Integrated system for ultra-pure water treatment and wastewater dynamic recycling for new energy

Abstract

The present application relates to the technical field of ultrapure water treatment, and particularly relates to an integrated system for ultrapure water treatment and wastewater dynamic recycling for new energy, comprising: a sensing network module that collects current response signals to determine dynamic purification impedance spectrum characteristic values of each processing unit; an impedance signal processing module that compensates and eliminates abnormal data to obtain standard impedance spectrum time series data; a wastewater diagnosis module that performs frequency band decomposition on the time series data, extracts impedance characteristics of each frequency band to determine pollution characteristic types and pollution levels; a self-adaptive execution module that matches physical execution mechanisms according to the pollution characteristic types, determines self-cleaning action execution intensity according to the pollution levels and generates self-cleaning execution instructions, adjusts recycling flow according to the pollution levels, and verifies the self-cleaning effect. The present application realizes accurate pollution diagnosis, differentiated self-cleaning, dynamic flow adjustment and effect verification.

Description

Technical Field

[0001] This invention relates to the field of ultrapure water treatment technology, and in particular to an integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications. Background Technology

[0002] In the new energy industry, the production processes of photovoltaics and lithium batteries have extremely high requirements for ultrapure water, while also generating large amounts of complex wastewater containing fluoride and salt. To achieve water resource recycling, wastewater reuse systems have become standard facilities in new energy manufacturing bases. These systems typically include multiple stages such as pretreatment, membrane filtration, and advanced treatment. Each unit gradually fails due to the accumulation of pollutants during operation and requires regular cleaning and maintenance.

[0003] Existing wastewater reuse systems often employ timed control methods for cleaning and maintenance. This involves initiating backwashing procedures at fixed intervals or relying solely on differential pressure signals to determine the degree of contamination before executing a uniform cleaning process. The limitations of this approach are: it cannot differentiate between contaminant types, leading to inefficient or excessive cleaning due to the use of the same cleaning method for different types of pollutants; it cannot pinpoint the exact location of contamination, often resulting in the entire system being cleaned, leading to resource waste; and the cleaning effect cannot be verified, as the system is assumed to be restored after cleaning, even though residual contaminants may still exist. Furthermore, existing systems often operate at a fixed flow rate for reuse, failing to proactively reduce the flow rate to protect equipment when contamination worsens, leading to accelerated aging of membrane modules or fluctuations in effluent quality. Summary of the Invention

[0004] To address these issues, the present invention provides an integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications. This system overcomes the problems of existing technologies that fail to employ impedance spectroscopy sensing networks for dynamic pollution monitoring of water treatment units, fail to accurately determine pollution types and quantify pollution levels, rely solely on timed or differential pressure signals to perform uniform cleaning actions without verifying cleaning effectiveness, and do not adjust reuse flow rates in conjunction with pollution status. Consequently, the new energy ultrapure water treatment system suffers from low cleaning efficiency, easy equipment aging, and fluctuating effluent quality.

[0005] To achieve the above objectives, the present invention provides an integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications, comprising: A sensor network module is used to collect the current response signal applied to each processing unit in order to determine the dynamic purification impedance spectrum characteristic value of each processing unit. The processing unit includes a pretreatment stage reaction vessel, a filtration stage membrane module, and a deep treatment stage adsorption unit. The impedance signal processing module is used to compensate the characteristic values ​​of each of the dynamic purification impedance spectra, and to identify and remove abnormal data to obtain standard impedance spectrum time series data. The wastewater diagnostic module is used to perform frequency band decomposition and analysis on the standard impedance spectrum time series data, extract the impedance characteristics of each frequency band to combine and determine the pollution characteristic type, and calculate the pollution degree parameter based on the amplitude change of the impedance characteristics to determine the pollution level. An adaptive execution module is used to determine the processing unit that needs to initiate a self-cleaning action, determine the execution intensity of the self-cleaning action according to the contamination level, generate a self-cleaning execution command to drive the physical execution mechanism of the corresponding processing unit to perform differentiated self-cleaning actions, and determine the current maximum allowable reuse rate and the reuse flow rate that needs to be adjusted according to the contamination level, and generate a reuse flow rate adjustment command. Furthermore, after the action is executed, the current response signal is re-acquired to redetermine the characteristic value of the dynamic purification impedance spectrum, confirm whether the self-cleaning effect meets the standard, and if the self-cleaning effect does not meet the standard, the parameters are adjusted again according to the current degree of contamination until the system returns to a stable operating state. If the self-cleaning effect meets the standard, the rated reuse flow rate of each treatment unit is restored.

[0006] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy applications, the sensor network module includes: A plurality of impedance sensors are provided, each of which is fixedly disposed at the inlet and outlet of the corresponding processing unit. Each impedance sensor includes at least two electrode bodies made of inert conductive material. A sweep frequency signal generator is electrically connected to each of the impedance sensors to output a multi-frequency AC voltage excitation with a gradient frequency to each of the impedance sensors. A current acquisition unit is electrically connected to each of the impedance sensors to acquire the current response signal flowing through the electrode body under the multi-frequency AC voltage excitation, and convert the current response signal into digital raw impedance data. The eigenvalue calculation unit is used to calculate the dynamic purification impedance spectrum eigenvalues ​​of each processing unit based on the original impedance data.

[0007] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the impedance signal processing module filters the characteristic values ​​of the dynamic purification impedance spectrum and performs temperature compensation on the filtered characteristic values ​​to generate initial impedance spectrum time series data. Furthermore, the initial impedance spectrum time series data corresponding to the impedance sensors at the inlet and outlet of each upstream and downstream associated processing unit are cross-validated for consistency. Abnormal data are identified and removed based on the correlation between upstream and downstream data to obtain the standard impedance spectrum time series data.

[0008] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the wastewater diagnostic module performs multi-band decomposition on the standard impedance spectrum time series data, separates high-frequency, mid-frequency and low-frequency impedance time series data, and extracts the amplitude and phase characteristics of the impedance time series data of each frequency band respectively. Among them, when the amplitude characteristic of the high-frequency band increases abnormally and the phase characteristic offset is less than the preset particulate matter impact threshold, while the characteristics of other frequency bands are normal, the pollution characteristic type is determined to be particulate matter accumulation pollution. When the amplitude characteristic of the mid-frequency band increases abnormally and the phase characteristic shift exceeds the preset organic matter adsorption threshold, while the characteristics of other frequency bands are normal, it is determined that the pollution characteristic type is organic matter adsorption pollution. When the amplitude characteristic of the low frequency band continues to increase and the phase characteristic offset exceeds the preset scaling characteristic threshold, while the characteristics of other frequency bands are normal, it is determined that the pollution characteristic type is inorganic salt scaling pollution. When the number of abnormal frequency bands is not unique, it is determined that there is a corresponding combination of pollution.

[0009] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the wastewater diagnostic module calculates the change in amplitude characteristics of each frequency band and the corresponding cleanliness baseline of each treatment unit based on the high-frequency band amplitude characteristics, mid-frequency band amplitude characteristics and low-frequency band amplitude characteristics of each treatment unit. The pollution level parameter is obtained by normalizing the amplitude characteristic changes in the high-frequency band, the mid-frequency band, and the low-frequency band, and then combining them for calculation.

[0010] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the wastewater diagnostic module determines the corresponding pollution level based on the pollution degree parameter. Wherein, in response to the pollution level parameter being lower than the low pollution threshold, it is determined to be a low pollution level; If the pollution level parameter is between the low pollution threshold and the high pollution threshold, it is determined to be a medium pollution level. If the pollution level parameter is higher than the high pollution threshold, it is determined to be a high pollution level.

[0011] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the adaptive execution module determines the treatment unit that needs to initiate self-cleaning action based on the pollution characteristic type, determines the physical execution mechanism of the self-cleaning action based on the pollution characteristic type, and determines the execution intensity of the self-cleaning action based on the pollution level and the number of pollution characteristic types. The self-cleaning execution instruction generated by the adaptive execution module includes a processing unit, a physical execution mechanism for the self-cleaning action, and the execution intensity.

[0012] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the adaptive execution module determines the maximum allowable reuse rate based on the pollution level and the preset reuse rate, obtains the actual reuse flow of each treatment unit, calculates the difference between the actual reuse flow and the maximum allowable reuse rate, determines the reuse flow to be adjusted, and generates the reuse flow adjustment command to adjust the reuse flow.

[0013] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the adaptive execution module receives the redefined dynamic purification impedance spectrum characteristic values ​​of each treatment unit after the self-cleaning action is executed and the reuse flow rate is adjusted. The redefined dynamic purification impedance spectrum characteristic values ​​are compared with the preset stable operating threshold range to confirm whether the self-cleaning effect meets the standard. In response to the dynamic purification impedance spectrum characteristic values ​​of each processing unit recovering to the preset stable operating threshold range, the self-cleaning effect is determined to be up to standard, and a recovery command is generated to restore the rated reuse flow of each processing unit. If the dynamic purification impedance spectrum characteristic value of any processing unit fails to recover to the preset stable operating threshold range, the self-cleaning effect is determined to be substandard. The preset stable operation threshold range is the amplitude and phase characteristics corresponding to the non-pollution characteristic type.

[0014] As a preferred technical solution for an integrated system of ultrapure water treatment and dynamic wastewater reuse for new energy, the adaptive execution module responds to the judgment result that the self-cleaning effect does not meet the standard, and redetermines the adjusted self-cleaning action execution intensity and reuse flow rate adjustment range based on the difference between the current pollution level parameter and the low pollution threshold.

[0015] Compared with existing technologies, the beneficial effects of this invention are as follows: By continuously changing the frequency gradient of the excitation signal, this invention achieves synchronous, dynamic, and comprehensive pollution monitoring of the surface of the treatment unit, the interior of the membrane pores, and the deep layers of the substrate. Through a non-parallel unified impedance spectrum acquisition and analysis process, a single gradient detection completes the simultaneous identification and combined judgment of three types of pollution. Based on the detection results, the pollution type, level, and location of each treatment unit can be accurately identified. A dedicated physical actuator can be matched to the pollution unit, and the self-cleaning execution intensity can be determined by combining the pollution level, type, and quantity. At the same time, the reuse flow rate can be dynamically adjusted to achieve differentiated self-cleaning and precise flow control. Furthermore, a closed loop for verifying the effect of self-cleaning and flow adjustment is constructed. When the standard is not met, the self-cleaning intensity and flow rate amplitude can be precisely adjusted according to the difference between the pollution degree parameter and the low pollution threshold. This effectively solves the problems of low efficiency of timed uniform cleaning and equipment aging and water quality fluctuation caused by fixed flow rate in traditional systems. It significantly reduces energy and reagent consumption, ensures the quality of ultrapure water output, delays equipment aging, and improves the water resource recycling rate. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy in an embodiment of the present invention; Figure 2 This is a logic diagram for determining the corresponding pollution level based on pollution degree parameters in an embodiment of the present invention; Figure 3 This is a logic diagram for confirming whether the self-cleaning effect meets the standard in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0018] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0019] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate the direction or positional relationship, are based on the direction or positional relationship shown in the drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0020] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0021] Please see Figures 1-3 As shown, the present invention provides an integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications, comprising: a sensor network module, an impedance signal processing module, a wastewater diagnostic module, and an adaptive execution module.

[0022] In implementation, based on the functional attributes of each processing unit and the types of pollution that are likely to be generated, different processing units are specially equipped with matching physical actuators. The pretreatment stage reaction tank is equipped with a rotary spray mechanism, a mechanical scraper mechanism, and a chemical cleaning spray mechanism. The rotary spray mechanism, for example, consists of a motor-driven rotary spray ball that rotates at a set speed and sprays cleaning water onto the tank wall after receiving a command. The mechanical scraper mechanism, for example, consists of a motor-driven polytetrafluoroethylene scraper that rotates along the tank wall to scrape off the scale layer after receiving a command. The chemical cleaning spray mechanism, for example, consists of a metering pump and spray pipes that add chemical cleaning solution into the tank at a set flow rate after receiving a command.

[0023] The filtration membrane module is equipped with an air-water backwashing mechanism, a vibration desorption mechanism, and a chemically enhanced backwashing mechanism. The air-water backwashing mechanism, for example, consists of an air compressor and a backwash pump, which, upon receiving a command, reversely delivers compressed air and cleaning water to the inside of the membrane module at a set air and water pressure. The vibration desorption mechanism, for example, consists of an ultrasonic transducer, which, upon receiving a command, vibrates at a set frequency to induce micro-vibrations in the membrane module. The chemically enhanced backwashing mechanism, for example, consists of a metering pump, which, upon receiving a command, adds sodium hypochlorite or sodium hydroxide cleaning agent to the backwash water at a set flow rate.

[0024] The deep treatment adsorption unit is equipped with a backwashing mechanism, such as a backwash pump, which, upon receiving a command, reverse-flows cleaning water into the activated carbon filter at a set flow rate.

[0025] Specifically, the sensor network module includes: several impedance sensors, each comprising at least two electrodes made of inert conductive material; a sweep frequency signal generator that outputs a multi-frequency AC voltage excitation with a gradient frequency to each impedance sensor; a current acquisition unit that converts the current response signal into digitized raw impedance data; and a feature value calculation unit that calculates the dynamic purified impedance spectrum feature values ​​of each processing unit based on the raw impedance data.

[0026] In practice, inert conductive materials such as titanium, platinum, or graphite can be selected to ensure that the electrodes have good chemical stability and corrosion resistance when in long-term contact with complex wastewater bodies, thus avoiding measurement errors or water pollution caused by the electrode's own reaction.

[0027] The frequency sweep signal generator outputs multi-frequency AC voltage excitation with gradient frequency changes sequentially to the electrode body from low frequency to high frequency. The low frequency band is set to 1mHz to 100mHz, the mid frequency band to 100mHz to 10kHz, and the high frequency band to 10kHz to 1MHz. The duration of a single full-band frequency sweep is 10s, completing the acquisition of voltage excitation and current response signals across the low, mid, and high frequency bands, meeting the basic requirements for accurate calculation of impedance spectrum characteristic values. When the system is clean and there are no warnings, it performs a routine scan every 5 minutes. When any treatment unit triggers a pollution warning, it automatically switches to a high-frequency scan every 1 minute, providing core data support for dynamic pollution monitoring and self-cleaning control of new energy ultrapure water treatment.

[0028] It is understandable that the sensitivity of current signals to pollutants varies at different frequencies. The higher the signal frequency, the shallower the penetration depth, and it can only act on the surface area of ​​the structure being tested; the lower the signal frequency, the deeper the penetration depth, and it can penetrate into the internal area of ​​the structure being tested. High-frequency signals have weak penetration capabilities, only acting on the outer surface of the filter element and membrane module. Particulate matter accumulation mainly occurs in this surface area, and the adhesion of surface pollutants directly alters the surface impedance characteristics. Therefore, high-frequency signals show a significant response to particulate matter accumulation on the filter element surface. Mid-frequency signals have moderate penetration depth, penetrating into the pores of the membrane module. Organic matter adsorption mainly occurs on the inner wall of the membrane pores, directly affecting the internal impedance changes. Therefore, mid-frequency signals are more sensitive to organic matter adsorption within the membrane pores. Low-frequency signals have the deepest penetration depth, penetrating the surface structure to reach the interface between the water body and the membrane substrate and packing material. Inorganic salt scaling mainly forms in this deep region. Only low-frequency signals can sense impedance changes in this region to reflect the inorganic salt scaling state. Different frequency signals, due to differences in penetration depth, detect the pollution state at different locations, laying a technical foundation for subsequent differentiation and determination of pollution types.

[0029] The current acquisition unit synchronously acquires the current response signal flowing through the electrode and converts the analog current signal into digital raw impedance data. Specifically, for each applied excitation frequency, the ratio of the voltage amplitude to the current amplitude is calculated to obtain the impedance amplitude, and the phase difference between the voltage and the current is calculated to obtain the impedance phase angle, thus forming a set of raw impedance data containing amplitude and phase information.

[0030] The eigenvalue calculation unit performs preliminary calculations on the original impedance data based on the equivalent circuit model fitting method. A model of a parallel resistor-capacitor circuit with series resistance is adopted, where each circuit element corresponds to a different physical meaning: solution resistance characterizes the conductivity of the water, membrane surface capacitance characterizes the degree of fouling layer coverage, and charge transfer resistance characterizes the membrane pore blockage. The original impedance spectrum data is curve-fitted using the nonlinear least squares method. Iterative optimization minimizes the error between the calculated and measured values, thereby solving for the parameter values ​​of each circuit element. The maximum-minimum normalization method is used to eliminate dimensional and numerical range differences, mapping the normalized parameter values ​​to the [0,1] interval. A 3D feature matrix is ​​constructed from the three normalized parameters. Principal component analysis (PCA) is used to reduce the dimensionality of the feature matrix, extracting the first principal component with a cumulative variance contribution rate ≥90% as the dynamic purification impedance spectrum eigenvalue. This eigenvalue simultaneously contains amplitude and phase information.

[0031] Specifically, the impedance signal processing module filters the received dynamic purification impedance spectrum feature values. The filtering can be done using a moving average filtering method. Specifically, the sliding window size is set to 5 data points, that is, the average value is calculated by taking 5 consecutive dynamic purification impedance spectrum feature values ​​in sequence. This average value is used to replace the intermediate data points in the original sequence, thereby eliminating high-frequency random noise in the measurement process and making the feature value sequence show a stable trend, avoiding misjudgment of subsequent diagnosis due to instantaneous fluctuations.

[0032] Temperature compensation corrects the filtered dynamic purification impedance spectrum characteristic values ​​based on a pre-calibrated temperature-impedance relationship curve. The calibration method for the temperature-impedance relationship curve is as follows: During the initial system debugging phase, clean water is selected as the test object, and the water temperature is controlled within the range of 5℃ to 40℃. The dynamic purification impedance spectrum characteristic values ​​of the clean water are collected every 5℃. The collected temperature data and the corresponding impedance characteristic values ​​are subjected to regression analysis to obtain the temperature-impedance relationship curve. During implementation, the water temperature is collected in real time, and the filtered dynamic purification impedance spectrum characteristic values ​​are corrected according to the curve to eliminate the interference caused by temperature fluctuations and generate the initial impedance spectrum time series data.

[0033] During the implementation of cross-validation, the initial impedance spectrum time series data of each processing unit's inlet and outlet collected during normal system operation are used to determine the correlation threshold of upstream and downstream data through a limited number of tests. Generally, the threshold for the difference in the variation amplitude of the initial impedance spectrum time series data of the same processing unit's inlet and outlet is preset to 10%, and the threshold for the difference in the response time between the inlet and outlet data is preset to 30s. During cross-validation, if the difference in the variation amplitude of the initial impedance spectrum time series data of a certain processing unit's inlet or outlet with the corresponding upstream and downstream data exceeds 10%, or the response time difference exceeds 30s, the data is determined to be abnormal data and is removed. The remaining data is integrated to form standard impedance spectrum time series data for use by the wastewater diagnostic module.

[0034] Specifically, when the wastewater diagnostic module responds to an abnormal increase in the amplitude characteristics of the high-frequency band and the phase characteristic offset is less than the preset particulate matter influence threshold, while the characteristics of other frequency bands are normal, it determines that the pollution characteristic type is particulate matter accumulation pollution; when the amplitude characteristics of the frequency band are abnormally increased and the phase characteristic offset exceeds the preset organic matter adsorption threshold, while the characteristics of other frequency bands are normal, it determines that the pollution characteristic type is organic matter adsorption pollution; when the amplitude characteristics of the low-frequency band are continuously increased and the phase characteristic offset exceeds the preset scaling characteristic threshold, while the characteristics of other frequency bands are normal, it determines that the pollution characteristic type is inorganic salt scaling pollution. When the number of abnormal frequency bands is not unique, it is determined that there is a corresponding combination of pollution.

[0035] Understandably, the wastewater diagnostic module utilizes the differences in response to various types of pollution using impedance signals of different frequencies to accurately determine the type of pollution characteristics. The high-frequency, mid-frequency, and low-frequency AC voltage excitation output by the sweep frequency signal generator addresses the sensitive characteristics of three types of pollution: particulate matter accumulation, organic matter adsorption, and inorganic salt scaling. Therefore, by performing multi-band decomposition on the standard impedance spectrum time series data, impedance time series data corresponding to different types of pollution can be separated, thereby determining whether the corresponding pollution exists. If multiple frequency bands show abnormalities simultaneously, it can be determined as combined pollution, achieving comprehensive identification of various types of pollution and combined pollution.

[0036] Specifically, the preset thresholds for particulate matter impact, organic matter adsorption, and scaling characteristics are all determined through a limited number of tests during the initial system commissioning phase. During initial system operation, with the membrane modules in a clean and uncontaminated state, impedance amplitude and phase characteristics at each frequency band are first collected to determine the normal amplitude baseline and normal fluctuation range for each band. Then, single-polluted wastewater simulating particulate matter accumulation, organic matter adsorption, and inorganic salt scaling, as well as combined polluted wastewater at different proportions, are prepared, progressively changing the pollution level. Simultaneously, impedance amplitude and phase characteristic shift data for each frequency band are collected under different pollution conditions. Through fitting analysis of the experimental data and calibration of the pollution critical state, the critical phase characteristic shift and amplitude abnormal increase judgment criteria that can effectively distinguish various types of pollution are determined, ultimately forming the preset thresholds for the corresponding pollution types. Generally, the preset particulate matter impact threshold is 5°, the preset organic matter adsorption threshold is 8°, and the preset scaling characteristic threshold is 10°.

[0037] For the determination of combined pollution, when the characteristics of two or three frequency bands are abnormal at the same time, it is determined to be combined pollution of the pollution type associated with the corresponding frequency band. For example, when the characteristics of high frequency and mid frequency bands are abnormal at the same time, and the characteristics of low frequency band are normal, it is determined to be a combined pollution of particulate matter accumulation and organic matter adsorption; when the characteristics of all three frequency bands are abnormal, it is determined to be a combined pollution of three types of pollution.

[0038] In this invention, the wastewater diagnostic module accurately identifies various single and combined pollutants, providing strong support for the precise actions of the subsequent adaptive execution module, ensuring that the system can respond to various pollution situations in a timely manner and maintain stable treatment and reuse effects.

[0039] During implementation, in the initial debugging phase of the system, a limited number of tests were conducted on each processing unit under clean conditions. When the processing unit was in a standard operating condition without pollution, amplitude characteristic data of high frequency, medium frequency and low frequency bands were collected. The baseline of clean status corresponding to the processing unit was formed by averaging the test data.

[0040] The wastewater diagnostic module normalizes the three types of amplitude characteristic changes based on the changes in amplitude characteristics of each frequency band to unify the numerical scale, eliminate the calculation deviation caused by the difference in amplitude numerical range of different frequency bands, and combine the normalized changes of each frequency band to calculate their arithmetic mean, finally obtaining a pollution degree parameter that can comprehensively reflect the overall pollution status of the treatment unit.

[0041] It should be understood that after normalization, the amplitude characteristics of the three frequency bands have been standardized on a unified numerical scale, and each frequency band independently corresponds to a pollution area and has equal representational status. Using the arithmetic mean can objectively reflect the overall state dominated by pollution in a single area when there is single pollution, and similarly, it can balance and integrate pollution information from multiple areas when there is combined pollution, accurately reflecting the degree of pollution accumulation across the entire region.

[0042] Specifically, the wastewater diagnostic module determines the pollution level as low pollution if the pollution level parameter is below the low pollution threshold; it determines the pollution level as medium pollution if the pollution level parameter is between the low pollution threshold and the high pollution threshold; and it determines the pollution level as high pollution if the pollution level parameter is above the high pollution threshold.

[0043] In implementation, the determination of low and high pollution thresholds involves gradually increasing the amount of pollutants added to the treatment unit while it is in a clean and pollution-free state. This simulates a continuous change in pollution level from mild to severe, and the pollution level parameter is determined simultaneously for each level. As the pollutant dosage increases, key nodes indicating significant changes in the treatment unit's operating status are recorded. When the pollutant dosage reaches a certain value, a noticeable decrease in the reuse flow rate begins, or the frequency of self-cleaning actions needs to be increased accordingly. The pollution level parameter value corresponding to this node is then designated as the low pollution threshold. The pollutant dosage continues to increase until the treatment unit approaches its operational limit, at which point self-cleaning actions can no longer effectively restore the operating state. The pollution level parameter value corresponding to this limit node is then designated as the high pollution threshold.

[0044] Through comprehensive analysis of multiple sets of experimental data, specific values ​​for low-pollution and high-pollution thresholds that can effectively distinguish different pollution stages were finally determined. In one exemplary embodiment, the low-pollution threshold is 0.3, and the high-pollution threshold is 0.7.

[0045] In this invention, the continuously changing pollution level parameter is discretized into a finite number of pollution levels, providing a clear decision-making basis for the adaptive execution module. Different pollution levels correspond to different self-cleaning action execution intensities and reuse flow rate adjustment ranges. Through this hierarchical processing method, the system can ensure treatment effectiveness while avoiding excessive intervention, thus optimizing energy and reagent consumption.

[0046] In practice, for pretreatment stage reaction tanks, when the pollution characteristics include a combination of particulate matter accumulation, a rotary spray mechanism is matched; when the pollution characteristics include a combination of organic matter adsorption, a chemical cleaning spray mechanism is matched; and when the pollution characteristics include a combination of inorganic salt scaling, a mechanical scraper mechanism is matched.

[0047] For filtration membrane modules, when the fouling characteristics include a combination of particulate matter accumulation, an air-water backwashing mechanism is used; when the fouling characteristics include a combination of organic matter adsorption, a vibration desorption mechanism or a chemically enhanced backwashing mechanism is used; and when the fouling characteristics include a combination of inorganic salt scaling, a chemically enhanced backwashing mechanism is used.

[0048] For the deep treatment adsorption unit, when the pollution characteristics include a combination of particulate matter accumulation, a backwashing mechanism is matched; when the pollution characteristics include a combination of organic matter adsorption or a combination of inorganic salt scaling, the deep treatment adsorption unit has no directly corresponding physical actuator, indicating external intervention.

[0049] Specifically, the parameters corresponding to each pollution level were determined through a limited number of tests during the initial system commissioning phase. Simulated wastewater of different concentrations was prepared to simulate the three pollution levels, and self-cleaning tests were conducted at different execution intensities. The time required for the dynamic purification impedance spectrum characteristic value of the treatment unit to recover to the stable operating threshold range after self-cleaning, as well as the corresponding cleaning agent consumption, were recorded. Through comparative analysis, the execution intensity with the shortest time or lowest consumption was determined as the execution intensity level corresponding to that operating condition, with time taking precedence over consumption.

[0050] For low pollution levels corresponding to a single abnormal frequency band, use the low-intensity execution level; for medium pollution levels corresponding to a single abnormal frequency band, use the medium-intensity execution level; for high pollution levels corresponding to a single abnormal frequency band, use the high-intensity execution level; for combined pollution corresponding to multiple abnormal frequency bands, increase the execution intensity by one level based on the same pollution level. If the execution intensity corresponding to a single pollution level is high, for combined pollution, increase the execution intensity to the ultra-high intensity level, which is the highest execution intensity for self-cleaning. Considering both cleaning effect and equipment protection, physical cleaning parameters should not exceed 120% of the rated value of the intensity level corresponding to high pollution, chemical cleaning parameters should not exceed 110%, and the duration of a single ultra-high intensity self-cleaning operation should not exceed 30 minutes.

[0051] The self-cleaning execution instructions generated by the adaptive execution module contain clearly defined targets and action requirements. For example, when particulate matter buildup and contamination at a medium level occur in the pretreatment stage reactor, the self-cleaning execution instruction could be described as activating the rotary spray mechanism of the pretreatment stage reactor to perform medium-intensity rotary spraying.

[0052] In practice, the preset reuse rate is based on the reuse rate data of the system under various operating conditions in historical data that can operate stably and meet the ultrapure water quality requirements. By fitting and analyzing the experimental data, the correspondence between different pollution levels and the corresponding maximum reuse rate is determined.

[0053] The adaptive execution module matches the pollution level of each processing unit with the corresponding maximum reuse rate based on the relationship between different pollution levels. This determines the maximum allowable reuse rate for each processing unit, calculates the difference between the actual reuse flow and the corresponding maximum reuse rate, clarifies the specific range of reuse flow that needs to be adjusted for each processing unit, and finally generates a reuse flow adjustment command. This command drives the corresponding adjustment mechanism to adjust the reuse flow of each processing unit to a range that matches the maximum reuse rate. This achieves differentiated and precise adjustment of the reuse flow, ensuring that the reuse flow always matches the pollution state of the processing unit. This guarantees the treatment quality of ultrapure water while making rational use of water resources, maintaining a stable and efficient operating state for the system.

[0054] Specifically, the adaptive execution module verifies the effectiveness of the self-cleaning action and the recycle flow adjustment, ensuring that the system can return to normal operation after completing self-cleaning. After the self-cleaning action and recycle flow adjustment are completed, this module re-receives the dynamic purification impedance spectrum characteristic values ​​of each processing unit collected and calculated by the sensor network module. It compares these newly determined characteristic values ​​with the preset stable operating threshold range one by one, determines whether the self-cleaning effect meets the standard based on the comparison results, and generates corresponding subsequent instructions.

[0055] After the self-cleaning action and reuse flow adjustment are completed, the adaptive execution module compares the newly determined dynamic purification impedance spectrum characteristic values ​​of each processing unit with the aforementioned stable operating threshold range. If the characteristic value of any processing unit still does not fall within the stable operating threshold range, it indicates that the self-cleaning action has not completely removed the contamination of that unit, or that new disturbances have occurred during the self-cleaning process, preventing it from returning to normal. In this case, the adaptive execution module determines that the self-cleaning effect has not met the standard and enters the next round of adjustment process. Conversely, it indicates that the self-cleaning action has effectively removed the contamination and the system has returned to a clean and stable state. In this case, the adaptive execution module determines that the self-cleaning effect has met the standard and generates a recovery command to send to the reuse flow adjustment actuator of each processing unit to restore the reuse flow to the rated value, so that the system can run at maximum efficiency again.

[0056] Specifically, the adaptive execution module re-determines the intensity of the self-cleaning action and the adjustment range of the reuse flow rate based on the difference between the current pollution level parameter and the low pollution threshold.

[0057] In this embodiment, the deviation is quantified by calculating the difference between the current pollution level parameter and the low pollution threshold, and then dividing this difference by the low pollution threshold to obtain the normalized deviation ratio. For example, when the low pollution threshold is set to 0.3, if the current pollution level parameter of a certain processing unit is 0.45, then its difference from the low pollution threshold is 0.15, and the deviation ratio is 50%. This deviation ratio reflects the distance between the current pollution state and the boundary of the low pollution level. The larger the deviation, the more serious the pollution and the higher the degree of failure to meet the self-cleaning standard.

[0058] The adjusted self-cleaning action intensity is determined linearly based on the deviation ratio, specifically by multiplying the original self-cleaning action intensity by a coefficient of (1 + deviation ratio). For example, when the deviation ratio is 50%, the intensity increases by 50%; when the deviation ratio is 100%, the intensity increases by 100%. The intensity is reflected in the specific operating parameters of the physical actuators: for rotary spray mechanisms, it's spray pressure and rotation speed; for mechanical scraper mechanisms, it's scraper speed and scraping frequency; for chemical cleaning spray mechanisms, it's cleaning agent concentration and dosage; for air-water backwash mechanisms, it's backwash air pressure, backwash water pressure, and backwash duration; for vibration desorption mechanisms, it's vibration frequency and vibration duration; for chemically enhanced backwash mechanisms, it's cleaning agent concentration and soaking time; and for backflushing mechanisms, it's backflushing flow rate and rinsing duration.

[0059] The adjusted reuse flow rate is also determined linearly based on the deviation ratio. Specifically, it is a further reduction of (deviation ratio × rated flow rate) from the original adjusted reuse flow rate. For example, when the rated flow rate is 100m³... 3 / h, the current adjusted flow rate is 70m³ / h 3 / h, when the deviation ratio is 50%, then at 70m 3 Reduce by 50m based on / h. 3 / h to 20m 3 / h; when the deviation ratio is 100%, then at 70m 3 Reduce by another 100m based on / h 3 / h, until the lower limit of traffic is reached. If the traffic is lower than the protection threshold after the adjustment, the protection threshold will be applied.

[0060] The adaptive execution module generates a new round of self-cleaning execution commands and reuse flow adjustment commands based on the redefined adjusted parameters, driving the corresponding mechanisms to perform actions again. This process is repeated cyclically, with the contamination level parameters recalculated and the self-cleaning effect reassessed after each cycle, until the contamination level parameters are reduced below the low contamination threshold, at which point the system returns to a stable operating state. Through this dynamic adjustment mechanism based on the degree of deviation, the system can adaptively respond to different levels of contamination residue, intervening with the most appropriate intensity, avoiding repeated ineffective self-cleaning due to insufficient adjustment, or resource waste due to excessive adjustment.

[0061] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0062] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications, characterized in that, include: A sensor network module is used to collect the current response signal applied to each processing unit in order to determine the dynamic purification impedance spectrum characteristic value of each processing unit. The processing unit includes a pretreatment stage reaction vessel, a filtration stage membrane module, and a deep treatment stage adsorption unit. Impedance signal processing module, which is used to compensate the characteristic values ​​of each dynamic purification impedance spectrum, and to identify and remove abnormal data to obtain standard impedance spectrum time series data. The wastewater diagnostic module is used to perform frequency band decomposition and analysis on the standard impedance spectrum time series data, extract the impedance characteristics of each frequency band to combine and determine the pollution characteristic type, and calculate the pollution degree parameter based on the amplitude change of the impedance characteristics to determine the pollution level. An adaptive execution module is used to determine the processing unit that needs to initiate a self-cleaning action, determine the execution intensity of the self-cleaning action according to the contamination level, generate a self-cleaning execution command to drive the physical execution mechanism of the corresponding processing unit to perform differentiated self-cleaning actions, and determine the current maximum allowable reuse rate and the reuse flow rate that needs to be adjusted according to the contamination level, and generate a reuse flow rate adjustment command. Furthermore, after the action is executed, the current response signal is re-acquired to redetermine the characteristic value of the dynamic purification impedance spectrum, confirm whether the self-cleaning effect meets the standard, and if the self-cleaning effect does not meet the standard, the parameters are adjusted again according to the current degree of contamination until the system returns to a stable operating state. If the self-cleaning effect meets the standard, the rated reuse flow rate of each treatment unit is restored.

2. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 1, characterized in that, The sensor network module includes: A plurality of impedance sensors are provided, each of which is fixedly disposed at the inlet and outlet of the corresponding processing unit. Each impedance sensor includes at least two electrode bodies made of inert conductive material. A sweep frequency signal generator is electrically connected to each of the impedance sensors to output a multi-frequency AC voltage excitation with a gradient frequency to each of the impedance sensors. A current acquisition unit is electrically connected to each of the impedance sensors to acquire the current response signal flowing through the electrode body under the multi-frequency AC voltage excitation, and convert the current response signal into digital raw impedance data. The eigenvalue calculation unit is used to calculate the dynamic purification impedance spectrum eigenvalues ​​of each processing unit based on the original impedance data.

3. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 2, characterized in that, The impedance signal processing module filters the dynamic purification impedance spectrum feature values ​​and performs temperature compensation on the filtered feature values ​​to generate initial impedance spectrum time series data. Furthermore, the initial impedance spectrum time series data corresponding to the impedance sensors at the inlet and outlet of each upstream and downstream associated processing unit are cross-validated for consistency. Abnormal data are identified and removed based on the correlation between upstream and downstream data to obtain the standard impedance spectrum time series data.

4. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 3, characterized in that, The wastewater diagnostic module performs multi-band decomposition on the standard impedance spectrum time series data, separates high-frequency, mid-frequency and low-frequency impedance time series data, and extracts the amplitude and phase characteristics of the impedance time series data of each frequency band respectively. Among them, when the amplitude characteristic of the high-frequency band increases abnormally and the phase characteristic offset is less than the preset particulate matter impact threshold, while the characteristics of other frequency bands are normal, the pollution characteristic type is determined to be particulate matter accumulation pollution. When the amplitude characteristic of the mid-frequency band increases abnormally and the phase characteristic shift exceeds the preset organic matter adsorption threshold, while the characteristics of other frequency bands are normal, it is determined that the pollution characteristic type is organic matter adsorption pollution. When the amplitude characteristic of the low frequency band continues to increase and the phase characteristic offset exceeds the preset scaling characteristic threshold, while the characteristics of other frequency bands are normal, it is determined that the pollution characteristic type is inorganic salt scaling pollution. When the number of abnormal frequency bands is not unique, it is determined that there is a corresponding combination of pollution.

5. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 4, characterized in that, The wastewater diagnostic module calculates the change in amplitude characteristics of each frequency band and the corresponding treatment unit's cleanliness baseline based on the high-frequency, mid-frequency, and low-frequency amplitude characteristics of each treatment unit. The pollution level parameter is obtained by normalizing the amplitude characteristic changes in the high-frequency band, the mid-frequency band, and the low-frequency band, and then combining them for calculation.

6. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 5, characterized in that, The wastewater diagnostic module determines the corresponding pollution level based on the pollution degree parameter; Wherein, in response to the pollution level parameter being lower than the low pollution threshold, it is determined to be a low pollution level; If the pollution level parameter is between the low pollution threshold and the high pollution threshold, it is determined to be a medium pollution level. If the pollution level parameter is higher than the high pollution threshold, it is determined to be a high pollution level.

7. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 6, characterized in that, The adaptive execution module determines the processing unit that needs to initiate a self-cleaning action based on the pollution characteristic type, determines the physical execution mechanism of the self-cleaning action based on the pollution characteristic type, and determines the execution intensity of the self-cleaning action based on the pollution level and the number of pollution characteristic types. The self-cleaning execution instruction generated by the adaptive execution module includes a processing unit, a physical execution mechanism for the self-cleaning action, and the execution intensity.

8. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 7, characterized in that, The adaptive execution module determines the maximum allowed reuse rate based on the pollution level and the preset reuse rate, obtains the actual reuse flow of each processing unit, calculates the difference between the actual reuse flow and the maximum allowed reuse rate, determines the reuse flow that needs to be adjusted, and generates the reuse flow adjustment command to adjust the reuse flow.

9. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 8, characterized in that, After the self-cleaning action is executed and the reuse flow is adjusted, the adaptive execution module receives the redefined dynamic purification impedance spectrum characteristic values ​​of each processing unit, and compares the redefined dynamic purification impedance spectrum characteristic values ​​with the preset stable operation threshold range to confirm whether the self-cleaning effect meets the standard. In response to the dynamic purification impedance spectrum characteristic values ​​of each processing unit recovering to the preset stable operating threshold range, the self-cleaning effect is determined to be up to standard, and a recovery command is generated to restore the rated reuse flow of each processing unit. If the dynamic purification impedance spectrum characteristic value of any processing unit fails to recover to the preset stable operating threshold range, the self-cleaning effect is determined to be substandard. The preset stable operation threshold range is the amplitude and phase characteristics corresponding to the non-pollution characteristic type.

10. The integrated system for ultrapure water treatment and dynamic wastewater reuse for new energy applications according to claim 9, characterized in that, In response to the determination that the self-cleaning effect has not met the standard, the adaptive execution module re-determines the intensity of the self-cleaning action and the adjustment range of the reuse flow rate based on the difference between the current pollution level parameter and the low pollution threshold.

Images