0031] 2) Construction of corrosion risk index Rc: Construct the corrosion risk model using Cl - , SO4 2- , dissolved oxygen DO and pH deviation, and the preferred form is: Rc=b1×C(Cl - )+b2×C(SO4 2- )+b3×C(DO)+b4×|pH-pHref|; Wherein, b1 to b4 are regression / calibration coefficients, used to characterize the contribution weight of each corrosion risk influencing factor to the corrosion risk index Rc; the coefficients can be determined after normalizing the input quantities, or the coefficients themselves can absorb the difference in dimensions, making Rc a dimensionless index.

[0032] pH is the online monitored pH value of the urban reclaimed water and / or circulating cooling water system; pHref is a preset reference pH value, which is the target control pH of the circulating cooling water system or the central value of the allowable control interval.

[0033] 3) Construction of biological risk index Rb: Construct the biological risk model using TOC, UV254, turbidity and residual chlorine decay rate, and the preferred form is: Rb=c1×TOC+c2×A+c3×TU+c4×kCl; Wherein, c1 to c4 are regression / calibration coefficients, used to characterize the contribution weight of each biological risk influencing factor to the biological risk index Rb; the coefficients can be determined after normalizing the input quantities, or the coefficients themselves can absorb the difference in dimensions, making Rb a dimensionless index.

[0034] TOC is the total amount of carbon contained in organic matter in water; A is the ultraviolet absorbance of water at a wavelength of 254 nanometers; TU is the turbidity of water; kCl is the decay rate of residual chlorine in water, kCl=(lnC0-lnCt) / Δt, where C0 is the residual chlorine concentration at the start of the time window, Ct is the residual chlorine concentration at the end of the time window; Δt is a preset time window, preferably Δt=6h.

[0035] 4) Comprehensive risk index Rtotal: Rs, Rc and Rb are normalized and then fused according to weights: Rtotal=α×Rs+β×Rc+γ×Rb, and α+β+γ=1; Where α, β and γ are adjustable weight parameters, the initial values of which are set according to the device material, target concentration ratio and historical failure modes, and are adaptively corrected during operation.

[0036] The normalization preferably adopts min-max normalization: Xn=(X-Xmin) / (Xmax-Xmin); Where Xn is the normalized risk index value (dimensionless), used to represent the normalized scaling risk index Rs, corrosion risk index Rb or biological risk index Rb; X is the original risk index value before normalization, which is the calculation result of the scaling risk index Rs, corrosion risk index Rc or biological risk index Rb; Xmin is the minimum reference value for normalization, which is the minimum value of the original risk index value X in historical statistics or a rolling window; Xmax is the maximum reference value for normalization, which is the maximum value of the original risk index value X in historical statistics or a rolling window.

[0037] (3) Quality-based classification strategy (classified diversion and water use decision-making) Carry out at least three levels of quality-based classification on reclaimed water according to the comprehensive risk index Rtotal: Class I water: Rtotal≤0.4 → directly used as circulating water make-up water; Class II water: 0.4<Rtotal≤0.7 → used as make-up water after advanced membrane treatment; Class III water: Rtotal>0.7 → only used for low-grade applications, restricted for bypass use or temporarily suspended from use; The above thresholds can be dynamically corrected in combination with seasons, loads, equipment materials and working condition fluctuations, and are implemented in interlock with the bypass valve group and water source switching.

[0038] (4) Linked control of operating parameters (multi-objective coordinated regulation) Linked regulation is implemented on the controlled objects according to the changes of Rs, Rc and Rb, and the controlled objects at least include: RO recovery rate, blowdown ratio, scale inhibitor dosage, corrosion inhibitor dosage, bactericide dosage and side-stream filtration / filtration operation strategy; the preferred linkage logic is: 1) When Rs increases (scaling risk increases): automatically reduce RO recovery rate by 3%-8% and / or increase scale control intensity (e.g., increase scale inhibitor dosage, enhance side-filter operation), and set stricter constraints on key circulating water indicators (e.g., carbonate / silicon risk characterization).

[0039] 2) When Rc increases (corrosion risk increases): automatically increase the discharge ratio by 0.3-0.8 and / or increase the dosage of corrosion inhibitor, and adjust the Cl... - Enrichment and conductivity limits are dynamically restricted.

[0040] 3) When Rb increases (biological risk increases): activate enhanced sterilization (shock or increase the frequency / dosage) and enhance side-filter / filtration, and dynamically adjust the residual chlorine control target or supplement with non-oxidizing bactericides according to the residual chlorine decay rate.

[0041] (5) Adaptive correction and closed-loop optimization Using the heat exchanger pressure drop growth rate, measured corrosion monitoring values, and biofilm index as feedback signals, the weights of α, β, and γ, the classification threshold, and the linkage control parameters are reverse-corrected, and the optimization rules are as follows: 1) When the pressure drop growth rate exceeds the limit or the scaling trend intensifies, increase α and tighten the Class I water threshold or reduce the target recovery rate; 2) When the corrosion rate exceeds the limit or the risk of pitting corrosion increases, increase β and increase the discharge ratio / corrosion inhibitor control intensity; 3) When the biofilm index exceeds the limit or the residual chlorine decays rapidly, increase γ and increase the intensity of sterilization and side-filtration control; The α, β, and γ values ​​are normalized to satisfy α+β+γ=1, thereby achieving adaptive and stable control of fluctuations in inflow water and operating conditions.

[0042] Example 1 (Classification and linkage control of urban greywater recycling for high-load circulating cooling water systems in the steel industry) (1) System and object The circulating cooling water system of a certain steel plant has a circulation volume of approximately 3.5 × 10⁻⁶. 4 m 3 The system is configured with online monitoring (conductivity, pH, temperature, turbidity, SiO2, Cl-, TOC / UV254, residual chlorine), a UF+RO deep treatment branch (RO recovery rate adjustable), a blowdown valve group (blowdown ratio adjustable), scale inhibitor / corrosion inhibitor / bactericide metering and dosing devices, a bypass filter unit, and a heat exchanger pressure drop monitoring point.

[0043] (2) Calculation of typical inflow indicators and risk index The typical range of urban greywater raw water at different water inflow periods is shown in Table 1 below.

[0044] Table 1 A normalized exponential model was used for calculation, with initial weights set to α=0.45, β=0.35, and γ=0.20 (considering that the main risks of this system are scaling and corrosion). During a period of high salt, high silica, and high hardness fluctuations, the calculation results were as follows: Rs=0.78, Rc=0.66, Rb=0.32; Rtotal=0.45×0.78+0.35×0.66+0.20×0.32=0.63.

[0045] (3) Classification and grading and destination decision-making Based on Rtotal=0.63, this batch of raw water was classified as Class II water. The system automatically executed the following: after entering the UF+RO deep treatment branch, it was used as circulating water makeup water; and the RO recovery rate, sewage discharge ratio and chemical dosage were adjusted in conjunction.

[0046] (4) Linkage control action (typical single adjustment process) When an increase in Rs and a simultaneous increase in Rc are detected, the control strategy is executed as follows: 1) The RO recovery rate has been reduced from 75% to 70% (a decrease of 5%). 2) The sewage discharge ratio was increased from 3.1 to 4.2 (an increase of 1.1, to be completed in two steps, with each step not exceeding 0.6). 3) The dosage of scale inhibitor was adjusted from 5.4 mg / L to 4.6-5.0 mg / L (adjusted according to the risk window after the recovery rate decreases to avoid excessive dosage); 4) The corrosion inhibitor dosage was adjusted from 3.2 mg / L to 4.0 mg / L, and the upper limit of the circulating water conductivity was set to a dynamic upper limit (depending on Cl). - (Trend linkage downward adjustment) 5) The side-filter unit is switched from intermittent operation to continuous operation for 48 hours to reduce suspended solids and sediment-induced particles.

[0047] (5) Operational results (statistics after 6 months of continuous operation) Compared with the control operation with a fixed recovery rate of 75% + fixed discharge ratio of 3.0 + empirical dosing, which did not apply the present invention, the results are shown in Table 2 below.

[0048] Table 2 (6) Feedback closed-loop correction In the second month of operation, it was found that the pressure drop rate of a certain heat exchanger branch was increasing faster than the system average. The system adjusted the fouling weight α from 0.45 to 0.50 and lowered the upper limit of the Class II threshold from 0.70 to 0.68. Simultaneously, the SiO2 term coefficient a2 was fine-tuned online to make Rs more sensitive to high silicon fluctuations. After the correction, the pressure drop rate decreased to below 0.5% per week.

[0049] Example 2 (Biohazard Priority Linkage Control of Urban Reclaimed Water Reuse in Coking Industry Circulating Water System) (1) System and object The circulating cooling water system in the coking industry uses a mixture of municipal deep-treatment effluent and some secondary effluent for makeup water, posing a significant microbial risk during the high-temperature summer months. The system is equipped with online monitoring (conductivity, pH, temperature, turbidity, TOC, UV254, residual chlorine, residual chlorine decay rate (kCl), Cl-). - The system includes a side-stream filter unit, a dosing unit (with switchable oxidizing / non-oxidizing bactericides), a drain valve assembly, and online corrosion monitoring points.

[0050] (2) Calculation of typical inflow indicators and risk index During a certain period of summer, there were two consecutive weeks of fluctuations in "TOC / UV254 increase + residual chlorine decay accelerated", and the typical indicators are shown in Table 3 below.

[0051] Table 3 Considering that the primary issue in this system is biological pollution, the initial weights are set as α=0.25, β=0.25, and γ=0.50. The index calculation results for a certain period of high organic matter concentration are as follows: Rs=0.35Rc=0.42Rb=0.82; Rtotal=0.25×0.35+0.25×0.42+0.50×0.82=0.60.

[0052] (3) Classification and grading and destination decision-making Rtotal=0.60 indicates Class II water: it will be used as makeup water after deep treatment / enhanced filtration; at the same time, biological risk linkage control will be prioritized.

[0053] (4) Linkage control action (typical single adjustment process) If Rb remains above 0.75 for more than 6 hours, the system will execute: 1) Sterilization control: Activate the combined strategy of "oxidative shock + non-oxidative maintenance" - oxidative bactericide shock for 2 hours, then switch to non-oxidative bactericide maintenance. 2) Dynamic upward adjustment of residual chlorine target: The residual chlorine control target for circulating water is increased from 0.3-0.5 mg / L to 0.6-0.8 mg / L, and the dosing frequency is adjusted in real time according to kCl. 3) Enhanced side-stream filtration: The side-stream filtration is switched from intermittent operation to continuous operation for 72 hours, while the backwashing frequency is increased; 4) Fine-tuning of the discharge ratio: In order to reduce the accumulation of organic matter and nutrients, the discharge ratio will be increased from 3.5 to 3.9 (an increase of 0.4), and will be restored to 3.6-3.7 after Rb falls back; 5) Corrosion inhibitor linkage protection: During the shock sterilization period, the dosage of corrosion inhibitor is increased by 10% as a short-term protection to avoid the risk of corrosion caused by oxidants.

[0054] (5) Operational results (statistics for 3 consecutive months) Compared with the existing "fixed-cycle sterilization + fixed sewage discharge rate" in the park, the results are shown in Table 4 below.

[0055] Table 4 (6) Feedback closed-loop correction During operation, it was found that the increase in kCl was more significant during the high-temperature weekend period. The system increased the biological weight γ from 0.50 to 0.55 and decreased the Rb trigger threshold from 0.75 to 0.72. At the same time, the coefficient c4 of the residual chlorine decay term was identified online, making Rb more sensitive to "accelerated residual chlorine decay" and realizing early intervention.

[0056] In summary, this invention constructs a multidimensional coupled model of scaling risk index, corrosion risk index, and biological risk index to implement an adaptive control method and system that links differentiated water supply with membrane recovery rate, wastewater discharge ratio, and chemical dosage. This method is applicable to industries such as steel, power, and petrochemicals where water quality fluctuates (TOC, Cl-, etc.). - Under conditions of hardness, alkalinity, SiO2, etc., the system can achieve safe and stable operation of the circulating water system, improve water recovery rate, and reduce the risk of scaling, corrosion and biological pollution.

[0057] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for the graded and adaptive control of urban greywater reuse in industrial circulating water based on multidimensional risk index linkage, characterized in that, Includes the following steps: Obtain water quality indicators for urban greywater and / or circulating cooling water systems online; Based on the aforementioned water quality indicators, the scaling risk index Rs, corrosion risk index Rc, and biological risk index Rb are calculated respectively, and Rs, Rc, and Rb are normalized to the same dimension range. The comprehensive risk index Rtotal is obtained by weighting and fusing the data with adjustable weights α, β, and γ, where Rtotal = α·Rs + β·Rc + γ·Rb, and α + β + γ = 1. According to Rtotal, urban wastewater is classified into at least three categories and its destination is determined: the first category enters the circulating water makeup; the second category enters the membrane deep treatment process and is used as makeup. The third category requires restricted use or bypass processing; The operating parameters are adjusted in conjunction with the changes in Rs, Rc, and Rb. The operating parameters include at least two or more of the following: membrane treatment unit recovery rate, fouling ratio, scale inhibitor dosage, corrosion inhibitor dosage, bactericide dosage, and side-stream filtration / filtration operation strategy. Collect operational feedback signals, which include at least one or more of the following: heat exchanger pressure drop growth rate, corrosion monitoring value, and biofilm characterization index; when any feedback signal exceeds the corresponding threshold, increase the risk index weight corresponding to the feedback signal and decrease the classification threshold of at least one type of water or strengthen the corresponding linkage regulation parameter, and then perform normalization update on α, β, and γ to satisfy α+β+γ=1.

2. The method according to claim 1, characterized in that, The formula for calculating the scaling risk index Rs is as follows: Rs=a1×LSI+a2×C(SiO2)+a3×H+a4×f(T); Where a1-a4 are coefficients, determined by regression of historical data, online identification or segmented calibration; LSI is the Langerile saturation index; C(SiO2) is the SiO2 concentration in water; H is the hardness of water; f(T) is the temperature correction term, f(T)=(T-Tref) / Tspan, where T is the online temperature monitoring value, Tref is the reference temperature, and Tspan is the temperature span constant.

3. The method according to claim 1, characterized in that, The formula for calculating the corrosion risk index Rc is as follows: Rc= b1 x C(Cl) + b2 x C(SO4) + b3 x C(DO) + b4 x |pH - pHref|; - 2- + b3 x C(DO) + b4 x |pH - pHref|;​ Where b1-b4 are coefficients, determined based on regression of historical data from the field, online identification, or segmented calibration; C(Cl - ) is Cl in water - Concentration, C(SO4) 2- SO4 in water 2- Concentration, C(DO) is the dissolved oxygen DO concentration; pH is the online monitored acidity / alkalinity value of the urban wastewater and / or circulating cooling water system; pHref is a preset reference pH value, which is the target control pH or the center value of the allowable control range of the circulating cooling water system.

4. The method according to claim 1, characterized in that, The formula for calculating the biological risk index Rb is as follows: Rb=c1×TOC+c2×A+c3×TU+c4×kCl; Wherein, c1-c4 are coefficients, determined based on regression of historical data, online identification, or segmented calibration; TOC is the total carbon content of organic matter in water; A is the ultraviolet absorbance of water at a wavelength of 254 nm; TU is the turbidity of water; kCl is the residual chlorine decay rate in water, kCl=(lnC0-lnCt) / Δt, where C0 is the residual chlorine concentration at the beginning of the time window, Ct is the residual chlorine concentration at the end of the time window; and Δt is the preset time window.

5. The method according to claim 1, characterized in that, Minimum-maximum normalization is applied to Rs, Rc, and Rb respectively: Xn = (X - Xmin) / (Xmax - Xmin); where Xn is the normalized risk index value (dimensionless), which is used to represent the normalized scaling risk index Rs, corrosion risk index Rc or biological risk index Rb; X is the original risk index value before normalization, which is the calculation result of the scaling risk index Rs, corrosion risk index Rc or biological risk index Rb; Xmin is the minimum reference value for normalization, which is the minimum value of the original risk index value X in historical statistics or a rolling window; Xmax is the maximum reference value for normalization, which is the maximum value of the original risk index value X in historical statistics or a rolling window.

6. The method according to claim 1, characterized in that, The step of dividing urban reclaimed water into at least three categories according to Rtotal includes: when Rtotal≤0.4, the water is classified as the first category; when 0.4<Rtotal≤0.7, the water is classified as the second category; when Rtotal>0.7, the water is classified as the third category; and the quality classification thresholds are allowed to be dynamically corrected according to differences in seasons, loads or equipment materials.

7. The method according to claim 1, characterized in that, The coordinated adjustment includes: when the scaling risk index Rs rises, performing at least one operation of reducing the recovery rate of the membrane treatment unit, increasing the scale inhibition control intensity, and strictly restricting the key indicators of circulating water; when the corrosion risk index Rc rises, performing at least one operation of increasing the blowdown ratio, increasing the dosage of corrosion inhibitor, and dynamically limiting the upper limit of the conductivity of circulating water; when the biological risk index Rb rises, performing at least one operation of enhancing sterilization dosing, strengthening the operation of side filtration / filtration, and dynamically adjusting the residual chlorine control target according to the residual chlorine attenuation rate.

8. A quality-classification and adaptive control system for urban greywater reuse in industrial circulating water based on multi-dimensional risk index linkage, characterized in that, The system includes: an online monitoring unit, configured to acquire water quality indicators of urban reclaimed water and / or a circulating cooling water system online; a risk index calculation unit, configured to calculate the scaling risk index Rs, corrosion risk index Rc, and biological risk index Rb and perform normalization processing thereon; a fusion assessment unit, configured to calculate the comprehensive risk index Rtotal according to Rtotal=α·Rs+β·Rc+γ·Rb, where α+β+γ=1; a quality classification decision unit, configured to perform at least three levels of quality classification according to Rtotal and output a destination instruction; a coordinated control unit, configured to adjust at least two types of operating parameters according to changes in Rs, Rc and Rb; an operation feedback acquisition unit, configured to acquire one or more of the pressure drop growth rate of the heat exchanger, the corrosion monitoring value, and the biofilm characterization indicator; a feedback correction unit, configured to adjust α, β, γ and / or the quality classification thresholds and coordinated control parameters when the operation feedback signal exceeds a limit, and perform normalization update on α, β, γ to satisfy α+β+γ=1.

9. The system according to claim 8, characterized in that, The online monitoring unit comprises a plurality of online or semi-online monitoring meters for conductivity, pH, temperature, turbidity, hardness, alkalinity, silica, chloride ions, sulfate radicals, dissolved oxygen, total organic carbon or ultraviolet absorbance, residual chlorine and residual chlorine attenuation rate.

10. The system according to claim 8, characterized in that: The coordinated control unit is communicatively connected to at least two of the following actuators: a recovery rate adjusting mechanism of the membrane advanced treatment unit, a blowdown valve group, a scale inhibitor metering pump, a corrosion inhibitor metering pump, a bactericide metering pump, and a start-stop and backwashing control mechanism of the side filtration / filtration unit.

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